Gts.trajectory

class pyacs.gts.Gts.Gts(code=None, lat=None, lon=None, h=None, X0=None, Y0=None, Z0=None, t0=None, data=None, data_xyz=None, data_corr_neu=None, data_corr_xyz=None, offsets_dates=[], offsets_values=None, outliers=[], annual=None, semi_annual=None, velocity=None, ifile=None, log=None, metadata=None)[source]
trajectory(model_type, offset_dates=[], eq_dates=[], H_fix={}, H_constraints={}, H_bounds={}, component='NEU', verbose=False)

Estimate parameters of a (non-linear) trajectory model for the time series.

Model: y(t) = trend + annual + semi-annual + offsets + post-seismic (psd_log).

Parameters:

  • model_type (str) – String of key-word parameters to estimate: ‘trend’, ‘annual’, ‘semi-annual’, ‘seasonal’, ‘offset’, ‘psd_log’. E.g. ‘trend-seasonal-offset-psd_log’ for full model.

  • offset_dates (list, optional) – List of offset dates in decimal year.

  • eq_dates (list, optional) – List of earthquake dates for post-seismic (psd_log) estimation.

  • H_fix (dict, optional) – Parameters to fix, e.g. {‘psd_log_offset_00’: [10., 15., 0.], ‘psd_log_tau_00’: [100., 100., 100.]}.

  • H_constraints (dict, optional) – Parameters to constrain (center, sigma), e.g. {‘psd_log_tau_01’: [[500., 50], [500., 50], [500., 50]]}.

  • H_bounds (dict, optional) – Bounds, e.g. {‘psd_log_tau_02’: [[2*365., 3*365.], …]}.

  • component (str, optional) – Components to estimate (‘NEU’ or subset).

  • verbose (bool, optional) – Verbose mode.

Returns:

(results_dict, model_Gts, residual_Gts, daily_predictions_Gts). Unlike most pyacs.gts functions, trajectory returns these 4 elements.

Return type:

tuple