pyacs.gts.lib.noise package

Submodules

Module contents

Pyacs noise package: wrappers for realistic uncertainties (tsfit, CATS, add_vel_sigma).

pyacs.gts.lib.noise.add_vel_sigma(self, b_fn=4, verbose=True)[source]

Estimate velocity uncertainties from residuals (white + flicker noise).

Velocity and residual time series must exist: run detrend(), detrend_annual(), or detrend_seasonal() first. Uncertainty on velocity components (N, E, U) is computed using white noise from the residual scatter and flicker noise (Williams, 2003, eq. 19 and 23). Returns a new Gts with velocity sigmas set.

Parameters:

  • b_fn (float, optional) – Flicker noise parameter in mm/yr^0.25. Default is 4.

  • verbose (bool, optional) – If True, print flicker noise variance. Default is True.

Returns:

New Gts with velocity uncertainties set in velocity[3:6] (m/yr), or None if self.velocity is not set.

Return type:

Gts or None

Notes

White noise is estimated from the first differences of the residual time series. The combined white + flicker sigma is scaled by component RMS so that the minimum component (N, E, or U) keeps the nominal flicker level.

References

Williams, S. D. P. (2003). The effect of coloured noise on the uncertainties of rates from geodetic time series. Journal of Geodesy, 76(9-10), 483-494.

pyacs.gts.lib.noise.get_spectral_index(cats_file)[source]
pyacs.gts.lib.noise.get_vel_and_sigma(cats_file)[source]
pyacs.gts.lib.noise.realistic_sigma(self, option='tsfit', in_place=False, verbose=False)[source]

Calculate realistic velocity uncertainties (GLOBK tsfit or CATS).

Parameters:

  • option (str, optional) – ‘tsfit’: GLOBK T. Herring realistic sigma; ‘cats_pl’: CATS with noise type (–model=pl:); ‘cats_seasonal_pl’: CATS with seasonal (–model=pl: –sinusoid=1y1); ‘cats_flicker’: CATS flicker (–model=pl:k-1); ‘cats_seasonal_flicker’: CATS seasonal + flicker.

  • in_place (bool, optional) – If True, update Gts in place.

  • verbose (bool, optional) – Verbose mode.

Returns:

self (possibly with updated velocity uncertainties) or result of CATS/tsfit.

Return type:

Gts or None

pyacs.gts.lib.noise.sigma_cats(self, in_place=False, verbose=False, k='k-1', seasonal='')[source]

Run CATS to obtain realistic velocity uncertainties.

Parameters:

  • in_place (bool, optional) – If True, update Gts in place.

  • verbose (bool, optional) – Verbose mode.

  • k (str, optional) – CATS noise model (e.g. ‘k-1’ for flicker).

  • seasonal (str, optional) – Seasonal option for CATS.

Returns:

self or result from CATS run.

Return type:

Gts or None

pyacs.gts.lib.noise.sigma_vel_tsfit(self, in_place=False, verbose=False)[source]

runs tsfit for getting realistic sigma

pyacs.gts.lib.noise.wrms(self)[source]

Return the weighted RMS of the time series (NEU).

Returns:

np.array([wrms_n, wrms_e, wrms_up]).

Return type:

ndarray