pygwb.delta_sigma_cut.dsc_cut
- pygwb.delta_sigma_cut.dsc_cut(naive_sigma: ndarray, slide_sigma: ndarray, dsc: float = 0.2, bf_ss: float = 1, bf_ns: float = 1)[source]
Function that performs the delta sigma cut, a veto that marks certain GPS times as unusable if the estimation of the PSD in the naive (estimating sigma in bin J) and sliding (estimating sigma in bins J pm 1) differ by more than a certain threshold:
\[\frac{|\bar{\sigma}_{t, \alpha} b_{\rm avg} - \sigma_{t, \alpha} b_{\rm nav} |} {\bar{\sigma}_{t, \alpha} b_{\rm avg}}>{\rm threshold}\]- Parameters:
naive_sigma (
array_like) – Array containing the naive sigmas.slide_sigma (
array_like) – Array containing the sliding sigmas.dsc (
float, optional) – Threshold used for the delta sigma cut. Default is 0.2.bf_ss (
float, optional) – Bias factor for sliding sigmas. Default is 1.bf_ns (
float, optional) – Bias factor for naive sigmas. Default is 1.
- Returns:
- dsigma >= dsc:
bool Mask containing bools indicating whether the segment’s delta sigma exceeds the threshold value or not. True indicates that the corresponding GPS times were bad, whereas False denotes good GPS times.
- dsigma:
array_like Values of the difference between sliding sigma and naive sigma, i.e., the actual value of the delta sigma per segment.
- dsigma >= dsc: