pygwb.preprocessing.self_gate_data
- pygwb.preprocessing.self_gate_data(time_series_data: TimeSeries, tzero: float = 1.0, tpad: float = 0.5, gate_threshold: float = 50.0, cluster_window: float = 0.5, whiten: bool = True, gates: SegmentList | None = None)[source]
Function to self-gate data to be used in the stochastic pipeline.
- Parameters:
time_series_data (
gwpy.timeseries.TimeSeries) – Timeseries data to be analysed in the pipeline.tzero (
int, optional) – Half-width time duration (seconds) in which the timeseries is set to zero. Default is 1.0.tpad (
int, optional) – Half-width time duration (seconds) in which the Planck window is tapered. Default is 0.5.whiten (
bool, optional) – If True, data will be whitened before gating points are discovered, use of this option is highly recommended. Default is True.gate_threshold (
float, optional) – Amplitude threshold, if the data exceeds this value a gating window will be placed. Default is 50.0.cluster_window (
float, optional) – Time duration (seconds) over which gating points will be clustered. Default is 0.5.gates (
gwpy.segments.SegmentList, optional) – Argument where gates can be explicitly given to this function. Those gates would then be applied to the timeseries data. If not applied, equal to None.
- Returns:
- gated:
gwpy.timeseries.TimeSeries TimeSeries containing the gated data.
- deadtime:
gwpy.segments.SegmentList SegmentList containing the times that were gated, not including any padding applied.
- gated: