Gts.l1trend_to_breakpoints
- 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]
- l1trend_to_breakpoints(tol='auto', threshold=[1.0, 1.0, 5.0])
Convert a Gts resulting from a L1-trend-filtering to a dictionary of breakpoints. The breakpoints are computed by looking for significant changes in the slope of the time series.
- Parameters:
tol (float or 'auto') – Tolerance for detecting breakpoints in mm/yr. If ‘auto’, finds the greatest tol such that the max difference between interpolated breakpoints and the time series is below a threshold for each component.
threshold (list of floats) – List of thresholds in mm for each component (‘N’, ‘E’, ‘U’) to determine the best tolerance if tol is ‘auto’. Default is [1., 1., 5.] for ‘N’, ‘E’, and ‘U’ respectively. If tol is a float, this parameter is ignored.
- Returns:
bp – Dictionary with keys as component names (‘E’, ‘N’, ‘U’) and dates/values as bp[component][0], H_bp[component][1]
- Return type: