pyacs.gts.lib.l1trend.simplification module

Simplification functions for L1-trend filtered time series.

pyacs.gts.lib.l1trend.simplification.simplify_l1trend(self, tolerance=0.5, components='ENU')[source]

Remove unnecessary breakpoints from an L1-trend filtered time series.

This function iteratively removes breakpoints and tests if the simplified model still fits the original time series within a specified tolerance.

Parameters:
  • tolerance (float) – Maximum allowed difference (in mm) between original and simplified model. Default is 0.5 mm.

  • components (str) – Components to process. Default is ‘ENU’.

Returns:

Simplified Gts object with unnecessary breakpoints removed.

Return type:

pyacs.gts.Gts.Gts

pyacs.gts.lib.l1trend.simplification.simplify_l1trend_with_fisher_test(self, rawts, components='ENU', alpha=0.05)[source]

Simplify an L1-trend filtered time series by comparing to the unfiltered time series using Fisher-Snedecor tests.

This function iteratively removes breakpoints and tests their usefulness by comparing the fit quality with and without each breakpoint using Fisher-Snedecor tests.

Parameters:
  • rawts (pyacs.gts.Gts.Gts) – The unfiltered (raw) time series to compare against.

  • components (str) – Components to process. Default is ‘ENU’.

  • alpha (float) – Significance level for the Fisher-Snedecor test. Default is 0.05.

Returns:

Simplified Gts object with unnecessary breakpoints removed.

Return type:

pyacs.gts.Gts.Gts