pyacs.gts.lib.outliers package


pyacs.gts.lib.outliers.find_l1trend module

pyacs.gts.lib.outliers.find_l1trend.find_l1trend(self, lam, threshold, period=None, gap=10, components='NE', plot=False, verbose=False, in_place=False)[source]
  • self – Gts instance

  • lam – lambda parameter for L1 trend filtering

  • threshold – All residuals with threshold * standard deviation will be flagged as outliers

  • period – period(s) for searching outliers. Could be a single of a list of periods.

  • gap – number of days to consider that there is a gap. Default is gap=10.

  • components – components used for outliers detection

  • plot – boolean. If True, will plot the filter result and the flagged outliers

  • verbose – boolean. Verbose mode.

  • in_place – boolean. if True, apply to the original Gts. Default is False, returning a new Gts


a new Gts instance if in_place is False or the current Gts

pyacs.gts.lib.outliers.find_outliers_around_date module

pyacs.gts.lib.outliers.find_outliers_around_date.find_outliers_around_date(self, date, conf_level=95, n=3, lcomponent='NE', verbose=True)[source]

Find an outlier around a given date returns the index of the outlier, returns [] if no outlier found :param date : given date :param conf_level : confidence level for F_ratio test of outlier significance (default 95%%) :param n : number of dates either sides of date (default n=3) :param lcomponent : components ‘N’,’E’,’U’,’NE’,’NEU’ (default ‘NE’)

pyacs.gts.lib.outliers.find_outliers_percentage module

pyacs.gts.lib.outliers.find_outliers_percentage.find_outliers_percentage(self, percentage=0.03, in_place=False, verbose=False, component='NEU', periods=None, excluded_periods=None)[source]

detrend a time series and ranks the residuals by increasing absolute value populate the outliers with the x % largest ones on each component

pyacs.gts.lib.outliers.find_outliers_simple module

pyacs.gts.lib.outliers.find_outliers_simple.find_outliers_simple(self, threshold=100, window_length=10, in_place=False, verbose=False, component='NEU', periods=None, excluded_periods=None)[source]

pyacs.gts.lib.outliers.find_outliers_sliding_window module

pyacs.gts.lib.outliers.find_outliers_sliding_window.find_outliers_sliding_window(self, threshold=3, in_place=False, verbose=True, periods=[[]], excluded_periods=[[]], component='NE', window_len=15, automatic=True)[source]

Find outliers using sliding windows

pyacs.gts.lib.outliers.find_outliers_vondrak module

pyacs.gts.lib.outliers.find_outliers_vondrak.find_outliers_vondrak(self, threshold=10, fc=2.0, in_place=False, verbose=True, periods=[[]], excluded_periods=[[]], component='NE')[source]

Find outliers using a Vondrak filter

pyacs.gts.lib.outliers.remove_outliers module

pyacs.gts.lib.outliers.remove_outliers.remove_outliers(self, periods=None, in_place=False)[source]

removes outliers provided in self.outliers return a new Gts without the outliers if in_place = True then self has the outliers removed as well (in _place)

Module contents