ktk.filters.savgol

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ktk.filters.savgol#

savgol(ts, /, *, window_length, poly_order, deriv=0)[source]#

Apply a Savitzky-Golay filter on a TimeSeries.

Filtering occurs on the first axis (time). If the TimeSeries contains missing samples, a warning is issued, missing samples are interpolated using a first-order interpolation before filtering, and then replaced by np.nan in the filtered signal.

Parameters:

  • ts (TimeSeries) – Input TimeSeries

  • window_length (int) – The length of the filter window. window_length must be a positive odd integer less or equal than the length of the TimeSeries.

  • poly_order (int) – The order of the polynomial used to fit the samples. polyorder must be less than window_length.

  • deriv (int) – Optional. The order of the derivative to compute. The default is 0, which means to filter the data without differentiating.

Returns:

A copy of the input TimeSeries, which each data being filtered.

Return type:

TimeSeries

Raises:

ValueError – If sample rate is not constant, or if there is no data to filter.

See also

ktk.filters.smooth

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