cedalion.sigproc.frequency

Frequency-related signal processing methods.

Functions

freq_filter(timeseries, fmin, fmax[, ...])	Apply a Butterworth bandpass frequency filter.
sampling_rate(timeseries)	Estimate the sampling rate of the timeseries.

cedalion.sigproc.frequency.sampling_rate(

timeseries: Annotated[DataArray, DataArraySchema(dims='time', coords='time', 'time', 'samples')],

) → Quantity

Estimate the sampling rate of the timeseries.

Note

This functions assumes uniform sampling.

Parameters:

timeseries (NDTimeSeries, (time,*)) – the input time series

Returns:

The sampling rate estimated by averaging time differences between samples.

cedalion.sigproc.frequency.freq_filter(

timeseries: Annotated[DataArray, DataArraySchema(dims='time', coords='time', 'time', 'samples')],

fmin: Annotated[Quantity, '[frequency]'],

fmax: Annotated[Quantity, '[frequency]'],

butter_order: int = 4,

) → Annotated[DataArray, DataArraySchema(dims='time', coords='time', 'time', 'samples')]

Apply a Butterworth bandpass frequency filter.

Parameters:

• timeseries (NDTimeSeries, (time,*)) – the input time series

• fmin (Quantity, [frequency]) – lower threshold of the pass band

• fmax (Quantity, [frequency]) – higher threshold of the pass band

• butter_order – order of the filter

Returns:

The frequency-filtered time series