pymodalib.algorithms.signals module¶

Basic signal operations, such as pre-processing and down-sampling.

generate_times(signal: numpy.ndarray, fs: float) → numpy.ndarray¶

Generates the time values associated with a signal, starting from t=0.

Parameters:	signal (ndarray) – The signal to generate time values for. fs (float) – The sampling frequency of the signal.
Returns:	times – The times associated with the signal.
Return type:	ndarray

preprocess(signal: numpy.ndarray, fs: float, fmin: Optional[float] = None, fmax: Optional[float] = None) → numpy.ndarray¶

Pre-processes a signal, performing filtering and de-trending.

Parameters:	signal (ndarray) – [1D array] The signal to pre-process. fs (float) – The sampling frequency of the signal. fmin (float, optional) – The minimum frequency for filtering. fmax (float, optional) – The maximum frequency for filtering.
Returns:	[1D array] The pre-processed signal.
Return type:	ndarray

resampl_flow(signal: numpy.ndarray, original_freq: float, resample_freq: float) → numpy.ndarray¶

Down-samples a signal, using a moving-average.

Parameters:	signal (ndarray) – [1D array] The signal to down-sample. original_freq (float) – The original sampling frequency of the signal. resample_freq (float) – The sampling frequency of the down-sampled signal.
Returns:	[1D array] The down-sampled signal.
Return type:	ndarray