pyheartlib.features

Module Contents

Functions

get_stat_features(data[, features])	Computes statistical features for the input samples.
get_hrv_features([rri, features, only_names])	Computes hrv features for the input samples.
get_wf_feats([sig, interval, only_names])	Computes features for the signal waveform.

pyheartlib.features.get_stat_features(data, features='all')

Computes statistical features for the input samples.

Parameters:

• data (numpy.array) – A 2D numpy array with shape (#samples,len_series).

• features (list) – A list of features to be computed.

Returns:

features_arr – A 2D numpy array with the shape (#samples, #features).

Return type:

numpy.array

pyheartlib.features.get_hrv_features(rri=None, features='all', only_names=False)

Computes hrv features for the input samples.

Parameters:

• rri (numpy.array) – A 2D numpy array with shape (#samples, len_series). Series are rr intervals in milliseconds(ms).

• features (list) – A list of features to be computed.

Returns:

features_arr – A 2D numpy array with the shape (#samples, #features).

Return type:

numpy.array

pyheartlib.features.get_wf_feats(sig=None, interval=None, only_names=False)

Computes features for the signal waveform.

The input signal is segmented into sub-signals based on the given interval parameter.

Parameters:

• sig (numpy.array) – A 1D numpy array.

• interval (int) – Length of subsegments.

Returns:

features_arr – A 2D numpy array with the shape (#subsegments, #features).

Return type:

numpy.array