hermite_spline_normalization

HermiteSplineNormalization

Bases: SignalFilter

fs = signals.fs instance-attribute

peaks_distance_scale = signals.peaks_distance_scale instance-attribute

__init__(signals)

filter()

Normalizes signal using Cubic Hermite Splines fitted to the amplitude bounds (maxima and minima) of the signal.

Distance between min and max peaks determined as fraction of the median frequency.

Returns:

Type	Description
ndarray	np.ndarray: Normalized EGMs.

find_extended_peaks(signal, distance) staticmethod

Find peaks and add 0 and len(signal) - 1 as peaks without duplication

Parameters:

Name	Type	Description	Default
signal	ndarray[N]	Input signal.	required
distance	float	Minimal distance between peaks.	required

Returns:

Name	Type	Description
tuple	tuple[ndarray, ndarray]	Extended peaks and signal values at the peaks.

hermite_spline_bound(signal, distance) staticmethod

Find peaks and interpolate with CubicHermiteSpline

Parameters:

Name	Type	Description	Default
signal	ndarray[N]	Input signal.	required
distance	float	Minimal distance between peaks.	required

Returns:

Type	Description
ndarray	np.ndarray[N,]: Interpolated amplitudes.

lower_upper_bounds(distances)

Interpolates lower and upper bounds of the signal(s) using Cubic Hermit Spline.

Parameters:

Name	Type	Description	Default
distances	(ndarray[N], float)	Minimum distance between peaks.	required

Returns:

Type	Description
tuple[ndarray, ndarray]	lower_bounds, upper_bounds (tuple): Lower and upper bounds of the signals.