skdh.features.DetailPower#
- class skdh.features.DetailPower(wavelet='coif4', freq_band=None)#
The summed power in the detail levels that span the chosen frequency band.
- Parameters:
- waveletstr
Wavelet to use. Options are the discrete wavelets in PyWavelets. Default is ‘coif4’.
- freq_bandarray_like
2-element array-like of the frequency band (Hz) to get the power in. Default is [1, 3].
- Attributes:
- f_band
- wave
Methods
compute(signal[, fs, axis])Compute the detail power
References
[1]Sekine, M. et al. “Classification of waist-acceleration signals in a continuous walking record.” Medical Engineering & Physics. Vol. 22. Pp 285-291. 2000.
- compute(signal, fs=1.0, *, axis=-1)#
Compute the detail power
- Parameters:
- signalarray-like
Array-like containing values to compute the detail power for.
- fsfloat, optional
Sampling frequency in Hz. If not provided, default is 1.0Hz.
- axisint, optional
Axis along which the signal entropy will be computed. Ignored if signal is a pandas.DataFrame. Default is last (-1).
- Returns:
- powernumpy.ndarray
Computed detail power.