skdh.features.RangePowerSum#

class skdh.features.RangePowerSum(padlevel=2, low_cutoff=0.0, high_cutoff=5.0, demean=False, use_modulus=False, normalize=False)#

Sum of power spectral density values within the specified range. Can be normalized to the power spectral sum across the entire frequency range.

Parameters:

padlevelint, optional: Padding (factors of 2) to use in the FFT computation. Default is 2.
low_cutofffloat, optional: Low value of the frequency range. Default is 0.0 Hz
high_cutofffloat, optional: High value of the frequency range. Default is 5.0 Hz
demeanbool, optional: Demean (ignore 0 frequency component). Default is False.
use_modulusbool, optional: Use modulus instead of power. Default is False
normalizebool, optional: Normalize the range power sum by the total power spectral sum. Default is False.

Attributes:

Methods

compute(signal[, fs, axis])

Compute the power spectral density sum within the specified range.

Notes

The padlevel parameter effects the number of points to be used in the FFT computation by factors of 2. The computation of number of points is per

\[nfft = 2^{ceil(log_2(N)) + padlevel}\]

So padlevel=2 would mean that for a signal with length 150, the number of points used in the FFT would go from 256 to 1024.

compute(signal, fs=1.0, *, axis=-1)#

Compute the power spectral density sum within the specified range.

Parameters:

signalarray-like: Array-like containing values to compute the power spectral sum for.
fsfloat, optional: Sampling frequency in Hz. If not provided, default is assumed to be 1Hz.
axisint, optional: Axis along which the signal entropy will be computed. Ignored if signal is a pandas.DataFrame. Default is last (-1).

Returns: