cupyx.scipy.signal.periodogram#

cupyx.scipy.signal.periodogram(x, fs=1.0, window='boxcar', nfft=None, detrend='constant', return_onesided=True, scaling='density', axis=-1)[source]#

Estimate power spectral density using a periodogram.

Parameters:

x (array_like) – Time series of measurement values
fs (float, optional) – Sampling frequency of the x time series. Defaults to 1.0.
window (str or tuple or array_like, optional) – Desired window to use. If window is a string or tuple, it is passed to get_window to generate the window values, which are DFT-even by default. See get_window for a list of windows and required parameters. If window is array_like it will be used directly as the window and its length must be nperseg. Defaults to ‘boxcar’.
nfft (int, optional) – Length of the FFT used. If None the length of x will be used.
detrend (str or function or False, optional) – Specifies how to detrend each segment. If detrend is a string, it is passed as the type argument to the detrend function. If it is a function, it takes a segment and returns a detrended segment. If detrend is False, no detrending is done. Defaults to ‘constant’.
return_onesided (bool, optional) – If True, return a one-sided spectrum for real data. If False return a two-sided spectrum. Defaults to True, but for complex data, a two-sided spectrum is always returned.
scaling ({ 'density', 'spectrum' }, optional) – Selects between computing the power spectral density (‘density’) where Pxx has units of V**2/Hz and computing the power spectrum (‘spectrum’) where Pxx has units of V**2, if x is measured in V and fs is measured in Hz. Defaults to ‘density’
axis (int, optional) – Axis along which the periodogram is computed; the default is over the last axis (i.e. axis=-1).

Returns:

f (ndarray) – Array of sample frequencies.
Pxx (ndarray) – Power spectral density or power spectrum of x.