jax.scipy.signal.welch#

jax.scipy.signal.welch(x, fs=1.0, window='hann', nperseg=None, noverlap=None, nfft=None, detrend='constant', return_onesided=True, scaling='density', axis=-1, average='mean')[source]#

Estimate power spectral density (PSD) using Welch’s method.

This is a JAX implementation of scipy.signal.welch(). It divides the input signal into overlapping segments, computes the modified periodogram for each segment, and averages the results to obtain a smoother estimate of the PSD.

Parameters:

  • x (Array) – Array representing a time series of input values.

  • fs (ArrayLike) – Sampling frequency of the inputs (default: 1.0).

  • window (str) – Data tapering window to apply to each segment. Can be a window function name, a tuple specifying a window length and function, or an array (default: 'hann').

  • nperseg (int | None | None) – Length of each segment (default: 256).

  • noverlap (int | None | None) – Number of points to overlap between segments (default: nperseg // 2).

  • nfft (int | None | None) – Length of the FFT used, if a zero-padded FFT is desired. If None (default), the FFT length is nperseg.

  • detrend (str) – Specifies how to detrend each segment. Can be False (default: no detrending), 'constant' (remove mean), 'linear' (remove linear trend), or a callable accepting a segment and returning a detrended segment.

  • return_onesided (bool) – If True (default), return a one-sided spectrum for real inputs. If False, return a two-sided spectrum.

  • scaling (str) – Selects between computing the power spectral density ('density', default) or the power spectrum ('spectrum')

  • axis (int) – Axis along which the PSD is computed (default: -1).

  • average (str) – The type of averaging to use on the periodograms; one of 'mean' (default) or 'median'.

Returns:

A length-2 tuple of arrays (f, Pxx). f is the array of sample frequencies, and Pxx is the power spectral density of x.

Return type:

tuple[Array, Array]

See also