cupyx.scipy.signal.lombscargle#

cupyx.scipy.signal.lombscargle(x, y, freqs)[source]#

Computes the Lomb-Scargle periodogram.

The Lomb-Scargle periodogram was developed by Lomb 1 and further extended by Scargle 2 to find, and test the significance of weak periodic signals with uneven temporal sampling.

When normalize is False (default) the computed periodogram is unnormalized, it takes the value (A**2) * N/4 for a harmonic signal with amplitude A for sufficiently large N.

When normalize is True the computed periodogram is normalized by the residuals of the data around a constant reference model (at zero).

Input arrays should be one-dimensional and will be cast to float64.

Parameters

x (array_like) – Sample times.
y (array_like) – Measurement values.
freqs (array_like) – Angular frequencies for output periodogram.
precenter (bool, optional) – Pre-center amplitudes by subtracting the mean.
normalize (bool, optional) – Compute normalized periodogram.

Returns

pgram – Lomb-Scargle periodogram.

Return type

array_like

Raises

ValueError – If the input arrays x and y do not have the same shape.

Notes

This subroutine calculates the periodogram using a slightly modified algorithm due to Townsend 3 which allows the periodogram to be calculated using only a single pass through the input arrays for each frequency. The algorithm running time scales roughly as O(x * freqs) or O(N^2) for a large number of samples and frequencies.

References

1: N.R. Lomb “Least-squares frequency analysis of unequally spaced data”, Astrophysics and Space Science, vol 39, pp. 447-462, 1976
2: J.D. Scargle “Studies in astronomical time series analysis. II - Statistical aspects of spectral analysis of unevenly spaced data”, The Astrophysical Journal, vol 263, pp. 835-853, 1982
3: R.H.D. Townsend, “Fast calculation of the Lomb-Scargle periodogram using graphics processing units.”, The Astrophysical Journal Supplement Series, vol 191, pp. 247-253, 2010