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11.5.1.1. astroML.time_series.lomb_scargle

astroML.time_series.lomb_scargle()

(Generalized) Lomb-Scargle Periodogram with Floating Mean

Parameters :

t : array_like

sequence of times

y : array_like

sequence of observations

dy : array_like

sequence of observational errors

omega : array_like

frequencies at which to evaluate p(omega)

generalized : bool

if True (default) use generalized lomb-scargle method otherwise, use classic lomb-scargle.

subtract_mean : bool

if True (default) subtract the sample mean from the data before computing the periodogram. Only referenced if generalized is False.

significance : None or float or ndarray

if specified, then this is a list of significances to compute for the results.

Returns :

p : array_like

Lomb-Scargle power associated with each frequency omega

z : array_like

if significance is specified, this gives the levels corresponding to the desired significance (using the Scargle 1982 formalism)

Notes

The algorithm is based on reference [R21]. The result for generalized=False is given by equation 4 of this work, while the result for generalized=True is given by equation 20.

Note that the normalization used in this reference is different from that used in other places in the literature (e.g. [R22]). For a discussion of normalization and false-alarm probability, see [R21].

To recover the normalization used in Scargle [R23], the results should be multiplied by (N - 1) / 2 where N is the number of data points.

References

[R21](1, 2, 3)
  1. Zechmeister and M. Kurster, A&A 496, 577-584 (2009)
[R22](1, 2)
  1. Press et al, Numerical Recipies in C (2002)
[R23](1, 2) Scargle, J.D. 1982, ApJ 263:835-853