11.5.1.1. astroML.time_series.lomb_scargle¶

astroML.time_series.
lomb_scargle
(t, y, dy, omega, generalized=True, subtract_mean=True, significance=None)[source]¶ Deprecated since version 0.4: The lomb_scargle function is deprecated and may be removed in a future version. Use astropy.stats.LombScargle instead.
(Generalized) LombScargle Periodogram with Floating Mean
 Parameters
 tarray_like
sequence of times
 yarray_like
sequence of observations
 dyarray_like
sequence of observational errors
 omegaarray_like
frequencies at which to evaluate p(omega)
 generalizedbool
if True (default) use generalized lombscargle method otherwise, use classic lombscargle.
 subtract_meanbool
if True (default) subtract the sample mean from the data before computing the periodogram. Only referenced if generalized is False
 significanceNone or float or ndarray
if specified, then this is a list of significances to compute for the results.
 Returns
 parray_like
LombScargle power associated with each frequency omega
 zarray_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 [1]. 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. [2]). For a discussion of normalization and falsealarm probability, see [1].
To recover the normalization used in Scargle [3], the results should be multiplied by (N  1) / 2 where N is the number of data points.
References