11.5.1.2. astroML.time_series.lomb_scargle_bootstrap

astroML.time_series.lomb_scargle_bootstrap(t, y, dy, omega, generalized=True, subtract_mean=True, N_bootstraps=100, random_state=None)[source]

Deprecated since version 0.4: The lomb_scargle_bootstrap function is deprecated and may be removed in a future version. Use astropy.stats.LombScargle.false_alarm_probability instead.

Use a bootstrap analysis to compute Lomb-Scargle significance

Parameters
The first set of parameters are passed to the lomb_scargle algorithm
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 lomb-scargle method otherwise, use classic lomb-scargle.

subtract_meanbool

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

Remaining parameters control the bootstrap

N_bootstrapsint

number of bootstraps

random_stateNone, int, or RandomState object

random seed, or random number generator

Returns
Dndarray

distribution of the height of the highest peak