11.5.1.2. astroML.time_series.lomb_scargle_bootstrap¶
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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