Spectral methods

The basics: Fourier analysis

\[\mathcal{F}\{x(t)\} = \int_{-\infty}^{\infty} x(t)\exp(-j2 \pi ft)dt\]

The Lomb-Scargle periodogram

class periodicity.spectral.BGLST

Bases: object

class periodicity.spectral.GLS(fmin=None, fmax=None, n=5, psd=False)

Bases: object

References

1

Press W.H. and Rybicki, G.B, “Fast algorithm for spectral analysis of unevenly sampled data”. ApJ 1:338, p277, 1989

2

13. Zechmeister and M. Kurster, A&A 496, 577-584 (2009)

3

23. Press et al, Numerical Recipes in C (2002)

bootstrap(n_bootstraps, random_seed=None)

copy()

fal(fap)

fap(power)

fap_level: array-like, optional

List of false alarm probabilities for which you want to calculate approximate levels. Can also be passed as a single scalar value.

model(tf, f0)

Compute the Lomb-Scargle model fit at a given frequency

Parameters

• tf (float or array-like) – The times at which the fit should be computed

• f0 (float) – The frequency at which to compute the model

Returns

yf – The model fit evaluated at each value of tf

Return type

ndarray

window()

References and additional reading

Vanderplas 2018. Understanding the Lomb-Scargle Periodogram. ApJS, 236, 16.