lomb_scargle (pyleoclim.utils.spectral.lomb_scargle)¶

pyleoclim.utils.spectral.lomb_scargle(ys, ts, freq=None, freq_method='lomb_scargle', freq_kwargs=None, n50=3, window='hann', detrend=None, sg_kwargs=None, gaussianize=False, standardize=False, average='mean')[source]¶

Return the computed periodogram using lomb-scargle algorithm

Uses the lombscargle implementation from scipy.signal: https://scipy.github.io/devdocs/generated/scipy.signal.lombscargle.html#scipy.signal.lombscargle

Parameters

ys (array) – a time series
ts (array) – time axis of the time series
freq (str or array) – vector of frequency. If string, uses the following method:
freq_method (str) –
Method to generate the frequency vector if not set directly. The following options are avialable:
- log
- lomb_scargle (default)
- welch
- scale
- nfft
See utils.wavelet.make_freq_vector for details
freq_kwargs (dict) – Arguments for the method chosen in freq_method. See specific functions in utils.wavelet for details By default, uses dt=median(ts), ofac=4 and hifac=1 for Lomb-Scargle
n50 (int) – The number of 50% overlapping segment to apply
window (str or tuple) –
Desired window to use. Possible values:
boxcar

triang

blackman

hamming

hann (default)

bartlett

flattop

parzen

bohman

blackmanharris

nuttail

barthann

kaiser (needs beta)

gaussian (needs standard deviation)

general_gaussian (needs power, width)

slepian (needs width)

dpss (needs normalized half-bandwidth)

chebwin (needs attenuation)

exponential (needs decay scale)

tukey (needs taper fraction)
If the window requires no parameters, then window can be a string. If the window requires parameters, then window must be a tuple with the first argument the string name of the window, and the next arguments the needed parameters. If window is a floating point number, it is interpreted as the beta parameter of the kaiser window.
detrendstr
If None, no detrending is applied. Available detrending methods:

None - no detrending will be applied (default);

linear - a linear least-squares fit to ys is subtracted;

constant - the mean of ys is subtracted

savitzy-golay - ys is filtered using the Savitzky-Golay filters and the resulting filtered series is subtracted from y.

emd - Empirical mode decomposition
sg_kwargsdict
The parameters for the Savitzky-Golay filters. see pyleoclim.utils.filter.savitzy_golay for details.

gaussianizebool
If True, gaussianizes the timeseries

standardizebool
If True, standardizes the timeseriesprep_args : dict

average{‘mean’,’median’}
Method to use when averaging periodograms. Defaults to ‘mean’.

Returns

res_dict – the result dictionary, including - freq (array): the frequency vector - psd (array): the spectral density vector

Return type

dict