wwz_psd (pyleoclim.utils.spectral.wwz_psd)¶

pyleoclim.utils.spectral.wwz_psd(ys, ts, freq=None, freq_method='log', freq_kwargs=None, tau=None, c=0.001, nproc=8, detrend=False, sg_kwargs=None, gaussianize=False, standardize=False, Neff=3, anti_alias=False, avgs=2, method='Kirchner_numba')[source]¶

Return the psd of a timeseries using wwz method.

Parameters

ys (array) – a time series, NaNs will be deleted automatically
ts (array) – the time points, if ys contains any NaNs, some of the time points will be deleted accordingly
freq (array) – vector of frequency
freq_method (str, {'log', 'lomb_scargle', 'welch', 'scale', 'nfft'}) –
Method to generate the frequency vector if not set directly. The following options are avialable:
- ’log’ (default)
- ’lomb_scargle’
- ’welch’
- ’scale’
- ’nfft’
See pyleoclim.utils.wavelet.make_freq_vector() for details
freq_kwargs (dict) – Arguments for the method chosen in freq_method. See specific functions in pyleoclim.utils.wavelet for details
tau (array) – the evenly-spaced time vector for the analysis, namely the time shift for wavelet analysis
c (float) – the decay constant that will determine the analytical resolution of frequency for analysis, the smaller the higher resolution; the default value 1e-3 is good for most of the spectral analysis cases
nproc (int) – the number of processes for multiprocessing
detrend (str, {None, 'linear', 'constant', 'savitzy-golay'}) –
available methods for detrending, including
- None: the original time series is assumed to have no trend;
- ’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.
sg_kwargs (dict) – The parameters for the Savitzky-Golay filters. See pyleoclim.utils.filter.savitzky_golay() for details.
gaussianize (bool) – If True, gaussianizes the timeseries
standardize (bool) – If True, standardizes the timeseries
method (string, {'Foster', 'Kirchner', 'Kirchner_f2py', 'Kirchner_numba'}) –
available specific implementation of WWZ, including
- ’Foster’: the original WWZ method;
- ’Kirchner’: the method Kirchner adapted from Foster;
- ’Kirchner_f2py’: the method Kirchner adapted from Foster, implemented with f2py for acceleration;
- ’Kirchner_numba’: the method Kirchner adapted from Foster, implemented with Numba for acceleration (default);
Neff (int) – effective number of points
anti_alias (bool) – If True, uses anti-aliasing
avgs (int) – flag for whether spectrum is derived from instantaneous point measurements (avgs<>1) OR from measurements averaged over each sampling interval (avgs==1)

Returns

res – a namedtuple that includes below items

psdarray: power spectral density
freqarray: vector of frequency

Return type

namedtuple