xwc (pyleoclim.utils.wavelet.xwc)

pyleoclim.utils.wavelet.xwc(ys1, ts1, ys2, ts2, smooth_factor=0.25, tau=None, freq=None, freq_method='log', freq_kwargs=None, c=0.012665147955292222, Neff=3, nproc=8, detrend=False, sg_kwargs=None, nMC=200, gaussianize=False, standardize=False, method='Kirchner_numba', verbose=False)[source]

Return the cross-wavelet coherence of two time series.

Parameters

ys1 (array) – first of two time series
ys2 (array) – second of the two time series
ts1 (array) – time axis of first time series
ts2 (array) – time axis of the second time series
tau (array) – the evenly-spaced time points
freq (array) – vector of frequency
c (float) – the decay constant that determines the analytical resolution of frequency for analysis, the smaller the higher resolution; the default value 1/(8*np.pi**2) is good for most of the wavelet analysis cases
Neff (int) – effective number of points
nproc (int) – the number of processes for multiprocessing
nMC (int) – the number of Monte-Carlo simulations
detrend (string) –
- 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.
Empirical mode decomposition. The last mode is assumed to be the trend and removed from the series
sg_kwargs (dict) – The parameters for the Savitzky-Golay filters. see pyleoclim.utils.filter.savitzy_golay for details.
gaussianize (bool) – If True, gaussianizes the timeseries
standardize (bool) – If True, standardizes the timeseries
method (string) –
- ‘Foster’: the original WWZ method;
- ’Kirchner’: the method Kirchner adapted from Foster;
- ’Kirchner_f2py’: the method Kirchner adapted from Foster with f2py
- ’Kirchner_numba’: Kirchner’s algorithm with Numba support for acceleration (default)
verbose (bool) – If True, print warning messages

Returns

res – contains the cross wavelet coherence, cross-wavelet phase, vector of frequency, evenly-spaced time points, AR1 sims, cone of influence

Return type

dict