phaseran (pyleoclim.utils.correlation.phaseran)

pyleoclim.utils.correlation.phaseran(recblk, nsurr)[source]

Simultaneous phase randomization of a set of time series

It creates blocks of surrogate data with the same second order properties as the original time series dataset by transforming the oriinal data into the frequency domain, randomizing the phases simultaneoulsy across the time series and converting the data back into the time domain.

Written by Carlos Gias for MATLAB

http://www.mathworks.nl/matlabcentral/fileexchange/32621-phase-randomization/content/phaseran.m

Parameters

  • recblk (numpy array) – 2D array , Row: time sample. Column: recording. An odd number of time samples (height) is expected. If that is not the case, recblock is reduced by 1 sample before the surrogate data is created. The class must be double and it must be nonsparse.

  • nsurr (int) – is the number of image block surrogates that you want to generate.

Returns

surrblk – 3D multidimensional array image block with the surrogate datasets along the third dimension

Return type

numpy array

References

  • Prichard, D., Theiler, J. Generating Surrogate Data for Time Series with Several Simultaneously Measured Variables (1994)

Physical Review Letters, Vol 73, Number 7

  • Carlos Gias (2020). Phase randomization, MATLAB Central File Exchange