Compute WCT (Wavelet Coherence Transform)

Wavelet Coherence Transform (WCT) Computation This script performs the computation of the Wavelet Coherence Transform (WCT), a tool used to analyze the correlation between two time series in the time-frequency domain. The script supports parallel processing and interacts with a database to manage job statuses.

Filter Configuration Parameters

  • dtt_minlag : If dtt_lag =static: min lag time (in seconds) (default=5)

  • dtt_maxdt : Maximum dt values, MWCS points with values larger than that will not be used in the WLS (in seconds) (default=0.1)

  • dtt_mincoh : Minimum coherence on dt measurement, MWCS points with values lower than that will not be used in the WLS, [0:1] (default=0.65)

  • dtt_codacycles : number of cycles of period (1/freq) between lag_min and lag_max (default=20)

  • wct_ns : smoothing parameter in frequency (default=5)

  • wct_nt : smoothing parameter in time (default=5)

  • wct_vpo : spacing param between discrete scales (default=20)

  • wct_nptsfreq : number of freq points between min and max (default=300)

  • dvv_min_nonzero : percentage of data points with non-zero weighting required for regression otherwise nan (0 to 1) (default=0.25)

  • wct_norm : Is the REF and CCF are normalized before computing wavelet? [Y]/N (default=Y)

  • hpc : Is MSNoise going to run on an HPC? (default=N)

This process is job-based, so it is possible to run several instances in parallel.

To run this step:

$ msnoise cc dvv compute_wct

This step also supports parallel processing/threading:

$ msnoise -t 4 cc dvv compute_wct

will start 4 instances of the code (after 1 second delay to avoid database conflicts). This works both with SQLite and MySQL but be aware problems could occur with SQLite.