Nonlinear and Biomedical Physics Toolboxes
Here you can find GitHub links for the numerical toolbox MODA and algorithms developed by the Nonlinear and Biomedical Physics group at Lancaster University for analysing time-series data, either measured or numerically generated.
MODA is a user-friendly toolbox, written both in MatLab and in Python. It is designed for analysing time-series that result from multiscale oscillatory dynamics. It encompasses non-autonomous dynamics in which frequencies vary in time. MODA provides time-frequency spectra and enables detection of instantaneous frequencies. It includes an algorithm to detect high harmonics of time-varying frequencies.
MODA also contains algorithms for the investigation of interactions between oscillatory processes, including wavelet phase coherence and phase shifts, wavelet bispectral analysis, and coupling functions obtained through dynamical Bayesian inference.
MODA includes methods for univariate and simultaneously recorded/generated multivariate time-series.
These are algorithms and toolboxes that can be run individually. Some of them are included in MODA. They are all written in MatLab.