Project intends to fit Kuramoto to provided data. Currently there are two available scenarios:

• all-to-all, where fit is for N separated oscillators, and
• all-to-one, where fit is for signal that implicitly is composed of N oscillators.

In all cases the model is ran from respective directory with

$ python kuramoto.py

If this is run for the first time it might take a while to execute as Stan needs to compile the model. Another script is provided for displaying and comparing reconstruction:

$ python plot.py

Parameters for the models are stored in model.config. Currently this is used for generating model for tests and as initial values.

Input is supposed to be of dimension NxT, i.e. N oscillators and their T phases in time or Y_N(t) = (y₁(t), y₂(t), ..., y_N(t)). The model fits initial positions, couplings and intrinsic frequencies.

The input is a linear superposition of many oscillators: S_N(T) = s₁(t)+s₂(t)+...+s_N(t). The model fits initial positions, couplings and intrinsic frequencies.