kuramoto-model 0.0.1

A python implementation of the Kuramoto model

Kuramoto Model

A python implementation of the kuramoto model.

Installation

pip install kuramoto_model

Usage

Import the model,

from kuramoto_model.kuramoto_model import Kuramoto

Initialise the model with the following,

1. Number of neurons n
2. Coupling constant k
3. Timeseries timeseries: the timepoints to log results at
4. Intrinsic Frequencies omega_n: defaults to n random values from a normal distribution
5. Initial Phases theta_n: defaults to n random values between 0 and 2pi
6. Adjacency Matrix adjacency_nxn: defaults to all to all coupling (without self-coupling)

n = 100
k = 0.8
ts = np.linspace(0, 100, 1000)
model = Kuramoto(n, k, ts)

Find the phase, coherence and mean frequency timeseries,

phases = model.phase_timeseries()
coherences = model.coherence_timeseries()
mean_freq = model.mean_frequency_timeseries()