Toy example that shows what happens to the DTF when a sinusoid is added to white noise signals

example_sinedtf.py

import numpy as np
import matplotlib.pyplot as plt
import seaborn

from scot.var import VAR
from scot.connectivity import connectivity


fs = 100
n = 10001
disturbance = np.sin(np.arange(n) * 2 * np.pi * 20 / fs)
for i in range(3):
    np.random.seed(42)
    if i == 0:
        # three white noise signals
        x = np.random.randn(3, n)
    elif i == 1: 
        # a sinusoid added to the three signals
        x = np.random.randn(3, n)
        x += disturbance
    elif i == 2:        
        # in addition to adding the sinusoid, now we also include a fourth
        # signal that contains only the sinousoid (and a little noise)
        x = np.random.randn(4, n)
        x[3, :] *= 0.03
        x += disturbance
    plt.figure()
    var = VAR(15).fit(x)
    S = connectivity('S', var.coef, var.rescov)
    C = connectivity('DTF', var.coef, var.rescov)
    f = np.abs(np.linspace(0, fs / 2, S.shape[-1]))
    for i in range(x.shape[0]):
        for j in range(x.shape[0]):
            plt.subplot(x.shape[0], x.shape[0], i * x.shape[0] + j + 1)
            if i == j:
                plt.fill_between(f, 0, S[i, j, :], color=seaborn.color_palette()[1])
            else:
                plt.fill_between(f, 0, C[i, j, :], color = seaborn.color_palette()[0])
                plt.ylim(0, 1)
plt.show()

Results: