Piecewise 2D Gaussian process (
pw_normal simulates a 2D signal of Gaussian i.i.d. random variables with zero mean and covariance matrix alternating between \([[1, 0.9], [0.9, 1]]\) and \([[1, -0.9], [-0.9, 1]]\) at every change point.
Start with the usual imports and create a signal.
import numpy as np import matplotlib.pylab as plt import ruptures as rpt # creation of data n = 500, 3 # number of samples n_bkps = 3 # number of change points, noise standart deviation signal, bkps = rpt.pw_normal(n, n_bkps) rpt.display(signal, bkps)