Piecewise Gaussian (pw_normal)

Return a 2D piecewise Gaussian signal and the associated changepoints.

Parameters:

Name	Type	Description	Default
n_samples	int	signal length	200
n_bkps	int	number of change points	3
seed	int	random seed	None

Returns:

Name	Type	Description
tuple		signal of shape (n_samples, 2), list of breakpoints

Source code in ruptures/datasets/pw_normal.py

def pw_normal(n_samples=200, n_bkps=3, seed=None):
    """Return a 2D piecewise Gaussian signal and the associated changepoints.

    Args:
        n_samples (int, optional): signal length
        n_bkps (int, optional): number of change points
        seed (int): random seed

    Returns:
        tuple: signal of shape (n_samples, 2), list of breakpoints
    """
    # breakpoints
    bkps = draw_bkps(n_samples, n_bkps, seed=seed)
    # we create the signal
    signal = np.zeros((n_samples, 2), dtype=float)
    cov1 = np.array([[1, 0.9], [0.9, 1]])
    cov2 = np.array([[1, -0.9], [-0.9, 1]])
    rng = np.random.default_rng(seed=seed)
    for sub, cov in zip(np.split(signal, bkps), cycle((cov1, cov2))):
        n_sub, _ = sub.shape
        sub += rng.multivariate_normal([0, 0], cov, size=n_sub)

    return signal, bkps