dtw_cost_matrix#

dtw_cost_matrix(x: ndarray, y: ndarray, window: float = None) → ndarray[source]#

Compute the dtw cost matrix between two time series.

Parameters:

x: np.ndarray, of shape (n_channels, n_timepoints) or (n_timepoints,): First time series.
y: np.ndarray, of shape (m_channels, m_timepoints) or (m_timepoints,): Second time series.
window: float, default=None: The window to use for the bounding matrix. If None, no bounding matrix is used.

Returns:

np.ndarray (n_timepoints, m_timepoints): dtw cost matrix between x and y.

Raises:

ValueError: If x and y are not 1D or 2D arrays.

Examples

>>> import numpy as np
>>> from aeon.distances import dtw_cost_matrix
>>> x = np.array([[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]])
>>> y = np.array([[1, 2, 3, 4, 5, 6, 7, 8, 9, 10]])
>>> dtw_cost_matrix(x, y)
array([[  0.,   1.,   5.,  14.,  30.,  55.,  91., 140., 204., 285.],
       [  1.,   0.,   1.,   5.,  14.,  30.,  55.,  91., 140., 204.],
       [  5.,   1.,   0.,   1.,   5.,  14.,  30.,  55.,  91., 140.],
       [ 14.,   5.,   1.,   0.,   1.,   5.,  14.,  30.,  55.,  91.],
       [ 30.,  14.,   5.,   1.,   0.,   1.,   5.,  14.,  30.,  55.],
       [ 55.,  30.,  14.,   5.,   1.,   0.,   1.,   5.,  14.,  30.],
       [ 91.,  55.,  30.,  14.,   5.,   1.,   0.,   1.,   5.,  14.],
       [140.,  91.,  55.,  30.,  14.,   5.,   1.,   0.,   1.,   5.],
       [204., 140.,  91.,  55.,  30.,  14.,   5.,   1.,   0.,   1.],
       [285., 204., 140.,  91.,  55.,  30.,  14.,   5.,   1.,   0.]])