twe_cost_matrix

twe_cost_matrix(x: ndarray, y: ndarray, window: float = None, nu: float = 0.001, lmbda: float = 1.0) → ndarray

Compute the TWE 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: int, defaults = None

Window size. If None, the window size is set to the length of the shortest time series.

nu: float, defaults = 0.001

A non-negative constant which characterizes the stiffness of the elastic twe measure. Must be > 0.

lmbda: float, defaults = 1.0

A constant penalty that punishes the editing efforts. Must be >= 1.0.

Returns:

np.ndarray (n_timepoints_x, n_timepoints_y)

TWE 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 twe_cost_matrix
>>> x = np.array([[1, 2, 3, 4, 5, 6, 7, 8]])
>>> y = np.array([[1, 2, 3, 4, 5, 6, 7, 8]])
>>> twe_cost_matrix(x, y)
array([[ 0.   ,  2.001,  4.002,  6.003,  8.004, 10.005, 12.006, 14.007],
       [ 2.001,  0.   ,  2.001,  4.002,  6.003,  8.004, 10.005, 12.006],
       [ 4.002,  2.001,  0.   ,  2.001,  4.002,  6.003,  8.004, 10.005],
       [ 6.003,  4.002,  2.001,  0.   ,  2.001,  4.002,  6.003,  8.004],
       [ 8.004,  6.003,  4.002,  2.001,  0.   ,  2.001,  4.002,  6.003],
       [10.005,  8.004,  6.003,  4.002,  2.001,  0.   ,  2.001,  4.002],
       [12.006, 10.005,  8.004,  6.003,  4.002,  2.001,  0.   ,  2.001],
       [14.007, 12.006, 10.005,  8.004,  6.003,  4.002,  2.001,  0.   ]])