wddtw_cost_matrix¶
- wddtw_cost_matrix(x: ndarray, y: ndarray, window: float | None = None, g: float = 0.05, itakura_max_slope: float | None = None) ndarray [source]¶
Compute the WDDTW cost matrix between two time series.
- Parameters:
- xnp.ndarray, of shape (n_channels, n_timepoints) or (n_timepoints,)
First time series.
- ynp.ndarray, of shape (m_channels, m_timepoints) or (m_timepoints,)
Second time series.
- windowfloat, default=None
The window to use for the bounding matrix. If None, no bounding matrix is used.
- gfloat, default=0.05
Constant that controls the level of penalisation for the points with larger phase difference. Default is 0.05.
- itakura_max_slopefloat, default=None
Maximum slope as a proportion of the number of time points used to create Itakura parallelogram on the bounding matrix. Must be between 0. and 1.
- Returns:
- np.ndarray (n_timepoints_x, n_timepoints_y)
WDDTW cost matrix between x and y.
- Raises:
- ValueError
If x and y are not 1D or 2D arrays. If n_timepoints or m_timepoints are less than 2.
Examples
>>> import numpy as np >>> from aeon.distances import wddtw_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]]) >>> wddtw_cost_matrix(x, y) array([[0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0.], [0., 0., 0., 0., 0., 0., 0., 0.]])