sakoe_chiba_mask#

tslearn.metrics.sakoe_chiba_mask(sz1, sz2, radius=1, be=None)[source]#

Compute the Sakoe-Chiba mask.

Parameters:

sz1int: The size of the first time series
sz2int: The size of the second time series.
radiusint: The radius of the band.
beBackend object or string or None: Backend. If be is an instance of the class NumPyBackend or the string “numpy”, the NumPy backend is used. If be is an instance of the class PyTorchBackend or the string “pytorch”, the PyTorch backend is used. If be is None, the backend is determined by the input arrays. See our dedicated user-guide page for more information.

Returns:

maskarray-like, shape=(sz1, sz2): Sakoe-Chiba mask.

Examples

>>> sakoe_chiba_mask(4, 4, radius=2)
array([[ True,  True,  True, False],
       [ True,  True,  True,  True],
       [ True,  True,  True,  True],
       [False,  True,  True,  True]])