dtaidistance.dtw_barycenter¶
Dynamic Time Warping (DTW) Barycenter
author: | Wannes Meert |
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copyright: | Copyright 2020-2022 KU Leuven, DTAI Research Group. |
license: | Apache License, Version 2.0, see LICENSE for details. |
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dtaidistance.dtw_barycenter.
dba
(s, c, mask=None, samples=None, use_c=False, nb_initial_samples=None, **kwargs)¶ DTW Barycenter Averaging.
F. Petitjean, A. Ketterlin, and P. Gan ̧carski. A global averaging method for dynamic time warping, with applications to clustering. Pattern Recognition, 44(3):678–693, 2011.
Parameters: - s – Container of sequences
- c – Initial averaging sequence. If none is given, the first one is used (unless if nb_initial_samples is set). Better performance can be achieved by starting from an informed starting point (Petitjean et al. 2011).
- mask – Boolean array with the series in s to use. If None, use all.
- nb_initial_samples – If c is None, and this argument is not None, select nb_initial_samples samples and select the series closest to all other samples as c.
- use_c – Use a fast C implementation instead of a Python version.
- kwargs – Arguments for dtw.distance
Returns: Bary-center of length len(c).
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dtaidistance.dtw_barycenter.
dba_loop
(s, c=None, max_it=10, thr=0.001, mask=None, keep_averages=False, use_c=False, nb_initial_samples=None, nb_prob_samples=None, **kwargs)¶ Loop around the DTW Barycenter Averaging (DBA) method until convergence.
Parameters: - s – Container of sequences
- c – Initial averaging sequence. If none is given, the first one is used (unless if nb_initial_samples is set). Better performance can be achieved by starting from an informed starting point (Petitjean et al. 2011).
- max_it – Maximal number of calls to DBA.
- thr – Convergence if the DBA is changing less than this value.
- mask – Boolean array with the series in s to use. If None, use all.
- keep_averages – Keep all DBA values (for visualisation or debugging).
- nb_initial_samples – If c is None, and this argument is not None, select nb_initial_samples samples and select the series closest to all other samples as c.
- nb_prob_samples – Probabilistically sample the best path instead of the deterministic version.
- use_c – Use a fast C implementation instead of a Python version.
- kwargs – Arguments for dtw.distance