dtwParallel: A Python package to efficiently compute dynamic time warping between time series
Abstract
dtwParallel is a Python package that computes the Dynamic Time Warping (DTW) distance between a collection of (multivariate) time series (MTS). dtwParallel incorporates the main functionalities available in current DTW libraries and novel functionalities such as parallelization, computation of similarity (kernel-based) values, and consideration of data with different types of features (categorical, real-valued, . . . ). A low-floor, high-ceiling, and wide-walls software design principle has been adopted, envisioning uses in education, research, and industry. The source code and documentation of the package are available at https://github.com/oscarescuderoarnanz/dtwParallel.
Description
Work supported by the Spanish NSF (grants , PID2019-106623RB-C41/AEI/10.13039/501100011033 PID2019-105032GB-I00AEI/10.13039/501100011033, and PID2019-107768RA-I00/AEI/10.13039/501100011033), and the Community of Madrid, Spain (grants PEJ-2020-AI/TIC-18964, URJC-F661, and e-Madrid-CM-P2018/TCS-4307, co-financed by EU Structural Funds FSE and FEDER, Spain ).
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