dtwParallel: A Python package to efficiently compute dynamic time warping between time series
Fecha
2023
Título de la revista
ISSN de la revista
Título del volumen
Editor
Elsevier
Resumen
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.
Descripción
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 ).
Palabras clave
Citación
Óscar Escudero-Arnanz, Antonio G. Marques, Cristina Soguero-Ruiz, Inmaculada Mora-Jiménez, Gregorio Robles, dtwParallel: A Python package to efficiently compute dynamic time warping between time series, SoftwareX, Volume 22, 2023, 101364, ISSN 2352-7110, https://doi.org/10.1016/j.softx.2023.101364
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