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
Enlace externo
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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