dtwParallel: A Python package to efficiently compute dynamic time warping between time series
dc.contributor.author | Escudero-Arnanz, Óscar | |
dc.contributor.author | G. Marques, Antonio | |
dc.contributor.author | Soguero-Ruiz, Cristina | |
dc.contributor.author | Mora-Jiménez, Inmaculada | |
dc.contributor.author | Robles, Gregorio | |
dc.date.accessioned | 2023-10-09T06:53:08Z | |
dc.date.available | 2023-10-09T06:53:08Z | |
dc.date.issued | 2023 | |
dc.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 ). | es |
dc.description.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. | es |
dc.identifier.citation | 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 | es |
dc.identifier.doi | 10.1016/j.softx.2023.101364 | es |
dc.identifier.issn | 2352-7110 | |
dc.identifier.uri | https://hdl.handle.net/10115/24752 | |
dc.language.iso | eng | es |
dc.publisher | Elsevier | es |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | DTW | es |
dc.subject | Multivariate Time Series | es |
dc.subject | Kernel-based similarity | es |
dc.subject | Parallelization | es |
dc.subject | Python | es |
dc.title | dtwParallel: A Python package to efficiently compute dynamic time warping between time series | es |
dc.type | info:eu-repo/semantics/article | es |
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