{"repo":"wannesm/dtaidistance","free":true,"listed":false,"github":"https://github.com/wannesm/dtaidistance","clone":"git clone https://github.com/wannesm/dtaidistance.git","description":"Time series distances: Dynamic Time Warping (fast DTW implementation in C)","language":"Python","stars":1242,"topics":["timeseries","dtw","clustering","dynamic-time-warping","distance-measure","c","python"],"license":null,"category":"dev-tools","readme_excerpt":"Time Series Distances Library for time series distances (e.g. Dynamic Time Warping) used in the DTAI Research Group. The library offers a pure Python implementation and a fast implementation in C. The C implementation has only Cython as a dependency. It is compatible with Numpy and Pandas and implemented such that unnecessary data copy operations are avoided. Documentation: http://dtaidistance.readthedocs.io Example: from dtaidistance import dtw import numpy as np s1 = np.array([0.0, 0, 1, 2, 1, 0, 1, 0, 0]) s2 = np.array([0.0, 1, 2, 0, 0, 0, 0, 0, 0]) d = dtw.distance fast(s1, s2) Citing this work: Wannes Meert, Kilian Hendrickx, Toon Van Craenendonck, Pieter Robberechts, Hendrik Blockeel & Jesse Davis. DTAIDistance (Version v2). Zenodo. http://doi.org/10.5281/zenodo.5901139 New in v2 : - Numpy is now an optional dependency, also to compile the C library (only Cython is required). - Small optimizations throughout the C code to improve speed. - The consistent use of ssize t instead of int allows for larger data structures on 64 bit machines and be more compatible with Numpy. - The parallelization is now implemented directly in C (included if OpenMP is installed). - The max dist argument turned out to be similar to Silva and Batista's work on PrunedDTW [7]. The toolbox now implements a version that is equal to PrunedDTW since it prunes more partial distances. Additionally, a use pruning argument is added to automatically set max dist to the Euclidean distance, as suggested by ","default_branch":null,"files":null,"tree":[],"storefront":"/r/wannesm","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/wannesm/dtaidistance/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}