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dtw-python

View on PyPI — Reverse Dependencies (15)

1.4.2	dtw_python-1.4.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
	dtw_python-1.4.2-cp39-cp39-win_amd64.whl
	dtw_python-1.4.2-cp39-cp39-macosx_10_9_x86_64.whl
	dtw_python-1.4.2-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
	dtw_python-1.4.2-cp38-cp38-win_amd64.whl
	dtw_python-1.4.2-cp38-cp38-macosx_10_9_x86_64.whl
	dtw_python-1.4.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
	dtw_python-1.4.2-cp37-cp37m-win_amd64.whl
	dtw_python-1.4.2-cp37-cp37m-macosx_10_9_x86_64.whl
	dtw_python-1.4.2-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
	dtw_python-1.4.2-cp36-cp36m-win_amd64.whl
	dtw_python-1.4.2-cp36-cp36m-macosx_10_9_x86_64.whl
	dtw_python-1.4.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
	dtw_python-1.4.2-cp312-cp312-win_amd64.whl
	dtw_python-1.4.2-cp312-cp312-macosx_10_9_x86_64.whl
	dtw_python-1.4.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
	dtw_python-1.4.2-cp311-cp311-win_amd64.whl
	dtw_python-1.4.2-cp311-cp311-macosx_10_9_x86_64.whl
	dtw_python-1.4.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
	dtw_python-1.4.2-cp310-cp310-win_amd64.whl
	dtw_python-1.4.2-cp310-cp310-macosx_10_9_x86_64.whl

Wheel Details

Project:	dtw-python
Version:	1.4.2
Filename:	dtw_python-1.4.2-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Download:	[link]
Size:	718310
MD5:	`7733cada4e4f9ac24ba8935465157aa0`
SHA256:	`72cf20f8e55affb41ab8eb6221bb96450315bbf82fcc8593baea477d13e250ce`
Uploaded:	2024-03-19 07:46:39 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt · entry_points.txt

METADATA

Metadata-Version:	2.1
Name:	dtw-python
Version:	1.4.2
Summary:	A comprehensive implementation of dynamic time warping (DTW) algorithms. DTW computes the optimal (least cumulative distance) alignment between points of two time series. Common DTW variants covered include local (slope) and global (window) constraints, subsequence matches, arbitrary distance definitions, normalizations, minimum variance matching, and so on. Provides cumulative distances, alignments, specialized plot styles, etc.
Author:	Toni Giorgino
Author-Email:	toni.giorgino[at]gmail.com
Home-Page:	https://DynamicTimeWarping.github.io
License:	GNU General Public License v3
Keywords:	dtw,timeseries
Classifier:	Development Status :: 4 - Beta
Classifier:	Intended Audience :: Science/Research
Classifier:	Topic :: Scientific/Engineering
Classifier:	License :: OSI Approved :: GNU General Public License v2 or later (GPLv2+)
Classifier:	Natural Language :: English
Classifier:	Programming Language :: Python :: 3.6
Classifier:	Programming Language :: Python :: 3.7
Classifier:	Programming Language :: Python :: 3.8
Classifier:	Programming Language :: Python :: 3.9
Classifier:	Programming Language :: Python :: 3.10
Requires-Python:	>=3.6
Requires-Dist:	numpy (>=1.19)
Requires-Dist:	scipy (>=1.1)
Description-Content-Type:	text/x-rst
License-File:	COPYING
License-File:	AUTHORS.rst

[Description omitted; length: 6202 characters]

WHEEL

Wheel-Version:	1.0
Generator:	bdist_wheel (0.42.0)
Root-Is-Purelib:	false
Tag:	cp37-cp37m-manylinux_2_17_x86_64
Tag:	cp37-cp37m-manylinux2014_x86_64

RECORD

Path	Digest	Size
dtw/stepPattern.py	sha256=Z1TSbAVMsnhvPwyt1qDtXJdG2yw357Y9zZuSOti_gok	26034
dtw/dtw_core.h	sha256=9VeIOZ2OkJDA793PEzknfsOOXI8ZB2UXKEJkk27kMGw	1271
dtw/_backtrack.py	sha256=Gbi1Er7sVBVGU9zdBUjf_ZdFX3Xvgi7WBoiMD8Nw84M	2203
dtw/dtw.py	sha256=1E4MYeTKR5gn2SOqUrEb1Q-MU0SyTRyFa_gpfCBn060	15681
dtw/dtwPlot.py	sha256=QHu4txx_g8lDmWx47pCWbqk7kekBt3uk84S21ntKO0c	12039
dtw/countPaths.py	sha256=ad2TljKxqndmDx4rhmFTjxueicYd33jetEDzz82k2gM	2761
dtw/_dtw_utils.cpython-37m-x86_64-linux-gnu.so	sha256=HQ8dhl1Y6aO83dajadSnP_643KxIMC7JwowmxQgRtLo	1452848
dtw/_globalCostMatrix.py	sha256=ONWvCgg9UcZ4ZzG_CQKzhk50IWNRZIh3kyLL_kt3b2M	1920
dtw/warp.py	sha256=R8lLBa38Dw0pAUEYrAQmp9wFWnOZZ5cTprPimd2dRx0	3484
dtw/dtw_test_data.py	sha256=-m0HfD_UOHJEDdf0PLQ2kWCrQfywhB7kwecCfBI8pH4	3575
dtw/_dtw_utils.pyx	sha256=8VyWo94IRroY_wdvygFy9P7PPHvOauvjMvmYOh3RmJE	2999
dtw/__main__.py	sha256=8MwHLSzP9Mh-T96bDfmq_zf864GEzHlmgPN3G-liDqY	1410
dtw/__init__.py	sha256=pBHdDtNysrFn7MdnczVyr78LJgwSbfzW4g5tStfDgUw	1104
dtw/_dtw_utils.c	sha256=Jye61YsYbNUjf_pSpbpA5hKQqIcvT7FD4uUPyuFCoNo	1203205
dtw/window.py	sha256=rtrhSEFLF0MPEwCwbtacJZUPOZjiphB2CyNE1Xf2__Q	5800
dtw/mvm.py	sha256=hSCmWXgmW5JQviRPhLM3YP0QzccTPpYbVaEkSPRobm4	3073
dtw/dtw_core.c	sha256=FV4v8loQr_DCdcC3XAIyK3-UkzJ4349w3BbrpsChWl8	8418
dtw/warpArea.py	sha256=yLz5zS53wqrBY-o0eXThMer2g6zaCDLpwfUAkGlpgS4	2731
dtw/data/README.txt	sha256=UzAXkLqlzjHc7-vvVIpLP2BqIxkQcvTitAQ8UF2WbE8	501
dtw/data/aami3a.csv	sha256=Et1lAfJ0ZnP5T3kOv-BulRGuMFNGNXXiealTFxFaXnA	250698
dtw/data/aami3b.csv	sha256=Sk6DPVZNMduyvMbMtFQc5meZnlqR9HHAiEp_B1I8Xng	252781
dtw_python-1.4.2.dist-info/RECORD	—	—
dtw_python-1.4.2.dist-info/entry_points.txt	sha256=orLlgtCdI8Hp1Yzf6uZNADOuUC1P-5tG-VWtgsYCAKk	42
dtw_python-1.4.2.dist-info/AUTHORS.rst	sha256=yFj6t9rluCnD6KJxj88g7JRcmwXsdtJ0HEIWaFefuY8	149
dtw_python-1.4.2.dist-info/WHEEL	sha256=XTrbe1v1RZIwaNy2ykqZ1b32V5o3CvHsSToseXBj9JY	150
dtw_python-1.4.2.dist-info/METADATA	sha256=X80Wvepd060AFDLCjJ5_Pqd-hcshEASRalR0UyXZ0Fw	7550
dtw_python-1.4.2.dist-info/COPYING	sha256=OXLcl0T2SZ8Pmy2_dmlvKuetivmyPd5m1q-Gyd-zaYY	35149
dtw_python-1.4.2.dist-info/top_level.txt	sha256=1ifHycuL2nGfdMqj8AupbXgI8OVrskwR2rfuJRUxbUM	4

top_level.txt

dtw

entry_points.txt

[console_scripts]

dtw = dtw.__main__:main