Package: dtw 1.23-2

dtw: Dynamic Time Warping Algorithms

A comprehensive implementation of dynamic time warping (DTW) algorithms in R. 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., as described in Giorgino (2009) <doi:10.18637/jss.v031.i07>.

Authors:Toni Giorgino [aut, cre]

dtw_1.23-2.tar.gz
dtw_1.23-2.zip(r-4.7)dtw_1.23-2.zip(r-4.6)dtw_1.23-2.zip(r-4.5)
dtw_1.23-2.tgz(r-4.6-x86_64)dtw_1.23-2.tgz(r-4.6-arm64)dtw_1.23-2.tgz(r-4.5-x86_64)dtw_1.23-2.tgz(r-4.5-arm64)
dtw_1.23-2.tar.gz(r-4.7-arm64)dtw_1.23-2.tar.gz(r-4.7-x86_64)dtw_1.23-2.tar.gz(r-4.6-arm64)dtw_1.23-2.tar.gz(r-4.6-x86_64)
dtw_1.23-2.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
dtw/json (API)

# Install 'dtw' in R:
install.packages('dtw', repos = c('https://tonigi.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:
  • aami3a - ANSI/AAMI EC13 Test Waveforms, 3a and 3b
  • aami3b - ANSI/AAMI EC13 Test Waveforms, 3a and 3b

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

8.77 score 5 stars 49 packages 660 scripts 12k downloads 16 mentions 46 exports 1 dependencies

Last updated from:824b057180. Checks:12 OK, 1 ERROR. Indexed: yes.

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linux-devel-x86_64OK99
source / vignettesERROR194
linux-release-arm64OK98
linux-release-x86_64OK103
macos-release-arm64OK147
macos-release-x86_64OK233
macos-oldrel-arm64OK197
macos-oldrel-x86_64OK275
windows-develOK83
windows-releaseOK85
windows-oldrelOK85
wasm-releaseOK90

Exports:asymmetricasymmetricP0asymmetricP05asymmetricP1asymmetricP2countPathsdtwdtwDistdtwPlotdtwPlotAlignmentdtwPlotDensitydtwPlotThreeWaydtwPlotTwoWaydtwWindow.plotis.dtwis.stepPatternitakuraWindowmori2006mvmStepPatternnoWindowrabinerJuangStepPatternrigidsakoeChibaWindowslantedBandWindowsymmetric1symmetric2symmetricP0symmetricP05symmetricP1symmetricP2typeIatypeIastypeIbtypeIbstypeIctypeIcstypeIdtypeIdstypeIIatypeIIbtypeIIctypeIIdtypeIIIctypeIVcwarpwarpArea

Dependencies:proxy

Computing and Visualizing Dynamic Time Warping Alignments in R: The dtw Package

Rendered fromdtw.Rnwusingutils::Sweaveon May 09 2026.

Last update: 2019-08-21
Started: 2013-12-11

Readme and manuals

Help Manual

Help pageTopics
Comprehensive implementation of Dynamic Time Warping (DTW) algorithms in R.dtw-package
ANSI/AAMI EC13 Test Waveforms, 3a and 3baami aami3a aami3b
Count the number of warping paths consistent with the constraints.countPaths
Dynamic Time Warpdtw is.dtw print.dtw
Compute a dissimilarity matrixdtwDist
Plotting of dynamic time warp resultsdtwPlot dtwPlotAlignment plot.dtw
Display the cumulative cost density with the warping path overimposeddtwPlotDensity
Plotting of dynamic time warp results: annotated warping functiondtwPlotThreeWay
Plotting of dynamic time warp results: pointwise comparisondtwPlotTwoWay
Global constraints and windowing functions for DTWdtwWindow.plot dtwWindowingFunctions itakuraWindow noWindow sakoeChibaWindow slantedBandWindow
Minimum Variance Matching algorithmmvm mvmStepPattern
Step patterns for DTWasymmetric asymmetricP0 asymmetricP05 asymmetricP1 asymmetricP2 is.stepPattern mori2006 plot.stepPattern print.stepPattern rabinerJuangStepPattern rigid stepPattern symmetric1 symmetric2 symmetricP0 symmetricP05 symmetricP1 symmetricP2 t.stepPattern typeIa typeIas typeIb typeIbs typeIc typeIcs typeId typeIds typeIIa typeIIb typeIIc typeIId typeIIIc typeIVc
Apply a warping to a given timeserieswarp
Compute Warping Path AreawarpArea