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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>.

Functions (15)

aami

ANSI/AAMI EC13 Test Waveforms, 3a and 3b

countPaths

Count the number of warping paths consistent with the constraints.

dtw

Dynamic Time Warp

dtw-internal

Internal dtw Functions

dtw-package

Comprehensive implementation of Dynamic Time Warping (DTW) algorithms in R.

dtwDist

Compute a dissimilarity matrix

dtwPlot

Plotting of dynamic time warp results

dtwPlotDensity

Display the cumulative cost density with the warping path overimposed

dtwPlotThreeWay

Plotting of dynamic time warp results: annotated warping function

dtwPlotTwoWay

Plotting of dynamic time warp results: pointwise comparison

dtwWindowingFunctions

Global constraints and windowing functions for DTW

mvm

Minimum Variance Matching algorithm

stepPattern

Step patterns for DTW

warp

Apply a warping to a given timeseries

warpArea

Compute Warping Path Area

dtw

Dynamic Time Warping Algorithms

v1.22-3
GPL (>= 2)
Authors
Toni Giorgino [aut, cre]
Initial release
2020-9-26

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