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dtw (version 1.21-3)

Dynamic Time Warping Algorithms

Description

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.

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Version

Install

install.packages('dtw')

Monthly Downloads

6,121

Version

1.21-3

License

GPL (>= 2)

Homepage

https://dynamictimewarping.github.io/

Maintainer

Toni Giorgino

Last Published

September 1st, 2019

Functions in dtw (1.21-3)

Plotting of dynamic time warp results: pointwise comparison

Compute a dissimilarity matrix

Plotting of dynamic time warp results

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

Count the number of warping paths consistent with the constraints.

dtwPlotThreeWay

Plotting of dynamic time warp results: annotated warping function

Internal dtw Functions

Dynamic Time Warp

Display the cumulative cost density with the warping path overimposed

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

Apply a warping to a given timeseries

Step patterns for DTW

dtwWindowingFunctions

Global constraints and windowing functions for DTW

Compute Warping Path Area

Minimum Variance Matching algorithm