Package: dtwclust 6.0.0

Alexis Sarda

dtwclust: Time Series Clustering Along with Optimizations for the Dynamic Time Warping Distance

Time series clustering along with optimized techniques related to the Dynamic Time Warping distance and its corresponding lower bounds. Implementations of partitional, hierarchical, fuzzy, k-Shape and TADPole clustering are available. Functionality can be easily extended with custom distance measures and centroid definitions. Implementations of DTW barycenter averaging, a distance based on global alignment kernels, and the soft-DTW distance and centroid routines are also provided. All included distance functions have custom loops optimized for the calculation of cross-distance matrices, including parallelization support. Several cluster validity indices are included.

Authors:Alexis Sarda-Espinosa

dtwclust_6.0.0.tar.gz
dtwclust_6.0.0.tar.gz(r-4.5-noble)dtwclust_6.0.0.tar.gz(r-4.4-noble)
dtwclust.pdf |dtwclust.html✨
dtwclust/json (API)
NEWS

# Install 'dtwclust' in R:

install.packages('dtwclust', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/asardaes/dtwclust/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

Datasets:

CharTraj - Subset of character trajectories data set
CharTrajLabels - Subset of character trajectories data set
CharTrajMV - Subset of character trajectories data set
dtwclustTimings - Results of timing experiments

41 exports 1 stars 3.52 score 75 dependencies 13 dependents 11 mentions 458 scripts 6.4k downloads

Last updated 2 months agofrom:89d34105e1. Checks:OK: 1 NOTE: 1. Indexed: no.

Target	Result	Date
Doc / Vignettes	OK	Aug 23 2024
R-4.5-linux-x86_64	NOTE	Aug 23 2024

Exports:as.matrix compare_clusterings compare_clusterings_configs compute_envelope cvi cvi_evaluators dba DBA dtw_basic dtw_lb dtw2 fuzzy_control gak GAK hierarchical_control interactive_clustering lb_improved lb_keogh NCCc pam_cent partitional_control pdc_configs plot predict reinterpolate repeat_clustering sbd SBD sdtw sdtw_cent shape_extraction show ssdtwclust tadpole TADPole tadpole_control tsclust tsclust_args tslist update zscore

Dependencies:base64enc bslib cachem class cli clue cluster codetools colorspace commonmark crayon digest dplyr dtw fansi farver fastmap flexclust fontawesome foreach fs generics ggplot2 ggrepel glue gtable htmltools httpuv isoband iterators jquerylib jsonlite labeling later lattice lifecycle magrittr MASS Matrix memoise mgcv mime modeltools munsell nlme pillar pkgconfig plyr promises proxy R6 rappdirs RColorBrewer Rcpp RcppArmadillo RcppEigen RcppParallel RcppThread reshape2 rlang RSpectra sass scales shiny shinyjs sourcetools stringi stringr tibble tidyselect utf8 vctrs viridisLite withr xtable

Comparing Time-Series Clustering Algorithms in R Using the dtwclust Package

Rendered fromdtwclust.Rnwusingknitr::knitr_notangleon Aug 23 2024.

Last update: 2019-09-19
Started: 2016-09-02

Parallelization considerations for dtwclust

Alexis Sarda-Espinosa

Rendered fromparallelization-considerations.Rmdusingknitr::rmarkdown_notangleon Aug 23 2024.

Last update: 2019-06-29
Started: 2018-01-29

Timing experiments for dtwclust

Alexis Sarda-Espinosa

Rendered fromtiming-experiments.Rmdusingknitr::rmarkdown_notangleon Aug 23 2024.

Last update: 2019-06-29
Started: 2017-08-09

Help page	Topics
Time series clustering along with optimizations for the Dynamic Time Warping distance	dtwclust-package dtwclust
as.matrix	as.matrix
Compare different clustering configurations	compare_clusterings
Create clustering configurations.	compare_clusterings_configs
Time series warping envelopes	compute_envelope
Cluster validity indices	cvi cvi,FuzzyTSClusters cvi,FuzzyTSClusters-method cvi,HierarchicalTSClusters cvi,HierarchicalTSClusters-method cvi,matrix-method cvi,PartitionalTSClusters cvi,PartitionalTSClusters-method
Cluster comparison based on CVIs	cvi_evaluators
DTW Barycenter Averaging	DBA dba
Distance matrix's lower triangular	DistmatLowerTriangular DistmatLowerTriangular-class
Basic DTW distance	dtw_basic
DTW distance matrix guided by Lemire's improved lower bound	dtw_lb
DTW distance with L2 norm	dtw2
Results of timing experiments	dtwclustTimings
Fast global alignment kernels	GAK gak
A shiny app for interactive clustering	interactive_clustering
Lemire's improved DTW lower bound	lb_improved
Keogh's DTW lower bound	lb_keogh
Cross-correlation with coefficient normalization	NCCc
Centroid for partition around medoids	pam_cent
Helper function for preprocessing/distance/centroid configurations	pdc_configs
Wrapper for simple linear reinterpolation	reinterpolate
Repeat a clustering configuration	repeat_clustering
Shape-based distance	SBD sbd
Soft-DTW distance	sdtw
Centroid calculation based on soft-DTW	sdtw_cent
Shape average of several time series	shape_extraction
A shiny app for semi-supervised DTW-based clustering	ssdtwclust
TADPole clustering	TADPole tadpole
Time series clustering	tsclust
Control parameters for clusterings with 'tsclust()'	fuzzy_control hierarchical_control partitional_control tadpole_control tsclust-controls tsclust_args
Class definition for 'TSClusters' and derived classes	FuzzyTSClusters FuzzyTSClusters-class HierarchicalTSClusters HierarchicalTSClusters-class PartitionalTSClusters PartitionalTSClusters-class TSClusters TSClusters-class
Methods for 'TSClusters'	initialize,TSClusters initialize,TSClusters-method plot,TSClusters,missing plot,TSClusters,missing-method plot.TSClusters predict,TSClusters predict,TSClusters-method predict.TSClusters show,TSClusters show,TSClusters-method TSClusters-methods tsclusters-methods update,TSClusters update,TSClusters-method update.TSClusters
Class definition for 'tsclustFamily'	tsclustFamily tsclustFamily-class
Coerce matrices or data frames to a list of time series	tslist
Subset of character trajectories data set	CharTraj CharTrajLabels CharTrajMV uciCT ucict
Wrapper for z-normalization	zscore

Package: dtwclust 6.0.0

dtwclust: Time Series Clustering Along with Optimizations for the Dynamic Time Warping Distance

Comparing Time-Series Clustering Algorithms in R Using the dtwclust Package

Parallelization considerations for dtwclust

Timing experiments for dtwclust

Citation

Readme and manuals

Help Manual

Usage by other packages (reverse dependencies)