Francisco Bischoff - 18 Aug 2022
| | Build | Dev | |----------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | Windows | | | | Coverage | | |
This version is being maintained to keep up with CRAN standards. As soon as possible a new version (with possible breaking changes) with less dependencies will be released later in 2022 or beginning of 2023.
R Functions implementing UCR Matrix Profile Algorithm (http://www.cs.ucr.edu/~eamonn/MatrixProfile.html).
This package allows you to use the Matrix Profile concept as a toolkit.
This package provides:
# Basic workflow:
matrix <- tsmp(data, window_size = 30) %>%
find_motif(n_motifs = 3) %T>%
plot()
# SDTS still have a unique way to work:
model <- sdts_train(data, labels, windows)
result <- sdts_predict(model, data, round(mean(windows)))
Please refer to the User Manual for more details.
Please be welcome to suggest improvements.
set.seed(2018)
data <- cumsum(sample(c(-1, 1), 40000, TRUE))
WIP in this version
# Install the released version from CRAN
install.packages("tsmp")
# Or the development version from GitHub:
# install.packages("devtools")
devtools::install_github("matrix-profile-foundation/tsmp")
head()
, tail()
, [
, etc.)Our next step unifying the Matrix Profile implementation in several programming languages.
Visit: Matrix Profile Foundation
Please note that the ‘tsmp’ project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
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