Package: twdtw 1.0-2
twdtw: Time-Weighted Dynamic Time Warping
Implements Time-Weighted Dynamic Time Warping (TWDTW), a measure for quantifying time series similarity. The TWDTW algorithm, described in Maus et al. (2016) <doi:10.1109/JSTARS.2016.2517118> and Maus et al. (2019) <doi:10.18637/jss.v088.i05>, is applicable to multi-dimensional time series of various resolutions. It is particularly suitable for comparing time series with seasonality for environmental and ecological data analysis, covering domains such as remote sensing imagery, climate data, hydrology, and animal movement. The 'twdtw' package offers a user-friendly 'R' interface, efficient 'Fortran' routines for TWDTW calculations, flexible time weighting definitions, as well as utilities for time series preprocessing and visualization.
Authors:
twdtw_1.0-2.tar.gz
twdtw_1.0-2.zip(r-4.5)twdtw_1.0-2.zip(r-4.4)twdtw_1.0-2.zip(r-4.3)
twdtw_1.0-2.tgz(r-4.4-x86_64)twdtw_1.0-2.tgz(r-4.4-arm64)twdtw_1.0-2.tgz(r-4.3-x86_64)twdtw_1.0-2.tgz(r-4.3-arm64)
twdtw_1.0-2.tar.gz(r-4.5-noble)twdtw_1.0-2.tar.gz(r-4.4-noble)
twdtw_1.0-2.tgz(r-4.4-emscripten)
twdtw.pdf |twdtw.html✨
twdtw/json (API)
NEWS
| # Install 'twdtw' in R: |
| install.packages('twdtw', repos = c('https://vwmaus.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/vwmaus/twdtw/issues
Last updated 1 years agofrom:d740a38151. Checks:9 OK. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Jan 23 2025 |
| R-4.5-win-x86_64 | OK | Jan 23 2025 |
| R-4.5-linux-x86_64 | OK | Jan 23 2025 |
| R-4.4-win-x86_64 | OK | Jan 23 2025 |
| R-4.4-mac-x86_64 | OK | Jan 23 2025 |
| R-4.4-mac-aarch64 | OK | Jan 23 2025 |
| R-4.3-win-x86_64 | OK | Jan 23 2025 |
| R-4.3-mac-x86_64 | OK | Jan 23 2025 |
| R-4.3-mac-aarch64 | OK | Jan 23 2025 |
Exports:date_to_numeric_cyclemax_cycle_lengthplot_cost_matrixto_date_timetwdtw
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Convert Date/POSIXct to a Numeric Cycle | date_to_numeric_cycle |
| Calculate the Maximum Possible Value of a Time Cycle | max_cycle_length |
| Plot TWDTW cost matrix | plot_cost_matrix |
| Print method for twdtw class | print.twdtw |
| Convert to Date or POSIXct Format | to_date_time |
| Calculate Time-Weighted Dynamic Time Warping (TWDTW) distance | twdtw twdtw.data.frame twdtw.matrix |
