Warning
Version 2.0.0 of distantia is a full re-write from scratch and will break existing workflows. Please refer to the Changelog for details before updating.
Summary
The distantia package has undergone a major overhaul to enhance both performance and usability. Core functions are now implemented in C++ for faster execution and improved memory efficiency, with streamlined R wrappers to simplify user interaction.
Function and argument names have been updated to follow modern conventions, offering a more intuitive experience. Additionally, most time series operations are now powered by the zoo library, providing consistent data handling and computational efficiency.
Version 2.0 introduces the concept of “time series lists” (tsl), using lists of zoo objects to manage and organize time series data. A full suite of functions prefixed with tsl_...() allows users to easily generate, resample, transform, analyze, and visualize univariate, multivariate, regular, or irregular time series. Many of these functions support parallel execution via the future package, with progress indicators provided by progressr for a smoother user experience.
Finally, to further aid learning and experimentation, new example datasets and tools for generating simulated time series are also included.
Citation
If you find this package useful, please cite it as:
Blas M. Benito, H. John B. Birks (2020). distantia: an open-source toolset to quantify dissimilarity between multivariate ecological time-series. Ecography, 43(5), 660-667. doi: 10.1111/ecog.04895.
Blas M. Benito (2024). distantia: A Toolset for Time Series Dissimilarity Analysis. R package version 2.0.0. url: https://blasbenito.github.io/distantia/.