Releases: BlasBenito/distantia
Release list
Version 2.0.2
Changelog
-
Fixed error (r-devel only) in test file
tests/testthat/test-utils_new_time.R -
Function
zoo_plot()now has the argumentguide_positionto modify the legend position.
Version 2.0.1
This release only involves bug-fixes:
- Fixed bug in function cost_matrix_diagonal_weighted_cpp() where the additional weight of the diagonal movement was not being correctly applied. This change will result in slightly different psi values in distantia(), distantia_dtw(), and distantia_dtw_plot() when diagonal = TRUE (default).
- Fixed bug in function cost_path_cpp, which still produced diagonal cost matrices when diagonal = FALSE because weighted = TRUE turned diagonal to TRUE. Now weighted is set to FALSE when diagonal = FALSE. This resulted in negative scores for orthogonal least-cost paths.
- All C++ functions returning values of type double to R functions now round their output to the 8th decimal. This should mitigate discrepancies between R and C++ functions due to differences in how these systems round floating point numbers.
distantia 2.0
Version 2.0.0
- This new version involves a massive rewrite that will break any previous code based on this package. To install the previous version (1.0.2):
#install from CRAN archive
remotes::install_version(
package = "distantia",
version = "1.0.2"
)
#install from archive branch in GitHub
remotes::install_github(
repo = "https://github.com/BlasBenito/distantia",
ref = "v1.0.2"
)-
Version 2.0.0 is a complete package rewrite from the ground up:
-
All core functions have been rewritten in C++ for increased speed and memory efficiency, and proper R wrappers for these functions are provided.
-
All functions and their arguments follow more modern naming conventions, and simplified interfaces to improve the user experience.
-
Most time series operations use the zoo library underneath, ensuring data consistency, computational speed, and memory efficiency.
-
Lists of zoo objects, named "time series lists" ("tsl" for short) throughout the package documentation, are used to organize time series data.
-
A complete toolset to manage time series lists is provided. All functions belonging are named using the prefix
tsl_...(). There are tools to generate, aggregate, resample, transform, plot, map, and analyze univariate or multivariate regular or irregular time series. -
Most functions taking time series lists as inputs are parallelized using the future package, and progress bars for parallelized operations are available as well via the progressr package.
-
New example datasets from different disciplines and functions to generate simulated time series are shipped with the package to improve the learning experience.
-
distantia
1.0.2 added cluster compatibility for windows platforms