From 3cdc8a557d65878c919c67e21af4f4d19bebbccf Mon Sep 17 00:00:00 2001 From: Jakob Bossek Date: Wed, 8 Mar 2023 16:56:19 +0100 Subject: [PATCH] fix URLs, update NEWS --- NEWS | 9 +++++++++ NEWS.md | 32 +++++++++++++++++++++++++++++++- R/docs.parallelization.R | 2 +- README.Rmd | 25 ++++++++++++------------- README.md | 32 +++++++++++++++----------------- man/ecr_parallelization.Rd | 2 +- 6 files changed, 69 insertions(+), 33 deletions(-) diff --git a/NEWS b/NEWS index e7b7e58..9b2eafc 100644 --- a/NEWS +++ b/NEWS @@ -1,3 +1,12 @@ +ecr 2.2.1 +========= + +Fixes + +* Fixed warnings raised by r-devel versions +* Fixed typo in the docs of approximateRefSets yielding the function not being exported + + ecr 2.2.0 ========= diff --git a/NEWS.md b/NEWS.md index 9ce4bd7..d73934f 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,4 +1,34 @@ -# ecr 2.1.1 (upcoming) +# ecr 2.2.1 + +## Fixes + +* Fixed warnings raised by r-devel versions +* Fixed typo in the docs of approximateRefSets yielding the function not being exported + + +# ecr 2.2.0 + +## Fixes + +* Fixed bug in mutPolynomial where parameter lower was sanity-checked twice and upper not at all +* Fixed some typos in function documentations +* Fixed bug in updateParetoArchive: optimization direction, e.g., minimize first, maximize second objective are now respected + +## Added + +* More literature references in documentation + +## New features + +* Performance assessment for stochastic multi-objective optimization algorithms (very powerful tool) + * Flexible scatterplots in 2D and 3D + * Function to calculate a set of unary and binary performance indicators for a set of problems and algorithms + * Function to visualize indicator distrbutions + * Functions to perform statistical tests and output results as well-formatted LaTeX tables +* Exported helper functions getNumberOfChildren, getNumberOfParentsNeededForMating and generatesMultipleChildren + + +# ecr 2.1.1 ## Fixes diff --git a/R/docs.parallelization.R b/R/docs.parallelization.R index 1003a75..f262a8e 100644 --- a/R/docs.parallelization.R +++ b/R/docs.parallelization.R @@ -4,7 +4,7 @@ #' In ecr it is possible to parallelize the fitness function evaluation #' to make use, e.g., of multiple CP cores or nodes in a HPC cluster. #' For maximal flexibility this is realized by means of the \pkg{parallelMap} package -#' (see the \href{https://github.com/berndbischl/parallelMap}{official +#' (see the \href{https://github.com/mlr-org/parallelMap}{official #' GitHub page} for instructions on how to set up parallelization). #' The different levels of parallelization can be specified in the #' \code{parallelStart*} function. At them moment only the level diff --git a/README.Rmd b/README.Rmd index a45a6cd..551d9c9 100644 --- a/README.Rmd +++ b/README.Rmd @@ -4,12 +4,11 @@ output: github_document # ecr: Evolutionary Computation in R -[![CRAN Status Badge](http://www.r-pkg.org/badges/version/ecr)](http://cran.r-project.org/web/packages/ecr) -[![CRAN Downloads](http://cranlogs.r-pkg.org/badges/ecr)](http://cran.rstudio.com/web/packages/ecr/index.html) -[![CRAN Downloads](http://cranlogs.r-pkg.org/badges/grand-total/ecr?color=orange)](http://cran.rstudio.com/web/packages/ecr/index.html) +[![CRAN Status Badge](http://www.r-pkg.org/badges/version/ecr)](https://cran.r-project.org/package=ecr) +[![CRAN Downloads](http://cranlogs.r-pkg.org/badges/ecr)](https://cran.r-project.org/package=ecr) +[![CRAN Downloads](http://cranlogs.r-pkg.org/badges/grand-total/ecr?color=orange)](https://cran.r-project.org/package=ecr) [![R-CMD-check](https://github.com/jakobbossek/ecr2/workflows/R-CMD-check/badge.svg)](https://github.com/jakobbossek/ecr2/actions) -[![Codecov test coverage](https://codecov.io/gh/jakobbossek/ecr2/branch/master/graph/badge.svg)](https://codecov.io/gh/jakobbossek/ecr2?branch=master) -[![Research software impact](http://depsy.org/api/package/cran/ecr/badge.svg)](http://depsy.org/package/r/ecr) +[![Codecov test coverage](https://codecov.io/gh/jakobbossek/ecr2/branch/master/graph/badge.svg)](https://app.codecov.io/gh/jakobbossek/ecr2?branch=master) **NOTE:** The **ecr package v2** is the official follow-up package to my package [ecr v1](https://github.com/jakobbossek/ecr). I was unsatisfied with some design choices and thus decided to restructure and rewrite a lot. Changes are that manifold and fundamental, that I decided to set up a new repository, since most of the **ecr v1** functions are either deprecated, renamed, deleted or underlie substantial interface changes. @@ -31,13 +30,13 @@ The **ecr** package (version 2), *Evolutionary Computation in R*, is conceived a * Powerful logging mechanism. * Possibility to use custom representations/genotypes. * Possibility to define custom EA operators, i.e., mutation, variation and selection operators. -* Easy parallelization via [parallelMap](https://cran.r-project.org/web/packages/parallelMap/index.html) +* Easy parallelization via [parallelMap](https://cran.r-project.org/package=parallelMap) * Black-box approach for standard tasks. * Single- and multi-objective optimization. * Implementations of some popular performance indicators in Evolutionary Multi-Objective Optimization (EMOA), e.g., hyper-volume-indicator, epsilon indicator as well as R1, R2 and R3 indicator. * Predefined state-of-the-art EMOA algorithms NSGA-II, SMS-EMOA and AS-EMOA. -The best way to illustrate the process of algorithm design in **ecr** is by example. Assume we aim to find the global minimum of the highly multimodal one-dimensional Ackley-Function. The function is available in the R package [smoof](https://cran.r-project.org/web/packages/smoof/index.html) and may be initialized as follows: +The best way to illustrate the process of algorithm design in **ecr** is by example. Assume we aim to find the global minimum of the highly multimodal one-dimensional Ackley-Function. The function is available in the R package [smoof](https://cran.r-project.org/package=smoof) and may be initialized as follows: ```r library(ecr) library(ggplot2) @@ -106,11 +105,11 @@ print(res$best.x) ## Installation Instructions -The package will be available at [CRAN](http://cran.r-project.org) soon. Install the release version via: +The package is available at [CRAN](https://cran.r-project.org/package=ecr). Install the release version via: ```r install.packages("ecr") ``` -If you are interested in trying out and playing around with the current github developer version use the [devtools](https://github.com/hadley/devtools) package and type the following command in R: +If you are interested in trying out and playing around with the current github developer version use the [devtools](https://github.com/r-lib/devtools) package and type the following command in R: ```r devtools::install_github("jakobbossek/ecr2") @@ -122,13 +121,13 @@ To cite **ecr** please use: > Bossek, J. (2017). Ecr 2.0: A Modular Framework for Evolutionary Computation > in R. In Proceedings of the Genetic and Evolutionary Computation Conference > (GECCO) Companion (pp. 1187–1193). Berlin, Germany: -> ACM. http://doi.org/10.1145/3067695.3082470 +> ACM. https://doi.org/10.1145/3067695.3082470 In case you made use of **ecr**'s performance assessment tools please cite: > Bossek, J. (2018). Performance Assessment of Multi-objective Evolutionary > Algorithms with the R Package Ecr. In Proceedings of the Genetic and > Evolutionary Computation Conference Companion (pp. 1350–1356). Kyoto, Japan: -> ACM. http://doi.org/10.1145/3205651.3208312 +> ACM. https://doi.org/10.1145/3205651.3208312 BibTeX entries for LaTeX users: ``` @@ -141,7 +140,7 @@ BibTeX entries for LaTeX users: address = {Kyoto, Japan}, series = {GECCO '18}, title = {{Performance Assessment of Multi-objective Evolutionary Algorithms with the R Package Ecr}}, - url = {http://doi.acm.org/10.1145/3205651.3208312}, + url = {https://doi.acm.org/10.1145/3205651.3208312}, year = {2018} } @inproceedings{B2017ecr, @@ -153,7 +152,7 @@ BibTeX entries for LaTeX users: series = {GECCO '18}, address = {Berlin, Germany}, title = {{Ecr 2.0: A Modular Framework for Evolutionary Computation in R}}, - url = {http://doi.acm.org/10.1145/3067695.3082470}, + url = {https://doi.acm.org/10.1145/3067695.3082470}, year = {2017} } ``` diff --git a/README.md b/README.md index b1df6ce..2afcee0 100644 --- a/README.md +++ b/README.md @@ -4,16 +4,14 @@ [![CRAN Status -Badge](http://www.r-pkg.org/badges/version/ecr)](http://cran.r-project.org/web/packages/ecr) +Badge](http://www.r-pkg.org/badges/version/ecr)](https://cran.r-project.org/package=ecr) [![CRAN -Downloads](http://cranlogs.r-pkg.org/badges/ecr)](http://cran.rstudio.com/web/packages/ecr/index.html) +Downloads](http://cranlogs.r-pkg.org/badges/ecr)](https://cran.r-project.org/package=ecr) [![CRAN -Downloads](http://cranlogs.r-pkg.org/badges/grand-total/ecr?color=orange)](http://cran.rstudio.com/web/packages/ecr/index.html) +Downloads](http://cranlogs.r-pkg.org/badges/grand-total/ecr?color=orange)](https://cran.r-project.org/package=ecr) [![R-CMD-check](https://github.com/jakobbossek/ecr2/workflows/R-CMD-check/badge.svg)](https://github.com/jakobbossek/ecr2/actions) [![Codecov test -coverage](https://codecov.io/gh/jakobbossek/ecr2/branch/master/graph/badge.svg)](https://codecov.io/gh/jakobbossek/ecr2?branch=master) -[![Research software -impact](http://depsy.org/api/package/cran/ecr/badge.svg)](http://depsy.org/package/r/ecr) +coverage](https://codecov.io/gh/jakobbossek/ecr2/branch/master/graph/badge.svg)](https://app.codecov.io/gh/jakobbossek/ecr2?branch=master) **NOTE:** The **ecr package v2** is the official follow-up package to my @@ -67,7 +65,7 @@ of ecr are the following - Possibility to define custom EA operators, i.e., mutation, variation and selection operators. - Easy parallelization via - [parallelMap](https://cran.r-project.org/web/packages/parallelMap/index.html) + [parallelMap](https://cran.r-project.org/package=parallelMap) - Black-box approach for standard tasks. - Single- and multi-objective optimization. - Implementations of some popular performance indicators in @@ -80,9 +78,8 @@ of ecr are the following The best way to illustrate the process of algorithm design in **ecr** is by example. Assume we aim to find the global minimum of the highly multimodal one-dimensional Ackley-Function. The function is available in -the R package -[smoof](https://cran.r-project.org/web/packages/smoof/index.html) and -may be initialized as follows: +the R package [smoof](https://cran.r-project.org/package=smoof) and may +be initialized as follows: ``` r library(ecr) @@ -171,8 +168,9 @@ print(res$best.x) ## Installation Instructions -The package will be available at [CRAN](http://cran.r-project.org) soon. -Install the release version via: +The package is available at +[CRAN](https://cran.r-project.org/package=ecr). Install the release +version via: ``` r install.packages("ecr") @@ -180,7 +178,7 @@ install.packages("ecr") If you are interested in trying out and playing around with the current github developer version use the -[devtools](https://github.com/hadley/devtools) package and type the +[devtools](https://github.com/r-lib/devtools) package and type the following command in R: ``` r @@ -193,14 +191,14 @@ To cite **ecr** please use: \> Bossek, J. (2017). Ecr 2.0: A Modular Framework for Evolutionary Computation \> in R. In Proceedings of the Genetic and Evolutionary Computation Conference \> (GECCO) Companion (pp. 1187–1193). Berlin, Germany: \> ACM. - + In case you made use of **ecr**’s performance assessment tools please cite: \> Bossek, J. (2018). Performance Assessment of Multi-objective Evolutionary \> Algorithms with the R Package Ecr. In Proceedings of the Genetic and \> Evolutionary Computation Conference Companion (pp. 1350–1356). Kyoto, Japan: \> ACM. - + BibTeX entries for LaTeX users: @@ -213,7 +211,7 @@ BibTeX entries for LaTeX users: address = {Kyoto, Japan}, series = {GECCO '18}, title = {{Performance Assessment of Multi-objective Evolutionary Algorithms with the R Package Ecr}}, - url = {http://doi.acm.org/10.1145/3205651.3208312}, + url = {https://doi.acm.org/10.1145/3205651.3208312}, year = {2018} } @inproceedings{B2017ecr, @@ -225,7 +223,7 @@ BibTeX entries for LaTeX users: series = {GECCO '18}, address = {Berlin, Germany}, title = {{Ecr 2.0: A Modular Framework for Evolutionary Computation in R}}, - url = {http://doi.acm.org/10.1145/3067695.3082470}, + url = {https://doi.acm.org/10.1145/3067695.3082470}, year = {2017} } diff --git a/man/ecr_parallelization.Rd b/man/ecr_parallelization.Rd index 4a9c632..bbeb469 100644 --- a/man/ecr_parallelization.Rd +++ b/man/ecr_parallelization.Rd @@ -7,7 +7,7 @@ In ecr it is possible to parallelize the fitness function evaluation to make use, e.g., of multiple CP cores or nodes in a HPC cluster. For maximal flexibility this is realized by means of the \pkg{parallelMap} package -(see the \href{https://github.com/berndbischl/parallelMap}{official +(see the \href{https://github.com/mlr-org/parallelMap}{official GitHub page} for instructions on how to set up parallelization). The different levels of parallelization can be specified in the \code{parallelStart*} function. At them moment only the level