Package: caRamel 1.4

Fabrice Zaoui

caRamel: Automatic Calibration by Evolutionary Multi Objective Algorithm

The caRamel optimizer has been developed to meet the requirement for an automatic calibration procedure that delivers a family of parameter sets that are optimal with regard to a multi-objective target (Monteil et al. <doi:10.5194/hess-24-3189-2020>).

Authors:Nicolas Le Moine [aut], Celine Monteil [aut], Frederic Hendrickx [ctb], Fabrice Zaoui [aut, cre], Alban de Lavenne [ctb]

caRamel_1.4.tar.gz
caRamel_1.4.tar.gz(r-4.5-noble)caRamel_1.4.tar.gz(r-4.4-noble)
caRamel_1.3.tgz(r-4.4-emscripten)caRamel_1.3.tgz(r-4.3-emscripten)
caRamel.pdf |caRamel.html
caRamel/json (API)
NEWS

# Install 'caRamel' in R:
install.packages('caRamel', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/fzao/caramel/issues

Uses libs:
  • fortran– Runtime library for GNU Fortran applications

4.15 score 40 scripts 374 downloads 20 exports 7 dependencies

Last updated 3 months agofrom:bbf7af84f9. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 12 2024
R-4.5-linux-x86_64OKOct 12 2024

Exports:boxescaRamelCextrapCinterpCrecombinationCusecovardecrease_popDimprovedominatedominateddownsizematvcovnewXvalparetoplot_caramelplot_paretoplot_populationrselectval2rankvol_splx

Dependencies:abindgeometrylinproglpSolvemagicRcppRcppProgress

Dealing with constraints

Rendered fromConstraints.Rmdusingknitr::rmarkdownon Oct 12 2024.

Last update: 2020-09-17
Started: 2020-09-17

Using a Python function with caRamel

Rendered fromPythonFunction.Rmdusingknitr::rmarkdownon Oct 12 2024.

Last update: 2022-02-25
Started: 2022-02-25

Compute several Pareto fronts for a better global result

Rendered fromMultiPareto.Rmdusingknitr::rmarkdownon Oct 12 2024.

Last update: 2022-02-25
Started: 2022-02-25

Three ways to call the user functions

Rendered fromCarallel.Rmdusingknitr::rmarkdownon Oct 12 2024.

Last update: 2022-02-25
Started: 2022-02-25

Multi-caRamel optimization with MPI

Rendered fromMPI.Rmdusingknitr::rmarkdownon Oct 12 2024.

Last update: 2022-02-25
Started: 2022-02-25

Sensitivity of the Pareto front

Rendered fromSensitivity.Rmdusingknitr::rmarkdownon Oct 12 2024.

Last update: 2020-09-17
Started: 2020-09-17

Using caRamel on two benchmark tests

Rendered fromBenchmark.Rmdusingknitr::rmarkdownon Oct 12 2024.

Last update: 2022-02-25
Started: 2020-09-17