/r4MAS

Package to translate stock synthesis input files into MAS inputs

Primary LanguageC++OtherNOASSERTION

r4MAS - R interface to the Metapopulation Assessment System

GitHub release (latest by date) R-CMD-check and release

The Metapopulation Assessment System (MAS) is a modular tool for creating and fitting fisheries stock assessment models. The R interface to MAS (r4MAS) allows users to build and run MAS models directly using the R language. It also includes functions to help translate between MAS and other stock assessment software and to plot outputs of MAS models, including estimates of key biological and observation parameters and derived quantities such as biological reference points, estimated biomass, and estimated numbers-at-age.

This tool is supported by the NOAA Fisheries Integrated Toolbox. More information can be found on the toolbox landing page

Getting started

Installation instructions

Since this package contains C++ files, you will need to ensure you have a C++ compiler installed. You can install a C++ compiler here, please make sure it is C++14 or more recent.

You will also need to have the Rcpp package installed.

Please install and load r4MAS from Github using the remotes package as follows:

install.packages("remotes")
remotes::install_github("nmfs-fish-tools/r4MAS")
library(r4MAS)

Windows users: Please ensure you have Rtools. If you receive errors related to C++ when loading r4MAS, it could be because your R installation uses the default Makevars.win file. To update your Makevars.win file, please run the following code in your R terminal:

dotR <- file.path(Sys.getenv("HOME"), ".R")
if (!file.exists(dotR)) 
  dir.create(dotR)
M <- file.path(dotR, "Makevars.win")
if (!file.exists(M)) 
  file.create(M)
cat("\nCXX14FLAGS=-O3 -Wno-unused-variable -Wno-unused-function",
    "CXX14 = $(BINPREF)g++ -m$(WIN) -std=c++1y",
    "CXX11FLAGS=-O3 -Wno-unused-variable -Wno-unused-function",
    file = M, sep = "\n", append = TRUE)

To get notifications about r4MAS, you can watch this GitHub project.

Creating a model

Once you've installed the package and have confirmed you can load it, we recommend starting with the introductory vignette to see an example of building and running a simple model within r4MAS. The write_test_data() function will generate simple dummy input data. You can replace these dummy data with your own data.

Disclaimer

“The United States Department of Commerce (DOC) GitHub project code is provided on an ‘as is’ basis and the user assumes responsibility for its use. DOC has relinquished control of the information and no longer has responsibility to protect the integrity, confidentiality, or availability of the information. Any claims against the Department of Commerce stemming from the use of its GitHub project will be governed by all applicable Federal law. Any reference to specific commercial products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply their endorsement, recommendation or favoring by the Department of Commerce. The Department of Commerce seal and logo, or the seal and logo of a DOC bureau, shall not be used in any manner to imply endorsement of any commercial product or activity by DOC or the United States Government.”

NOAA Fisheries

U.S. Department of Commerce | National Oceanographic and Atmospheric Administration | NOAA Fisheries