Added R-CMD-check github workflow for CI/CD.

.Rbuildignore

@@ -5,4 +5,4 @@
 ^docs/.*$
 ^.*\.o$
 ^.*\.a$
-^\.github$
+^\.github$

.github/.gitignore

@@ -0,0 +1 @@
+*.html

.github/workflows/R-CMD-check.yaml

@@ -0,0 +1,62 @@
+# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
+# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
+on:
+  push:
+    branches: [main, master]
+  pull_request:
+
+name: R-CMD-check.yaml
+
+permissions: read-all
+
+jobs:
+  R-CMD-check:
+    runs-on: ${{ matrix.config.os }}
+
+    name: ${{ matrix.config.os }} (${{ matrix.config.r }})
+
+    strategy:
+      fail-fast: false
+      matrix:
+        config:
+          - {os: macos-latest,   r: 'release'}
+          - {os: windows-latest, r: 'release'}
+          - {os: ubuntu-latest,   r: 'devel', http-user-agent: 'release'}
+          - {os: ubuntu-latest,   r: 'release'}
+          - {os: ubuntu-latest,   r: 'oldrel-1'}
+
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+      R_KEEP_PKG_SOURCE: yes
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/setup-pandoc@v2
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          r-version: ${{ matrix.config.r }}
+          http-user-agent: ${{ matrix.config.http-user-agent }}
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::rcmdcheck
+          needs: check
+
+      #- name: Build
+      #  run: |
+      #      R CMD build .
+
+      - uses: r-lib/actions/check-r-package@v2
+        with:
+          upload-results: true
+          upload-snapshots: true
+          build_args: 'c("--no-manual","--compact-vignettes=gs+qpdf")'
+
+      # - name: Upload test results
+      #   uses: actions/upload-artifact@v4
+      #   with:
+      #     name: samplelim_${{ matrix.config.os }}
+      #     path: samplelim*.tar.gz

DESCRIPTION

@@ -32,5 +32,5 @@ Suggests:
     GGally,
     testthat (>= 3.0.0)
 Config/testthat/edition: 3
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 VignetteBuilder: knitr

NAMESPACE

@@ -1,5 +1,6 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(plot,lim)
 export(Hpolytope)
 export(df2lim)
 export(full2red)
@@ -14,6 +15,8 @@ importFrom(Rcpp,evalCpp)
 importFrom(Rcpp,loadModule)
 importFrom(Rcpp,sourceCpp)
 importFrom(Rglpk,Rglpk_solve_LP)
+importFrom(igraph,graph_from_adjacency_matrix)
+importFrom(igraph,plot.igraph)
 importFrom(limSolve,lsei)
 importFrom(methods,new)
 importFrom(stats,cov)

R/plot_lim.R

@@ -1,37 +1,50 @@
-plot.lim <- function(lim, seed=NULL, ...) {
+#' Plot a metabolic network
+#' 
+##' @param x An object of class `lim` containing a component `Flowmatrix`.
+#' @param seed The seed for the PRNG of the R session
+#' @param ... Additionnal arguments to be passed to the function \code{plot.igraph()} from the package \code{\\{igraph\\}}.
+#' 
+#' @return Returns NULL, invisibly.
+#' @method plot lim
+#' 
+#' @examples
+#' DF <- system.file("extdata", "DeclarationFileBOWF-short.txt", package = "samplelim")
+#' BOWF <- df2lim(DF)
+#' plot(BOWF)
+plot.lim <- function(x, seed=NULL, ...) {
   # Check if 'Flowmatrix' exists in the object 'lim'
-  if (!exists("Flowmatrix", where = lim)) {
+  if (!exists("Flowmatrix", where = x)) {
     stop("'Flowmatrix' does not exist in used 'lim' object.")
   }
 
   # Check if 'Flowmatrix' is a matrix
-  if (!is.matrix(lim$Flowmatrix)) {
+  if (!is.matrix(x$Flowmatrix)) {
     stop("'Flowmatrix' from 'lim' object is not a matrix. ")
   }
 
   # Check if the dimensions of the matrix are equal to the expected dimensions
   # As dimensions depends of NComponents and NExternal we first check if they exist and are integers
-  if (!exists("NComponents", where = lim)){
+  if (!exists("NComponents", where = x)){
     stop("'NComponents' does not exist in used 'lim' object.")
   }
 
-  if (!is.integer(lim$NComponents)){
+  if (!is.integer(x$NComponents)){
     stop("'NComponents' from 'lim' object must be an integer.")
   }
 
-  if (!exists("NExternal", where = lim)){
+  if (!exists("NExternal", where = x)){
     stop("'NExternal' does not exist in used 'lim' object.")
   }
 
-  if (!is.integer(lim$NExternal)){
+  if (!is.integer(x$NExternal)){
     stop("'NExternal' from 'lim' object must be an integer.")
   }
 
   # Calculate the number of nodes
-  N_nodes <- lim$NComponents + lim$NExternal
+  N_nodes <- x$NComponents + x$NExternal
 
   expected_dim <- c(N_nodes, N_nodes)
-  if (all(dim(lim$Flowmatrix) != expected_dim)) {
+  if (all(dim(x$Flowmatrix) != expected_dim)) {
     stop("Flowmatrix from 'lim' object does not match the expected dimension.")
   }
 
@@ -40,8 +53,8 @@ plot.lim <- function(lim, seed=NULL, ...) {
     set.seed(seed) 
   }
 
-  adjacency_matrix <- as.matrix(lim$Flowmatrix > 0)
-  model_graph <- graph_from_adjacency_matrix(adjacency_matrix)
-  plot.igraph(model_graph, ...)
+  adjacency_matrix <- as.matrix(x$Flowmatrix > 0)
+  model_graph <- igraph::graph_from_adjacency_matrix(adjacency_matrix)
+  igraph::plot.igraph(model_graph, ...)
 
 }

R/samplelim.R

@@ -0,0 +1,35 @@
+#' MCMC sampling algorithms for linear inverse models
+#' 
+#' @description
+#' The package provides efficient implementations (C++ encoded) of 
+#' Monte Carlo Markov Chains (MCMC) algorithms for uniformly sampling high-dimensional polytopes. 
+#' It is particularly aimed at handling linear inverse models (LIM) in metabolic 
+#' (trophic, biochemical or urban) networks. 
+#' Some support functions are also included to facilitate its use by practitioners.
+#' @keywords 
+#' polytope
+#' sampling
+#' mcmc
+#' lim
+#' mirror-walk
+#' billard-walk
+#' trophic-network
+#' urban-network
+#' biochemical-network
+#' metabolic-network
+#' @references {
+#' D. Van Oevelen, K. Van den Meersche, F. J. R. Meysman, K. Soetaert, 
+#' J. J. Middelburg and A. F. Vézina, 
+#' \emph{Quantifying Food Web Flows Using Linear Inverse Models},
+#'  Ecosystems \strong{13}, 32-45 (2010).
+#' 
+#' B.T. Polyak and E.N. Gryazina, 
+#' \emph{Billiard walk - a new sampling algorithm for control and optimization}, 
+#' IFAC Proceedings Volumes, \strong{47(3)}, 6123-6128 (2014).
+#' 
+#' V. Girardin, T. Grente, N. Niquil and P. Regnault,
+#' \emph{Comparing and updating R packages of MCMC Algorithms for 
+#' Linear Inverse Modeling of Metabolic Networks}, to appear in
+#' Communications in Statistics - Simulation and Computation (2025)
+#' }
+"_PACKAGE"

README.Rmd

@@ -11,6 +11,7 @@ knitr::opts_chunk$set(echo = TRUE, eval = TRUE)
 ![](https://img.shields.io/badge/lifecycle-maturing-blue.svg)
 [![Project Status: Active – The project has reached a stable, usable state and is being actively developed.](http://www.repostatus.org/badges/latest/active.svg)](http://www.repostatus.org/#active)
 [![License: LGPL v3](https://img.shields.io/badge/License-LGPL%20v3-blue.svg)](https://www.gnu.org/licenses/lgpl-3.0)
+[![R-CMD-check](https://github.com/pregnault/samplelim/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/pregnault/samplelim/actions/workflows/R-CMD-check.yaml)
 [![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/regexplain)](https://cran.r-project.org/package=samplelim)
 
 The package `{samplelim}` for the R statistical software provides efficient implementations (C++ encoded) of Monte Carlo Markov Chains (MCMC) algorithms for uniformly sampling high-dimensional polytopes.