Add GitHub Actions CI for R CMD check

Author: simonbeyer1

.Rbuildignore

@@ -3,3 +3,4 @@
 ^src/.*\.c$
 ^src/.*\.so$
 
+^\.github$

.github/.gitignore

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

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

@@ -0,0 +1,52 @@
+# 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
+
+      - uses: r-lib/actions/check-r-package@v2
+        with:
+          upload-snapshots: true
+          build_args: 'c("--no-manual","--compact-vignettes=gs+qpdf")'
+          error-on: '"error"'

DESCRIPTION

@@ -35,9 +35,10 @@ Imports:
     abind,
     einsum,
     optimx
+Remotes:
+    simonbeyer1/CppODE@v1.0.0
 Suggests:
     MASS,
-    rPython,
     pander,
     knitr,
     rmarkdown,

README.Rmd

@@ -3,21 +3,53 @@ output:
   html_document: 
     keep_md: yes
 ---
-# dMod -- Dynamic Modeling and Parameter Estimation in R
+# dMod - Dynamic Modeling and Parameter Estimation in R
+
+<!-- badges: start -->
+
+[![R-CMD-check](https://github.com/JetiLab/dMod/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/JetiLab/dMod/actions/workflows/R-CMD-check.yaml)
+
+<!-- badges: end -->
 
 The dMod package is a framework that provides functions to generate ODEs of reaction networks, parameter transformations, observation functions, residual functions, etc. The framework follows the paradigm that derivative information should be used for optimization whenever possible. Therefore, all major functions produce and can handle expressions for symbolic derivatives.
 
 ## System requirements
 
-dMod uses the package [cOde](https://github.com/dkaschek/cOde) to set up ODE models as compiled C code (deSolve) or C++ code (Sundials). This means that **C and C++ compilers** are required on the system. On Linux, the compilers are installed by default. Windows users need to install [RTools](https://cran.r-project.org/bin/windows/Rtools/).
+dMod uses the package [cOde](https://github.com/dkaschek/cOde) to set up ODE models as compiled C code (deSolve) or [CppODE](https://github.com/simonbeyer1/CppODE) to autogenerate C++ code (Boost.Odeint). This means that **C and C++ compilers** are required on the system. On Linux, the compilers are installed by default. Windows users need to install [RTools](https://cran.r-project.org/bin/windows/Rtools/).
+
+For **parallelization**, dMod uses `mclapply()` on Linux and macOS. On Windows, parallelization is implemented via the `foreach` package using `%dopar%`.
+
+## Installation from GitHub
+
+To **install dMod from the GitHub repository**, it is convenient to use **RStudio**.
+
+1.  Create a new project via\
+    **File → New Project → Version Control → Git**.
+
+2.  Use the repository URL\
+
+```         
+
+[https://github.com/jetilab/dMod](https://github.com/jetilab/dMod)
+```
+
+and create the project.
+
+3.  Install all required package dependencies (including GitHub dependencies specified via `Remotes`) by running:
+
+``` r
+remotes::install_deps(dependencies = TRUE)
+```
+
+4.  Open the **Build** tab in RStudio and click **Build and Reload** (or **Install**).
 
-For **parallelization**, dMod uses `mclapply()` on Linux and Mac. For Windows, parallelization is implemented via the `foreach` package using `%dopar%`.
+Once these steps are completed, it should be possible to run the following example.
 
-To **install dMod from the git repository**, it is convenient to use RStudio. Create a "New Project" -> "Version Control" -> "Git". Use the address `https://github.com/dkaschek/dMod` and create project. Next, go to menu "Build" -> "Build and Reload". Once theses steps are completed, it should be possible to run the following example. 
+------------------------------------------------------------------------
 
-When installing dMod from github, you use the development version of dMod. Further packages might be needed to install. In particular, please make sure that if you install dMod from github, also [cOde](https://github.com/dkaschek/cOde) is installed from github.
+If **PEtab support** is required, **libSBML** is needed in addition. Installation and usage instructions can be found in the wiki under [Support for PEtab](https://github.com/dkaschek/dMod/wiki/Support-for-PEtab).
 
-If **PEtab support** is wanted, libSBML will be required in addition. Installation and usage instructions can be found in the wiki under [Support for PEtab](https://github.com/dkaschek/dMod/wiki/Support-for-PEtab)
+------------------------------------------------------------------------
 
 
 
@@ -177,7 +209,7 @@ plotProfile(profiles)
 # Cleaning step
 dlls <- list.files(pattern = "\\.(so|dll)$")
 for (d in dlls) try(dyn.unload(d), silent = TRUE)
-files <- list.files(pattern = "^(enzymeKinetics|obsfn).*(c|o|dll|so)$")
+files <- list.files(pattern = "^(enzymeKinetics|obsfn|expl_parfn_noDegradation|expl_parfn_withDegradation).*(c|cpp|o|dll|so)$")
 unlink(files)
 
 ```

README.html

@@ -1,18 +1,57 @@
+---
+output: 
+  html_document: 
+    keep_md: yes
+---
 # dMod - Dynamic Modeling and Parameter Estimation in R
 
+<!-- badges: start -->
+
+[![R-CMD-check](https://github.com/JetiLab/dMod/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/JetiLab/dMod/actions/workflows/R-CMD-check.yaml)
+
+<!-- badges: end -->
+
 The dMod package is a framework that provides functions to generate ODEs of reaction networks, parameter transformations, observation functions, residual functions, etc. The framework follows the paradigm that derivative information should be used for optimization whenever possible. Therefore, all major functions produce and can handle expressions for symbolic derivatives.
 
 ## System requirements
 
 dMod uses the package [cOde](https://github.com/dkaschek/cOde) to set up ODE models as compiled C code (deSolve) or [CppODE](https://github.com/simonbeyer1/CppODE) to autogenerate C++ code (Boost.Odeint). This means that **C and C++ compilers** are required on the system. On Linux, the compilers are installed by default. Windows users need to install [RTools](https://cran.r-project.org/bin/windows/Rtools/).
 
-For **parallelization**, dMod uses `mclapply()` on Linux and Mac. For Windows, parallelization is implemented via the `foreach` package using `%dopar%`.
+For **parallelization**, dMod uses `mclapply()` on Linux and macOS. On Windows, parallelization is implemented via the `foreach` package using `%dopar%`.
+
+## Installation from GitHub
+
+To **install dMod from the GitHub repository**, it is convenient to use **RStudio**.
+
+1.  Create a new project via\
+    **File → New Project → Version Control → Git**.
+
+2.  Use the repository URL\
 
-To **install dMod from the git repository**, it is convenient to use RStudio. Create a "New Project" -\> "Version Control" -\> "Git". Use the address `https://github.com/dkaschek/dMod` and create project. Next, go to menu "Build" -\> "Build and Reload". Once theses steps are completed, it should be possible to run the following example.
+```         
+
+[https://github.com/jetilab/dMod](https://github.com/jetilab/dMod)
+```
+
+and create the project.
+
+3.  Install all required package dependencies (including GitHub dependencies specified via `Remotes`) by running:
+
+``` r
+remotes::install_deps(dependencies = TRUE)
+```
+
+4.  Open the **Build** tab in RStudio and click **Build and Reload** (or **Install**).
+
+Once these steps are completed, it should be possible to run the following example.
+
+------------------------------------------------------------------------
+
+If **PEtab support** is required, **libSBML** is needed in addition. Installation and usage instructions can be found in the wiki under [Support for PEtab](https://github.com/dkaschek/dMod/wiki/Support-for-PEtab).
+
+------------------------------------------------------------------------
 
-When installing dMod from github, you use the development version of dMod. Further packages might be needed to install. In particular, please make sure that if you install dMod from github, also [cOde](https://github.com/dkaschek/cOde) and [CppODE](https://github.com/simonbeyer1/CppODE) are installed from github.
 
-If **PEtab support** is wanted, libSBML will be required in addition. Installation and usage instructions can be found in the wiki under [Support for PEtab](https://github.com/dkaschek/dMod/wiki/Support-for-PEtab)
 
 ## Simple example: enzyme kinetics
 
@@ -155,6 +194,7 @@ plot((g*x*p)(times, myfit$argument), data)
 
 ![](README_files/figure-html/trust-1.png)<!-- -->
 
+
 ### Compute the profile likelihood to analyze parameter identifiability
 
 ``` r
@@ -167,3 +207,8 @@ plotProfile(profiles)
 ```
 
 ![](README_files/figure-html/profiles-1.png)<!-- -->
+
+
+
+
+