Merge pull request #4 from CeresBarros/achubaty-patch-1

try fixing rmd render workflow

.github/workflows/render-validation-rmd.yaml

@@ -31,6 +31,7 @@ jobs:
 
       - uses: r-lib/actions/setup-r@v2
         with:
+          r-version: '4.2.1'
           use-public-rspm: true
 
       - name: Install additional system dependencies
@@ -47,36 +48,36 @@ jobs:
             libxml2-dev \
             python3-gdal
 
-      - name: Install remotes, knitr, rmarkdown, bookdown
+      - name: Set R library
         run: |
-          install.packages("remotes")
-          remotes::install_cran("rmarkdown")
-          remotes::install_cran("knitr")
-          remotes::install_cran("bookdown")
+          pkgPath <- file.path("packages", version$platform, paste0(version$major, ".", strsplit(version$minor, "[.]")[[1]][1]))
+          dir.create(dirname(pkgPath), recursive = TRUE)
+          file.symlink(Sys.getenv("R_LIBS_USER"), pkgPath)
         shell: Rscript {0}
 
-      - name: Install SpaDES packages
-        run: |
-          install.packages("SpaDES", dependencies = TRUE)
-          remotes::install_github("PredictiveEcology/SpaDES.docs@development")
-        shell: Rscript {0}
+      - uses: PredictiveEcology/actions/install-Require@v0
+        with:
+          GitTag: '5c44205bf407f613f53546be652a438ef1248147'
+
+      - uses: PredictiveEcology/actions/install-Rmd-pkgs@v0
+
+      - uses: PredictiveEcology/actions/install-SpaDES@v0
 
-      - name: Install module package dependencies
+      - name: Install additional packages
         run: |
-          mods <- dir("R/SpaDES/m")
-          pkgs <- sapply(mods, function(m) SpaDES.core::packages(modules = m, paths = "R/SpaDES/m"))
-          pkgs <- unique(unlist(pkgs))
-          Require::Require(pkgs)
+          options(repos = c(CRAN = "https://packagemanager.rstudio.com/all/__linux__/focal/latest", CRAN = "https://cran.rstudio.com"))
+          Require::Require(c("PredictiveEcology/LandR@development",
+                          "ggspatial", "ggpubr", "cowplot", "DiagrammeR"), require = FALSE)
         shell: Rscript {0}
 
       - name: Render validation Rmd
         run: |
-          rmarkdown::render("R/SpaDES/global.Rmd", encoding = "UTF-8", output_dir = "R/SpaDES")
+          rmarkdown::render("R/SpaDES/global.Rmd", encoding = "UTF-8", output_dir = "R/SpaDES", knit_root_dir = getwd())
         shell: Rscript {0}
 
       - name: Commit results
         run: |
           git config user.email "[email protected]"
           git config user.name "GitHub Actions"
-          git commit Biomass_borealDataPrep.html -m 'Re-build Biomass_borealDataPrep.Rmd' || echo "No changes to commit"
+          git commit R/SpaDES/global.html -m 'Re-build R/SpaDES/global.Rmd' || echo "No changes to commit"
           git push https://${{github.actor}}:${{secrets.GITHUB_TOKEN}}@github.com/${{github.repository}}.git HEAD:${{github.ref}} || echo "No changes to commit"

R/SpaDES/global.R

@@ -21,8 +21,8 @@ if (!"remotes" %in% installed.packages()) {
 }
 
 if (!"Require" %in% installed.packages(lib.loc = pkgPath) ||
-    packageVersion("Require", lib.loc = pkgPath) < "0.1.6.9005") {
-  remotes::install_github("PredictiveEcology/Require@8ac756d66bc145f226f39e703e3787d3aed159f2",
+    packageVersion("Require", lib.loc = pkgPath) < "0.1.6.9014") {
+  remotes::install_github("PredictiveEcology/Require@5c44205bf407f613f53546be652a438ef1248147",
                           upgrade = FALSE, force = TRUE)
 }
 ## use binary linux packages if on Ubuntu
@@ -33,29 +33,30 @@ Require::Require("PredictiveEcology/SpaDES.project@6d7de6ee12fc967c7c60de44f1aa3
 
 modulePath <- "R/SpaDES/m"
 SpaDES.project::getModule(modulePath = modulePath,
-                          c("PredictiveEcology/Biomass_speciesData@505fa065399da93e817424373ee1160e46703ce3",
-                            "PredictiveEcology/Biomass_borealDataPrep@6cd0c1242cdb95f7432d37becfb2f8dd03642e76",
-                            "PredictiveEcology/Biomass_core@5f7691af755a651579408f37bf292a7274b7678f",
-                            "PredictiveEcology/Biomass_validationKNN@ec9b5362aa0d07eee844fcdb74e33abeeda89b4b",
-                            "CeresBarros/Biomass_speciesParameters@31b66f22f915cd8b5774e5b56359dc2406691895"))
+                          c("PredictiveEcology/Biomass_speciesData@1dc71ebc6181b6eb9b0813db2ca4184488312197",
+                            "PredictiveEcology/Biomass_borealDataPrep@4f9858f767a2c19d2bceacf80047dd5eac661e73",
+                            "PredictiveEcology/Biomass_core@d36a902c23283ddd1c38d6e59ce86047ccdf14d8",
+                            "PredictiveEcology/Biomass_validationKNN@30829e0a9465513169a21c0477cfffd5f9a5c936",
+                            "PredictiveEcology/Biomass_speciesParameters@c7970580c1a5e1817d8cfeb4675076748eb50917"))
 
 pkgSnapshotFile <- file.path("packages",
                              paste0("pkgSnapshot_",
                                     paste0(version$major, "_", strsplit(version$minor, "[.]")[[1]][1]),
                                     ".txt"))
 
 if (file.exists(pkgSnapshotFile)) {
-  Require::Require(packageVersionFile = pkgSnapshotFile,
-                   require = FALSE, standAlone = TRUE)
+  Require::Require(packageVersionFile = pkgSnapshotFile, require = FALSE, standAlone = TRUE)
 } else {
   outs <- SpaDES.project::packagesInModules(modulePath = modulePath)
   Require::Require(c(unname(unlist(outs)),
-                     "PredictiveEcology/SpaDES.experiment@development",
+                     "PredictiveEcology/SpaDES.experiment@91bfad98d67ea2b7fcee3ea0115f8746e47534ad",
                      "devtools", "ggspatial", "ggpubr", "cowplot"),
                    require = FALSE, standAlone = TRUE)
 
   ## the next line is commented to prevent accidental execution, but can be run to generate a missing pkg snapshot
-  # Require::pkgSnapshot(pkgSnapshotFile, libPaths = pkgPath, standAlone = TRUE)
+  Require::pkgSnapshot(pkgSnapshotFile, libPaths = pkgPath,
+                       standAlone = TRUE, exact = TRUE, purge = TRUE,
+                       includeBase = FALSE)
 }
 
 ## load packages
@@ -112,7 +113,6 @@ GAemail <- NULL
 googledrive::drive_auth(email = GAemail)
 
 ## Get necessary objects like the study area.
-x11() ## open a new plotting window - avoids errors if the current one is too small.
 devtools::source_url(paste0("https://raw.githubusercontent.com/CeresBarros/",
                             "LandRBiomass_publication/repPkgInstall/R/SpaDES/",
                             "1_simObjects.R?raw=TRUE"))

R/SpaDES/global.Rmd

@@ -1,29 +1,39 @@
 ---
 title: "LandR Publication Simulations"
 author: "Ceres Barros"
-date: "22/01/2021"
+date: "Last updated: `r Sys.Date()`"
 output:
-  html_document:
+  bookdown::html_document2:
+    toc: true
+    toc_float: true
+    toc_depth: 4
+    theme: sandstone
+    number_sections: false
+    df_print: paged
     keep_md: yes
 editor_options:
   chunk_output_type: console
+  markdown: 
+    wrap: 80
+always_allow_html: true
 ---
 
-# A simplified example of publication runs
-For full code used in publication see `global.R`
+This provides a simplified example of publication runs. For full code used in 
+publication see `global.R`
 
 ```{r setup, include = FALSE}
 isInteractive <- interactive()
 knitr::opts_chunk$set(echo = TRUE, eval = isInteractive, results = "hold",
                       cache = 2)
 pkgPath <- file.path("packages", version$platform,
                      paste0(version$major, ".", strsplit(version$minor, "[.]")[[1]][1]))
-dir.create(pkgPath, recursive = TRUE)
 .libPaths(pkgPath, include.site = FALSE)
+
+modulePath <- "R/SpaDES/m"
 ```
 
-## Package installation
-```{pkgInstall}
+# Package installation and setup
+```{r pkgInstall}
 ## set CRAN repo
 options(repos = c(CRAN = "https://cloud.r-project.org"))
 
@@ -38,8 +48,8 @@ if (!"remotes" %in% installed.packages()) {
 }
 
 if (!"Require" %in% installed.packages(lib.loc = pkgPath) ||
-    packageVersion("Require", lib.loc = pkgPath) < "0.1.6.9005") {
-  remotes::install_github("PredictiveEcology/Require@8ac756d66bc145f226f39e703e3787d3aed159f2",
+    packageVersion("Require", lib.loc = pkgPath) < "0.1.6.9014") {
+  remotes::install_github("PredictiveEcology/Require@5c44205bf407f613f53546be652a438ef1248147",
                           upgrade = FALSE, force = TRUE)
 }
 
@@ -62,14 +72,13 @@ pkgSnapshotFile <- file.path("packages",
                                     paste0(version$major, "_", strsplit(version$minor, "[.]")[[1]][1]),
                                     ".txt"))
 
-Require::Require(packageVersionFile = pkgSnapshotFile,
-                 require = FALSE, standAlone = TRUE)
+Require::Require(packageVersionFile = pkgSnapshotFile, require = FALSE, standAlone = TRUE)
 ```
 
-## Package setup
-```{r init, eval = TRUE, results = FALSE}
+## Package loading and options, folder directories setup
+```{r init, eval = TRUE, results = FALSE, messages = FALSE, warnings = FALSE}
 Require::Require(c("raster", "terra", "dplyr", "data.table", "future",
-                   "SpaDES.core", "LandR", "reproducible",
+                   "SpaDES.core", "LandR", "reproducible", "ggplot2",
                    "ggspatial", "ggpubr", "cowplot"),
                  upgrade = FALSE, install = FALSE)
 
@@ -96,9 +105,9 @@ simPaths <- list(cachePath = Require::normPath(file.path("R/SpaDES/cache", simPa
                  , outputPath = Require::normPath(file.path("R/SpaDES/outputs", simPathName, runName)))
 ```
 
-## Simulation setup - part 1 
+# Simulation setup
 
-### Get study area and other necessary objects 
+## Part 1 - Get study area and other necessary objects 
 
 ```{r simulationSetup}
 ## Get necessary objects -----------------------
@@ -107,7 +116,7 @@ devtools::source_url(paste0("https://raw.githubusercontent.com/CeresBarros/",
                             "1_simObjects.R?raw=TRUE"))
 ```
 
-## Simulation setup - part 2 - species layers
+## Part 2 - Species layers
 
 ```{r simulationSetup2}
 ## Run Biomass_speciesData to get species layers
@@ -143,16 +152,9 @@ rstLCC2005 <- Cache(prepInputs,
 
 ```{r loadSppLayers, include=FALSE, eval = !isInteractive}
 simOutSpeciesLayers <- loadSimList(file.path("GitHubActionsSims", simPathName, runName, paste0("simList_speciesLayers", runName, ".qs")))
-
-## subset sppEquivalencies
-sppEquivalencies_CA <- sppEquivalencies_CA[Boreal %in% names(simOutSpeciesLayers$speciesLayers)]
-sppColorVect <- sppColorVect[c(names(simOutSpeciesLayers$speciesLayers), "Mixed")]
-
-## Get land-cover raster now that we have a rasterToMatchLarge
-rstLCC2005 <- raster(file.path("GitHubActionsSims", simPathName, runName, "rstLCC_966512e152b53d9b.tif"))
 ```
 
-## Simulation setup - part 3 - module parameters and outputs
+## Part 3 - Module parameters and outputs
 
 * `vegLeadingProportion` indicates what proportion the stand must be in one species group for it to be leading.
 If 0, then there is never a notion of "mixed" vegetation types and a species is a leading species if it has the highest relative biomass in the pixel.
@@ -260,7 +262,7 @@ simOutputs <- data.frame(
               saveTime = unique(seq(simTimes$start, simTimes$end, by = 1)),
               eventPriority = 1,
               stringsAsFactors = FALSE)
-  )
+)
 simOutputs <- rbind(simOutputs, 
                     data.frame(objectName = "pixelGroupMap",
                                saveTime = unique(seq(simTimes$start, simTimes$end, by = 1)),
@@ -300,7 +302,7 @@ LandRBiomass_simInit <- loadSimList(file.path("GitHubActionsSims", simPathName,
 objectDiagram(LandRBiomass_simInit, width = 1000, height = 2500)
 ```
 
-## Run simulation
+# Run simulation
 
 Here we run just one repetition
 
@@ -310,11 +312,6 @@ LandRBiomass_sim <- spades(LandRBiomass_simInit, .plotInitialTime = simTimes$sta
 saveSimList(LandRBiomass_sim, file.path(simPaths$outputPath, paste0("simList_LandRBiomass_sim_1rep_", runName, ".qs")))
 ```
 
-```{r loadSimulation, include=FALSE, eval = !isInteractive}
-## this has been commented because the simLists obj is not used at the moment.
-# LandRBiomass_sim <- qs::qread(file.path("GitHubActionsSims", simPathName, runName, paste0("simList_LandRBiomass_sim_", runName, ".qs")))
-```
-
 If we were to run several repetitions, this would be how:
 
 ```{r runExperiment}
@@ -369,31 +366,31 @@ Plot(LandRBiomass_simInit$rawBiomassMap,
 ## species % cover
 clearPlot(force = TRUE)
 Plot(simOutSpeciesLayers$speciesLayers,
-     title = names(simOutSpeciesLayers$speciesLayers))
+     title = paste(names(simOutSpeciesLayers$speciesLayers), collapse = ", "))
 ```
 
 ```{r plots2, fig.show = 'asis', eval = !isInteractive, echo = FALSE}
 plot(plotStudyAreas, main = " ")
 
 ## input stand biomass and age, ecological zonation (ecodistricts) and land-cover (LCC 2005)
 plotEcodist <- ggplot() +
-  layer_spatial(LandRBiomass_simInit$ecoregionLayer, aes(fill = as.factor(ECODISTRIC))) + 
+  layer_spatial(LandRBiomass_simInit$ecoregionLayer, aes(fill = as.factor(ECODISTRIC))) +
   labs(fill = "") +
   theme_void()
 
-plot(stack(LandRBiomass_simInit$rawBiomassMap,
-           LandRBiomass_simInit$standAgeMap, 
-           LandRBiomass_simInit$rstLCC),
-     main = c("kNN stand biomass - kNN stand age - land-cover"))
+plot(stack(file.path("GitHubActionsSims", simPathName, runName, "rawBiomassMap_966512e152b53d9b.tif"),
+           LandRBiomass_simInit$standAgeMap,
+           file.path("GitHubActionsSims", simPathName, runName, "rstLCC_966512e152b53d9b.tif")),
+     main = "")
+
+text(1.2, labels =  "kNN stand biomass - kNN stand age - land-cover", xpd = NA, cex = 1, adj = 1.2)
 
 plot(plotEcodist, main = "ecolocations")
 ## species % cover
-plot(simOutSpeciesLayers$speciesLayers,
-     main = paste(names(simOutSpeciesLayers$speciesLayers), collapse = ", "))
+plot(simOutSpeciesLayers$speciesLayers)
 ```
 
 
-
 Similarly, we can have a look at the species traits values used in the simulation directly from the `simList` object (although we also chose to save them).
 
 ```{r speciesTraits, eval=FALSE}
@@ -413,6 +410,8 @@ knitr::kable(LandRBiomass_simInit$species, caption = "Invariant species traits")
 
 Here we run the validation on the outputs of just one repetition.
 
+## Validation setup
+
 We begin by preparing all the inputs necessary for the `Biomass_validationKNN` module.
 
 ```{r validationPrep}
@@ -479,6 +478,8 @@ validationOutputs <- rbind(validationOutputs, data.frame(objectName = "speciesLa
                                                          eventPriority = 1))
 ```
 
+## Validation runs
+
 We can now run the validation:
 
 ```{r validationRun}