Read ST clusters with readAntares()

DESCRIPTION

@@ -15,6 +15,7 @@ Authors@R: c(
     person("Clement", "Berthet", role = "ctb"),
     person("Kamel", "Kemiha", role = "ctb"),
     person("Abdallah", "Mahoudi", role = "ctb"),
+    person("Nicolas", "Boitard", role = "ctb"),
     person("RTE", role = "cph")
     )
 Description: Import, manipulate and explore results generated by 'Antares', a 
@@ -40,7 +41,8 @@ Imports:
     utils,
     memuse,
     purrr,
-    lifecycle
+    lifecycle,
+    assertthat
 Suggests:
     rhdf5 (>= 2.24.0),
     testthat,

NAMESPACE

@@ -79,6 +79,7 @@ import(doParallel)
 import(jsonlite)
 import(parallel)
 import(plyr)
+importFrom(assertthat,assert_that)
 importFrom(doParallel,registerDoParallel)
 importFrom(grDevices,col2rgb)
 importFrom(grDevices,rgb)

NEWS.md

@@ -10,6 +10,7 @@ NEW FEATURES:
 * `readInputRES()` new parameter **areas** to get desired clusters from selected areas.
 * `setSimulationPath()` return a new parameter `binding` (for studies >= v8.7.0). 
 It contains a table with group dimensions of time series for binding constraints.
+* `readAntares()` new parameter **clustersST** to read (output simulation) short-term clusters
 
 BREAKING CHANGES :
 
@@ -18,6 +19,7 @@ BREAKING CHANGES :
 BUGFIXES :  
 
 * `readInputThermal()` return data from file data.txt with `thermalData` parameter
+* `setSimulationPath()` has also the parameter **areasWithSTClusters** in 'output' mode
 
 
 # antaresRead 2.7.0

R/importOutput.R

@@ -47,6 +47,7 @@
 #' - "areas", "values"  => areas
 #' - "areas", "details" => clusters
 #' - "areas", "details-res" => renewables clusters
+#' - "areas", "details-STstorage" => short-term clusters
 #' - "links", "values"  => links
 #'
 #' @return
@@ -281,30 +282,37 @@
 
 #' .get_value_columns_details_file
 #'
-#' Private function used to get the column names for the details-timeStep.txt or details-res-timeStep.txt.
-#' Used in .importOutputForClusters() and .importOutputForResClusters()
+#' Private function used to get the column names for the details-timeStep.txt, details-res-timeStep.txt, or details-STstorage-timeStep.txt.
+#' Used in .importOutputForClusters(), .importOutputForResClusters(), and .importOutputForSTClusters()
 #' From the opts, we detect which outputs the user decides to take 
 #'
 #' @return
 #' a vector
+#' 
+#' @importFrom assertthat assert_that
 #'
 #' @noRd
 #'
 .get_value_columns_details_file <- function(opts, type) {
 
-  if(type == "details") {
-    # Order is important. There is a correspondance between elements.
-    all_thematic_variables <- c("DTG by plant", "NP Cost by plant", "NODU by plant")
-    colNames <- c("production", "NP Cost", "NODU")
-    if (opts$antaresVersion >= 830){
-      all_thematic_variables <- c(all_thematic_variables, "Profit by plant")
-      colNames <- c(colNames, "profit")
-    }
-  } else if(type == "details-res") {
-    # Order is important. There is a correspondance between elements.
-    all_thematic_variables <- c("RES generation by plant")
-    colNames <- c("production")
-  }
+  assert_that(type %in% c("details","details-res","details-STstorage"))
+
+  simulation_variables_names_by_support <- read.table(system.file(
+    "format_output","simulation_variables_names_by_support.csv",package="antaresRead"
+  ),sep=";",fileEncoding="UTF-8",header = TRUE)
+
+  filtered_variables_names <- subset(simulation_variables_names_by_support,DETAILS_FILES_TYPE==type)
+  if (type=="details" && opts$antaresVersion < 830)
+    filtered_variables_names <- subset(filtered_variables_names,ANTARES_DISPLAYED_NAME!="Profit by plant")
+
+  # Order is important. There is a correspondance between elements
+  ordered_filtered_variables_names <- filtered_variables_names[
+    order(filtered_variables_names$ORDINAL_POSITION_BY_TOPIC),
+  ]
+
+  all_thematic_variables <- ordered_filtered_variables_names$ANTARES_DISPLAYED_NAME
+  colNames <- ordered_filtered_variables_names$RPACKAGE_DISPLAYED_NAME
+
   # With thematic-trimming enabled
   if (opts$parameters$general$`thematic-trimming`) {
     if ("variables selection" %in% names(opts$parameters)) {
@@ -346,36 +354,8 @@
 .importOutputForClusters <- function(areas, timeStep, select = NULL, mcYears = NULL, 
                                      showProgress, opts, mustRun = FALSE, parallel) {
 
-  # In output files, there is one file per area with the follwing form:
-  # cluster1-var1 | cluster2-var1 | cluster1-var2 | cluster2-var2
-  # the following function reshapes the result to have variable cluster in column.
-  # To improve greatly the performance we use our knowledge of the position of 
-  # the columns instead of using more general functions like dcast.
-  reshapeFun <- function(x) {
-
-    # Get cluster names
-    n <- names(x)
-    idx <- ! n %in% pkgEnv$idVars
-    clusterNames <- tolower(unique(n[idx]))
-
-    # Id vars names
-    idVarsId <- which(!idx)
-    idVarsNames <- n[idVarsId]
-
-    # Column names of the output table
-    colNames <- .get_value_columns_details_file(opts, "details")    
-
-    # Loop over clusters
-    nclusters <- length(clusterNames)
-
-    res <- llply(1:nclusters, function(i) {
-      dt <- x[, c(nclusters * 0:(length(colNames) - 1) + i, idVarsId), with = FALSE]
-      setnames(dt, c(colNames, idVarsNames))
-      dt[, cluster := as.factor(clusterNames[i])]
-      dt
-    })
-
-    rbindlist(res)
+  reshapeFun <- function(x){
+    .reshape_details_file(x,file_type="details",opts=opts)
   }
 
   if (!mustRun) {
@@ -488,6 +468,47 @@
 }
 
 
+#' .reshape_details_file
+#' 
+#' In output files, there is one file per area with the follwing form:
+#' cluster1-var1 | cluster2-var1 | cluster1-var2 | cluster2-var2
+#' the following function reshapes the result to have variable cluster in column.
+#' To improve greatly the performance we use our knowledge of the position of 
+#' the columns instead of using more general functions like dcast.
+#' 
+#' @return 
+#' a data.table
+#' 
+#' @noRd
+#' 
+.reshape_details_file <- function(x,file_type,opts) {
+
+  # Get cluster names
+  n <- names(x)
+  idx <- ! n %in% pkgEnv$idVars
+  clusterNames <- tolower(unique(n[idx]))
+
+  # Id vars names
+  idVarsId <- which(!idx)
+  idVarsNames <- n[idVarsId]
+
+  # Column names of the output table
+  colNames <- .get_value_columns_details_file(opts=opts,type=file_type)  
+
+  # Loop over clusters
+  nclusters <- length(clusterNames)
+
+  res <- llply(1:nclusters, function(i) {
+    dt <- x[, c(nclusters * 0:(length(colNames) - 1) + i, idVarsId), with = FALSE]
+    setnames(dt, c(colNames, idVarsNames))
+    dt[, cluster := as.factor(clusterNames[i])]
+    dt
+  })
+
+  rbindlist(res)
+}
+
+
 #' .importOutputForResClusters
 #'
 #' Private function used to import the output for the renewable clusters of one area
@@ -500,38 +521,11 @@
 .importOutputForResClusters <- function(areas, timeStep, select = NULL, mcYears = NULL, 
                                         showProgress, opts, parallel) {
 
-  # In output files, there is one file per area with the follwing form:
-  # cluster1-var1 | cluster2-var1 | cluster1-var2 | cluster2-var2
-  # the following function reshapes the result to have variable cluster in column.
-  # To improve greatly the performance we use our knowledge of the position of 
-  # the columns instead of using more general functions like dcast.
+
   reshapeFun <- function(x) {
-
-    # Get cluster names
-    n <- names(x)
-    idx <- ! n %in% pkgEnv$idVars
-    clusterNames <- tolower(unique(n[idx]))
-
-    # Id vars names
-    idVarsId <- which(!idx)
-    idVarsNames <- n[idVarsId]
-
-    # Column names of the output table
-    colNames <- .get_value_columns_details_file(opts, "details-res")  
-
-    # Loop over clusters
-    nclusters <- length(clusterNames)
-
-    res <- llply(1:nclusters, function(i) {
-      dt <- x[, c(nclusters * 0:(length(colNames) - 1) + i, idVarsId), with = FALSE]
-      setnames(dt, c(colNames, idVarsNames))
-      dt[, cluster := as.factor(clusterNames[i])]
-      dt
-    })
-
-    rbindlist(res)
+    .reshape_details_file(x,file_type="details-res",opts=opts)
   }
-
+    
   suppressWarnings(
     .importOutput("areas", "details-res", "area", areas, timeStep, NULL, 
                   mcYears, showProgress, opts, reshapeFun, sameNames = FALSE,
@@ -540,6 +534,29 @@
 }
 
 
+#' .importOutputForSTClusters
+#'
+#' Private function used to import the output for the short-term clusters of one area
+#'
+#' @return
+#' a data.table
+#'
+#' @noRd
+#'
+.importOutputForSTClusters <- function(areas, timeStep, select = NULL, mcYears = NULL, 
+                                        showProgress, opts, parallel) {
+
+  reshapeFun <- function(x) {
+    .reshape_details_file(x,file_type="details-STstorage",opts=opts)
+  }
+
+  suppressWarnings(
+    .importOutput("areas", "details-STstorage", "area", areas, timeStep, NULL, 
+                  mcYears, showProgress, opts, reshapeFun, sameNames = FALSE,
+                  objectDisplayName = "clustersST", parallel = parallel)
+  )
+}
+
 #' .importOutputForBindingConstraints
 #'
 #' Private function used to import the output for binding constraints.

R/readAntares.R

@@ -14,6 +14,8 @@
 #' Read the data of an Antares simulation
 #'
 #' @description
+#' `r antaresRead:::badge_api_ok()`
+#' 
 #' \code{readAntares} is a swiss-army-knife function used to read almost every
 #' possible time series of an antares Project at any desired time resolution
 #' (hourly, daily, weekly, monthly or annual).
@@ -85,6 +87,11 @@
 #'   import results at renewable cluster level. If \code{NULL} no cluster is imported. The
 #'   special value \code{"all"} tells the function to import renewable clusters from all
 #'   areas.
+#' @param clustersST
+#'   Vector containing the name of the areas for which you want to
+#'   import results at short-term cluster level. If \code{NULL} no cluster is imported. The
+#'   special value \code{"all"} tells the function to import short-term clusters from all
+#'   areas.
 #' @param bindingConstraints
 #'   Should binding constraints be imported (v8.4+)?
 #' @param districts
@@ -210,8 +217,8 @@
 #' @export
 #'
 readAntares <- function(areas = NULL, links = NULL, clusters = NULL,
-                        districts = NULL, clustersRes = NULL, bindingConstraints = FALSE,
-                        misc = FALSE, thermalAvailabilities = FALSE,
+                        districts = NULL, clustersRes = NULL, clustersST = NULL,
+                        bindingConstraints = FALSE, misc = FALSE, thermalAvailabilities = FALSE,
                         hydroStorage = FALSE, hydroStorageMaxPower = FALSE,
                         reserve = FALSE, linkCapacity = FALSE, mustRun = FALSE,
                         thermalModulation = FALSE,
@@ -221,7 +228,7 @@ readAntares <- function(areas = NULL, links = NULL, clusters = NULL,
                         mcWeights = NULL,
                         opts = simOptions(),
                         parallel = FALSE, simplify = TRUE, showProgress = TRUE) {
-  
+
   if((!is.null(opts$parameters$`other preferences`$`renewable-generation-modelling`) &&
       !opts$parameters$`other preferences`$`renewable-generation-modelling` %in% "clusters") || 
      is.null(opts$parameters$`other preferences`$`renewable-generation-modelling`)){
@@ -309,6 +316,7 @@ readAntares <- function(areas = NULL, links = NULL, clusters = NULL,
                                links = links,
                                clusters = clusters,
                                clustersRes = clustersRes,
+                               clustersST = clustersST,
                                districts = districts,
                                mcYears = mcYears)
 
@@ -317,6 +325,7 @@ readAntares <- function(areas = NULL, links = NULL, clusters = NULL,
   links <- reqInfos$links
   clusters <- reqInfos$clusters
   clustersRes <- reqInfos$clustersRes
+  clustersST <- reqInfos$clustersST
   districts <- reqInfos$districts
   mcYears <- reqInfos$mcYears
   synthesis <- reqInfos$synthesis
@@ -328,7 +337,7 @@ readAntares <- function(areas = NULL, links = NULL, clusters = NULL,
     return(aggregateResult(opts = opts,
                            verbose = showProgress,
                            filtering = TRUE,
-                           selected = list(areas = areas, links = links, clusters = clusters, clustersRes = clustersRes),
+                           selected = list(areas = areas, links = links, clusters = clusters, clustersRes = clustersRes, clustersST = clustersST),
                            timestep = timeStep,
                            writeOutput = FALSE,
                            mcWeights = mcWeights, mcYears = mcYears))
@@ -342,7 +351,7 @@ readAntares <- function(areas = NULL, links = NULL, clusters = NULL,
   }
 
   # If all arguments are NULL, import all areas
-  if (is.null(areas) & is.null(links) & is.null(clusters) & is.null(clustersRes) & is.null(districts)) {
+  if (is.null(areas) & is.null(links) & is.null(clusters) & is.null(clustersRes) & is.null(clustersST) & is.null(districts)) {
     areas <- "all"
   }
 
@@ -353,6 +362,7 @@ readAntares <- function(areas = NULL, links = NULL, clusters = NULL,
   links <- .checkArg(links, opts$linkList, "Links %s do not exist in the simulation.")
   clusters <- .checkArg(clusters, opts$areasWithClusters, "Areas %s do not exist in the simulation or do not have any thermal cluster.")
   clustersRes <- .checkArg(clustersRes, opts$areasWithResClusters, "Areas %s do not exist in the simulation or do not have any renewable cluster.")
+  clustersST <- .checkArg(clustersST, opts$areasWithSTClusters, "Areas %s do not exist in the simulation or do not have any short-term cluster.")
   districts <- .checkArg(districts, opts$districtList, "Districts %s do not exist in the simulation.")
   mcYears <- .checkArg(mcYears, opts$mcYears, "Monte-Carlo years %s have not been exported.", allowDup = TRUE)
 
@@ -476,6 +486,12 @@ readAntares <- function(areas = NULL, links = NULL, clusters = NULL,
                                                  opts, parallel = parallel)
   if(!is.null(res$clustersRes) && nrow(res$clustersRes) == 0) res$clustersRes <- NULL
 
+  # Import short-term clusters
+  res$clustersST <- .importOutputForSTClusters(clustersST, timeStep, NULL, 
+                                                 mcYears, showProgress, 
+                                                 opts, parallel = parallel)
+  if(!is.null(res$clustersST) && nrow(res$clustersST) == 0) res$clustersST <- NULL
+
   # Import thermal clusters and eventually must run
   if (!mustRun) {
     res$clusters <- .importOutputForClusters(clusters, timeStep, NULL, mcYears,
@@ -820,6 +836,7 @@ readAntaresAreas <- function(areas, links = TRUE, clusters = TRUE, clustersRes =
                              links,
                              clusters,
                              clustersRes,
+                             clustersST,
                              districts,
                              mcYears){
 
@@ -873,6 +890,10 @@ readAntaresAreas <- function(areas, links = TRUE, clusters = TRUE, clustersRes =
     if (!is.null(areas)) clustersRes <- areas
     else clustersRes <- "all"
   }
+  if ("clustersST" %in% unlist(select) & is.null(clustersST)) {
+    if (!is.null(areas)) clustersST <- areas
+    else clustersST <- "all"
+  }
   if ("mcYears" %in% unlist(select) & is.null(mcYears)) mcYears <- "all"
 
   # If all arguments are NULL, import all areas
@@ -888,6 +909,7 @@ readAntaresAreas <- function(areas, links = TRUE, clusters = TRUE, clustersRes =
               links = links,
               clusters = clusters,
               clustersRes = clustersRes,
+              clustersST = clustersST,
               districts = districts,
               mcYears = mcYears,
               synthesis = synthesis,

R/setSimulationPath.R

@@ -482,6 +482,20 @@ setSimulationPath <- function(path, simulation = NULL) {
   areasWithResClusters <- sort(union(areaList_mc_all[hasResClusters_mc_all], 
                                      areaList_mc_ind[hasResClusters_mc_ind]))
 
+
+  # Areas containing short-term clusters
+  hasSTClusters_mc_all <- laply(file.path(dataPath_mc_all, "areas", areaList_mc_all), function(x) {
+    f <- list.files(x)
+    any(grepl("details-STstorage-", f))
+  })
+  hasSTClusters_mc_ind <- laply(file.path(dataPath_mc_ind, "areas", areaList_mc_ind), function(x) {
+    f <- list.files(x)
+    any(grepl("details-STstorage-", f))
+  })
+
+  areasWithSTClusters <- sort(union(areaList_mc_all[hasSTClusters_mc_all], 
+                                     areaList_mc_ind[hasSTClusters_mc_ind]))
+
   # Available variables
   variables <- list()
 
@@ -523,6 +537,7 @@ setSimulationPath <- function(path, simulation = NULL) {
     linksDef = linksDef,
     areasWithClusters = areasWithClusters,
     areasWithResClusters = areasWithResClusters,
+    areasWithSTClusters = areasWithSTClusters,
     variables = variables,
     parameters = params
   )

R/utils_api.R

@@ -162,6 +162,15 @@ read_secure_json <- function(url, token = NULL, timeout = 60, config = list()) {
   )
 
   areasWithResClusters <- names(hasResClusters)[hasResClusters]
+
+  hasSTClusters <- unlist(
+    lapply(
+      read_secure_json(file.path(dataPath, "areas&depth=2"), ...),
+      function(x) any(grepl("details-STstorage-", names(x)))
+    )
+  )
+
+  areasWithSTClusters <- names(hasSTClusters)[hasSTClusters]
   # Available variables
   variables <- list()
 
@@ -212,6 +221,7 @@ read_secure_json <- function(url, token = NULL, timeout = 60, config = list()) {
       linksDef = linksDef,
       areasWithClusters = intersect(areasWithClusters, areaList),
       areasWithResClusters = intersect(areasWithResClusters, areaList),
+      areasWithSTClusters = intersect(areasWithSTClusters, areaList),
       variables = variables,
       parameters = params
     )

R/zzz.R

@@ -104,7 +104,8 @@ utils::globalVariables(
     "NODU", "min.stable.power", "thermalPmin", "name", "value",
     "Folder", "Mode", "Stats", "Name", "progNam", "mrgprice", "isLOLD_cum",
     "...To", "upstream", "downstream", "LOLD", "LOLD_data", "LOLP", "warn_for_status",
-    "MRG. PRICE", "H. LEV", "V2", "V1", "size")
+    "MRG. PRICE", "H. LEV", "V2", "V1", "size", "ORDINAL_POSITION_BY_TOPIC", 
+    "DETAILS_FILES_TYPE","ANTARES_DISPLAYED_NAME")
 )
 
 #-----------------------------  HDF5 ------------------------------------#

inst/format_output/simulation_variables_names_by_support.csv

@@ -0,0 +1,9 @@
+"TOPIC";"DETAILS_FILES_TYPE";"ANTARES_DISPLAYED_NAME";"ORDINAL_POSITION_BY_TOPIC";"TITLE";"ALIAS";"MIN_VERSION";"OUTPUT_DISPLAYED_NAME";"RPACKAGE_DISPLAYED_NAME"
+"Generation / Thermal";"details";"DTG by plant";1;"Dispatchable Thermal Generation by Thermal Cluster (MWh)";"dtgByPlant";;"MWh";"production"
+"Generation / Thermal";"details";"NODU by plant";3;"Number of Dispatched Units by Thermal Cluster";"noduByPlant";;"NODU";"NODU"
+"Generation / Thermal";"details";"NP Cost by plant";2;"Non-Proportional Costs by Thermal Cluster (€)";"npCostByPlant";;"NP Cost - Euro";"NP Cost"
+"Generation / Thermal";"details";"Profit by plant";4;"Net Profit by Thermal Cluster (€)";"profitByPlant";830;"Profit - Euro";"profit"
+"Generation / Renewables";"details-res";"RES generation by plant";1;"Renewable Energy Generation by Power Plant Cluster (MWh)";"resGenerationByPlant";810;"MWh";"production"
+"Generation / Short-Term Storages";"details-STstorage";"STS inj by plant";1;"Short-Term Storage Injection by Power Plant (MWh)";"stsInjByPlant";860;"P-injection - MW";"P.injection"
+"Generation / Short-Term Storages";"details-STstorage";"STS lvl by plant";2;"Short-Term Storage Level by Power Plant (MWh)";"stsLvlByPlant";860;"Levels - MWh";"levels"
+"Generation / Short-Term Storages";"details-STstorage";"STS withdrawal by plant";3;"Short-Term Storage Withdrawal by Power Plant (MWh)";"stsWithdrawalByPlant";860;"P-withdrawal - MW";"P.withdrawal"

revdep/README.md

@@ -10,18 +10,19 @@
 |collate  |French_France.utf8                  |
 |ctype    |French_France.utf8                  |
 |tz       |Europe/Paris                        |
-|date     |2024-05-27                          |
+|date     |2024-06-13                          |
 |rstudio  |2023.12.0+369 Ocean Storm (desktop) |
 |pandoc   |NA                                  |
 
 # Dependencies
 
 |package     |old   |new   |Δ  |
 |:-----------|:-----|:-----|:--|
-|antaresRead |2.6.1 |2.7.0 |*  |
+|antaresRead |2.7.0 |2.7.1 |*  |
 |cachem      |NA    |1.0.8 |*  |
 |fastmap     |NA    |1.1.1 |*  |
 |openssl     |NA    |2.1.2 |*  |
+|rlang       |NA    |1.1.3 |*  |
 |stringi     |NA    |1.8.3 |*  |
 
 # Revdeps

tests/testthat/test-importOutputForClusters.R

@@ -0,0 +1,62 @@
+#Copyright © 2016 RTE Réseau de transport d’électricité
+
+context("Functions .importOutput")
+
+path_study_test <- grep(pattern = "87", x = studyPathSV8, value = TRUE)
+
+opts <- setSimulationPath(path_study_test,simulation="20240105-0934eco")
+
+test_that(".importOutputForClusters is ok", {
+
+    OutputForClusters <- .importOutputForClusters(
+        areas="fr",
+        timeStep="annual",
+        showProgress=FALSE, 
+        parallel=FALSE,
+        opts=opts
+    )
+
+    required_order_simulation_variables <- c("production","NP Cost","NODU","profit")
+
+    order_simulation_variables <- colnames(OutputForClusters)[colnames(OutputForClusters) %in% required_order_simulation_variables] 
+
+    expect_equal(order_simulation_variables,required_order_simulation_variables)
+    expect_equal(nrow(OutputForClusters),1)
+})
+
+
+test_that(".importOutputForResClusters is ok", {
+
+    OutputForResClusters <- .importOutputForResClusters(
+        areas="fr",
+        timeStep="annual",
+        showProgress=FALSE, 
+        parallel=FALSE,
+        opts=opts
+    )
+
+    required_order_simulation_variables <- c("production")
+
+    order_simulation_variables <-  colnames(OutputForResClusters)[colnames(OutputForResClusters) %in% required_order_simulation_variables] 
+
+    expect_equal(order_simulation_variables,required_order_simulation_variables)
+    expect_equal(nrow(OutputForResClusters),1)
+})
+
+test_that(".importOutputForSTClusters is ok", {
+
+    OutputForSTClusters <- .importOutputForSTClusters(
+        areas="fr",
+        timeStep="annual",
+        showProgress=FALSE, 
+        parallel=FALSE,
+        opts=opts
+    )
+
+    required_order_simulation_variables <- c("P.injection","levels","P.withdrawal")
+
+    order_simulation_variables <- colnames(OutputForSTClusters)[colnames(OutputForSTClusters) %in% required_order_simulation_variables] 
+
+    expect_equal(order_simulation_variables,required_order_simulation_variables)
+    expect_equal(nrow(OutputForSTClusters),1)
+})

tests/testthat/test-readAntares_STclusters.R

@@ -0,0 +1,16 @@
+#Copyright © 2016 RTE Réseau de transport d’électricité
+
+context("Function readAntares (ST clusters)")
+
+path_study_test <- grep(pattern = "87", x = studyPathSV8, value = TRUE)
+
+opts <- setSimulationPath(path_study_test,simulation="20240105-0934eco")
+
+test_that("ST clusters importation is ok", {
+
+  clustersST <- readAntares(clustersST="all",timeStep="annual",opts = opts)$clustersST
+  expect_true(all(opts$areasWithSTClusters %in% clustersST$area))
+
+  clustersST_fr <- readAntares(clustersST="fr",timeStep="annual",opts = opts)$clustersST
+  expect_true("fr"==unique(clustersST_fr$area))
+})

tests/testthat/test-setSimulationPath.R

@@ -178,13 +178,28 @@ test_that("Folder 'maps' is not interpreted as a study (#49)", {
 
 }
 
+test_that("No meta info areas with a ST cluster < 860", {
+  opts <- setSimulationPath(studyPath, "input")
+  expect_true(length(opts$areasWithSTClusters)==0)
+})
+
 test_that("No meta info binding study < 870", {
   opts <- setSimulationPath(studyPath, "input")
   expect_null(opts$binding)
 })
 
 })
 
+# v860----
+test_that("New meta data for areas with a ST cluster", {
+  # read latest version study
+  path_study_test <- grep(pattern = "87", x = studyPathSV8, value = TRUE)
+  opts_study_test <- setSimulationPath(path_study_test, simulation = "20240105-0934eco")
+
+  expect_false(is.null(opts_study_test$areasWithSTClusters))
+})
+
+
 # v870----
 test_that("New meta data for group dimension of binding constraints", {
   # read latest version study