Merge branch 'develop' of https://github.com/rte-antares-rpackage/ant…

…aresRead into ant1432/feature
rte-antares-rpackage · Jul 10, 2024 · 48d0a37 · 48d0a37
2 parents 82438dd + 96cedad
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Package: antaresRead
 Type: Package
 Title: Import, Manipulate and Explore the Results of an 'Antares' Simulation
-Version: 2.7.0
+Version: 2.7.1
 Authors@R: c(
     person("Tatiana", "Vargas", email = "[email protected]", role = c("aut", "cre")),
     person("Jalal-Edine", "ZAWAM", role = "aut"),
@@ -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,

diff --git a/NAMESPACE b/NAMESPACE
@@ -48,6 +48,7 @@ export(ponderateMcAggregation)
 export(readAntares)
 export(readAntaresAreas)
 export(readAntaresClusters)
+export(readAntaresSTClusters)
 export(readBindingConstraints)
 export(readClusterDesc)
 export(readClusterResDesc)
@@ -79,6 +80,7 @@ import(doParallel)
 import(jsonlite)
 import(parallel)
 import(plyr)
+importFrom(assertthat,assert_that)
 importFrom(doParallel,registerDoParallel)
 importFrom(grDevices,col2rgb)
 importFrom(grDevices,rgb)

diff --git a/NEWS.md b/NEWS.md
@@ -1,5 +1,29 @@
 > Copyright © 2016 RTE Réseau de transport d’électricité
 
+# antaresRead 2.7.1 (development)
+
+NEW FEATURES:
+
+* `readInputThermal()` :
+    - new parameter **areas** to get desired clusters from selected areas.
+    - new parameter **thermalAvailabilities** to import time series.  
+* `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
+* New function `readAntaresSTClusters()`
+
+
+BREAKING CHANGES :
+
+* `readInputThermal()` / `readInputRES()` default value when no time series in the selected clusters.
+
+BUGFIXES :  
+
+* `readInputThermal()` return data from file data.txt with `thermalData` parameter
+* `setSimulationPath()` has also the parameter **areasWithSTClusters** in 'output' mode
+
+
 # antaresRead 2.7.0
 
 ### Breaking changes (Antares v8.7.0) : 
@@ -24,7 +48,7 @@ Dependencies :
 
 
 
-# antaresRead 2.6.2 (development)
+# antaresRead 2.6.2 
 
 BUGFIXES :
 * `readIniFile()` : avoid `utils::type.convert` on specific cases (ex : 789e or 123i) 
@@ -46,6 +70,8 @@ BUGFIXES :
 BREAKING CHANGES :  
 
 * `api_get()` has a new parameter to control JSON file parsing
+* `readInputThermal()` default value when no time series in the selected clusters.
+* `readInputRES()` default value when no time series in the selected clusters
 * `readClusterDesc()`/ `readClusterRESDesc()` / `readClusterSTDesc()` 
 return empty dataTable and warning if no cluster in Antares study.
 
@@ -61,7 +87,7 @@ BREAKING CHANGES (Antares v8.6) :
 * `readInputTS()` is now compatible to read time series with :  
   - "short-term storage"  
   - "mingen" (pmin hydro value)
-* `setSimulationPath()` has new parameter `areasWithSTClusters` (name of area with "st-storage" cluster)
+* `setSimulationPath()` has new parameter **areasWithSTClusters** (name of area with "st-storage" cluster)
 
 
 BUGFIXES : 

diff --git a/R/importInput.R b/R/importInput.R
@@ -369,8 +369,13 @@
 
     data$area <- area
     data$cluster <- cl
-    data <- data[opts$timeIdMin:opts$timeIdMax]
-    data$timeId <- opts$timeIdMin:opts$timeIdMax
+
+    # index blocks
+    a <- opts$parameters$general$simulation.start
+    b <- opts$parameters$general$simulation.end
+
+    data <- data[a:b]
+    data$timeId <- a:b
 
     changeTimeStep(data, timeStep, "daily", fun = "mean")
   })

diff --git a/R/importOutput.R b/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) {
@@ -490,6 +470,47 @@
 }
 
 
+#' .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
@@ -502,38 +523,11 @@
 .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,
@@ -542,6 +536,29 @@
 }
 
 
+#' .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.