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Add new function readAntaresSTClusters() #254

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Jul 4, 2024
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1 change: 1 addition & 0 deletions NAMESPACE
Original file line number Diff line number Diff line change
Expand Up @@ -48,6 +48,7 @@ export(ponderateMcAggregation)
export(readAntares)
export(readAntaresAreas)
export(readAntaresClusters)
export(readAntaresSTClusters)
export(readBindingConstraints)
export(readClusterDesc)
export(readClusterResDesc)
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2 changes: 2 additions & 0 deletions NEWS.md
Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,8 @@ NEW FEATURES:
* `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 :

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2 changes: 1 addition & 1 deletion R/readAntares.R
Original file line number Diff line number Diff line change
Expand Up @@ -897,7 +897,7 @@ readAntaresAreas <- function(areas, links = TRUE, clusters = TRUE, clustersRes =
if ("mcYears" %in% unlist(select) & is.null(mcYears)) mcYears <- "all"

# If all arguments are NULL, import all areas
if (is.null(areas) & is.null(links) & is.null(clusters) & is.null(districts)) {
if (is.null(areas) & is.null(links) & is.null(clusters) & is.null(districts) & is.null(clustersST)) {
areas <- "all"
}

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54 changes: 53 additions & 1 deletion R/readAntaresClusters.R
Original file line number Diff line number Diff line change
Expand Up @@ -36,4 +36,56 @@ readAntaresClusters <- function(clusters, selected = c("production", "NP Cost",

subset(res, cluster %in% clusters, select = c(setdiff(colnames(res),c("production", "NP Cost", "NODU", "profit")),
intersect(colnames(res),selected))) #support for up to v8.4
}
}


#' Read output for a list of short-term storage clusters
#'
#' @param clustersST vector of short-term storage clusters to be imported
#' @param selected vector of thematic trimming
#' @inheritParams readAntares
#'
#' @return data.table of results for short-term storage clusters
#'
#' @export
readAntaresSTClusters <- function(clustersST, selected = c("P.injection", "levels", "P.withdrawal"),
timeStep = c("hourly", "daily", "weekly", "monthly", "annual"),
opts = simOptions(), parallel = FALSE, showProgress = TRUE) {

if (missing(clustersST)) {
stop("The function 'readAntaresSTClusters' expects a vector of short-term storage clusters names as argument.")
}
if ("Input" %in% opts$mode) {
stop("Cannot use 'readAntaresSTClusters' in 'Input' mode.")
}
if (opts$antaresVersion < 860) {
stop("Cannot use 'readAntaresSTClusters' for a study version < 860.")
}

##Add check control for all
allSTClusters <- readClusterSTDesc(opts = opts)[, c("area","cluster")]
allSTClusters$lower_cluster <- tolower(allSTClusters$cluster)
ind_cluster <- which(allSTClusters$lower_cluster %in% .checkArg(tolower(clustersST),
tolower(unique(allSTClusters$cluster)),
"short-term storage clusters %s do not exist in the simulation."))
clustersST <- allSTClusters$cluster[ind_cluster]

ind_cluster <- which(allSTClusters$lower_cluster %in% .checkArg(tolower(clustersST),
tolower(unique(allSTClusters[area %in% opts$areasWithSTClusters]$cluster)),
"short-term storage clusters %s have no output."))
clustersST <- unique(allSTClusters$cluster[ind_cluster])

output_st_clusters <- data.table()
if (length(clustersST) > 0) {
areas <- unique(allSTClusters[cluster %in% clustersST]$area)

res <- readAntares(clustersST = areas, timeStep = timeStep, opts = opts,
parallel = parallel, showProgress = showProgress)

output_st_clusters <- subset(res, cluster %in% clustersST, select = c(setdiff(colnames(res),c("P.injection", "levels", "P.withdrawal")),
intersect(colnames(res),selected))
)
}

return(output_st_clusters)
}
37 changes: 37 additions & 0 deletions man/readAntaresSTClusters.Rd

Some generated files are not rendered by default. Learn more about how customized files appear on GitHub.

45 changes: 41 additions & 4 deletions tests/testthat/test-readAntares_STclusters.R
Original file line number Diff line number Diff line change
Expand Up @@ -4,13 +4,50 @@ context("Function readAntares (ST clusters)")

path_study_test <- grep(pattern = "87", x = studyPathSV8, value = TRUE)

opts <- setSimulationPath(path_study_test,simulation="20240105-0934eco")
suppressWarnings(opts <- setSimulationPath(path_study_test, simulation = "20240105-0934eco"))

test_that("ST clusters importation is ok", {

clustersST <- readAntares(clustersST="all",timeStep="annual",opts = opts)$clustersST
clustersST <- readAntares(clustersST = "all", timeStep = "annual",opts = opts)
expect_true(all(opts$areasWithSTClusters %in% clustersST$area))

clustersST_fr <- readAntares(clustersST="fr",timeStep="annual",opts = opts)$clustersST
expect_true("fr"==unique(clustersST_fr$area))
clustersST_fr <- readAntares(clustersST = "fr", timeStep = "annual", opts = opts)
expect_true("fr" == unique(clustersST_fr$area))
})


test_that("ST clusters importation is OK", {
nweeks_study <- 52
output_cols <- c("P.injection", "levels", "P.withdrawal")
clusters <- readAntaresSTClusters(clusters = "fr_st_other1", selected = output_cols[1:2], timeStep = "hourly", showProgress = FALSE, opts = opts)
expect_is(clusters, "data.table")
expect_true(!is.null(clusters$cluster))
expect_equal(nrow(clusters), 24 * 7 * nweeks_study)
expect_true(all(output_cols[1:2] %in% colnames(clusters)))
expect_false(output_cols[3] %in% colnames(clusters))
})


test_that("ST clusters importation is OK for all time resolutions.", {
nweeks_study <- 52
for (timeStep in c("hourly", "daily", "weekly", "monthly", "annual")) {
expected_rows = switch(timeStep,
hourly = 24 * 7 * nweeks_study,
daily = 7 * nweeks_study,
weekly = nweeks_study,
monthly = 12,
annual = 1)

clusters <- readAntaresSTClusters(clusters = "fr_st_other1", showProgress = FALSE, timeStep = timeStep)
expect_equal(nrow(clusters), expected_rows)
}
})


test_that("ST clusters importation is KO if clusters do not belong to the study output", {
expect_warning(clusters <- readAntaresSTClusters(clusters = c("fake_one", "not_a_cluster"), timeStep = "hourly", showProgress = FALSE, opts = opts),
regexp = "do not exist in the simulation"
)
expect_is(clusters, "data.table")
expect_true(nrow(clusters) == 0)
})
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