tests/testthat/test-ponderate.R

In antaresRead: Import, Manipulate and Explore the Results of an 'Antares' Simulation

context("mcWeights")

skip("readAntares empty when mcYears is NULL")

setSimulationPath(studyPathSV8)

sapply(c("hourly", "daily", "weekly", "monthly", "annual"), function(tim){
  correct_mc_weights <- 1:2
  output_correct_weights_hourly <- readAntares(areas = "all", links = "all", clusters = "all", mcYears = "all", timeStep = tim, mcWeights = correct_mc_weights, showProgress = F)
  output_synthetic_hourly <- readAntares(areas = "all", links = "all", clusters = "all", mcYears = NULL, timeStep = tim, showProgress = FALSE)

  ### Areas ###
  output_weighted_areas <- output_correct_weights_hourly$areas
  output_synthetic_areas <- output_synthetic_hourly$areas
  data.table::setcolorder(output_weighted_areas, colnames(output_synthetic_areas))

  # output_weighted_areas <- output_weighted_areas[, round(.SD, 2), .SDcols = sapply(output_weighted_areas, is.numeric)]
  # output_synthetic_areas <- output_synthetic_areas[, .SD, .SDcols = sapply(output_synthetic_areas, is.numeric)]
  test <- output_synthetic_areas[, .SD, .SDcols = !getIdCols(output_weighted_areas)] - output_weighted_areas[, .SD, .SDcols = !getIdCols(output_weighted_areas)]
  test <- round(test, 0)
  test$PSP <- test$`MISC. NDG` <- NULL
  non_null_cols <- colMeans(abs(test))
  non_null_cols <- which(non_null_cols > 1)
  test2 <- test[, .SD, .SDcols = non_null_cols]
  expect_true(ncol(test2) == 0)

  ### Links ###
  output_weighted_links <- output_correct_weights_hourly$links
  output_synthetic_links <- output_synthetic_hourly$links
  setcolorder(output_weighted_links, colnames(output_synthetic_links))

  output_weighted_links <- output_weighted_links[, round(.SD, 2), .SDcols = sapply(output_weighted_links, is.numeric)]
  output_synthetic_links <- output_synthetic_links[, .SD, .SDcols = sapply(output_synthetic_links, is.numeric)]
  test <- output_synthetic_links - output_weighted_links
  test <- round(test, 0)
  non_null_cols <- colMeans(abs(test))
  non_null_cols <- which(non_null_cols > 20)
  test2 <- test[, .SD, .SDcols = non_null_cols]
  expect_true(ncol(test2) == 0)

  ### Clusters ###
  output_weighted_clusters <- output_correct_weights_hourly$clusters
  output_synthetic_clusters <- output_synthetic_hourly$clusters
  setcolorder(output_weighted_clusters, colnames(output_synthetic_clusters))

  output_weighted_clusters <- output_weighted_clusters[, round(.SD, 2), .SDcols = sapply(output_weighted_clusters, is.numeric)]
  output_synthetic_clusters <- output_synthetic_clusters[, .SD, .SDcols = sapply(output_synthetic_clusters, is.numeric)]
  test <- output_synthetic_clusters - output_weighted_clusters
  test <- round(test, 0)
  non_null_cols <- colMeans(abs(test))
  non_null_cols <- which(non_null_cols > 1)
  test2 <- test[, .SD, .SDcols = non_null_cols]
  expect_true(ncol(test2) == 0)

})