library(devtools)
library(stringi)
library(stringr)
load_all('./challengeR') # Load challengeR from local development copy

folder = "./csv_files"
data_matrix_all =c(
  "data_matrix_3alg.csv",
  "data_matrix.csv",
  "data_matrix_single_task_19.csv",
  "data_matrix_single_task_27.csv",
  "data_matrix_single_task_30.csv"
  )

for (data_file in data_matrix_all) {
  data_matrix <- read.csv(paste(folder, data_file, sep="/"))


Title = data_file
File = str_sub(data_file, end=-5)

challenge <- as.challenge(data_matrix,
                          by = "task",
                          algorithm = "alg_name",
                          case = "case",
                          value = "value",
                          smallBetter = TRUE)


bootstrapSamples <- 10
ranking <- challenge %>% aggregateThenRank(FUN = mean, na.treat = 0, ties.method = "min")

meanRanks <- ranking %>% consensus(method = "euclidean")

if (bootstrapSamples > 0) {
  set.seed(1)
  rankingBootstrapped <- ranking %>% bootstrap(nboot = bootstrapSamples)
  ranking <- rankingBootstrapped
}


# Generate the report
ranking %>%
  report(consensus = meanRanks,
         title = Title,
         file = File,
         format = "PDF",
         latex_engine = "pdflatex",
         clean = TRUE,
         open = FALSE,)

}