T28966_test.R
aekavur (Ali Emre Kavur)
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	aekavur
	Feb 28 2022, 1:05 PM

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T28966_test.R
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	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,)

	}