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# ranking some students (from the article on Integrating Large Performance Differences in MR Sort by Meyer and Olteanu, 2015)
#library(MCDA)
# the performance table
test_that("LPDMRSortInferenceExact works", {
performanceTable <- rbind(c(10,10,9),c(10,9,10),c(9,10,10),c(9,9,10),c(9,10,9),c(10,9,9),
c(10,10,7),c(10,7,10),c(7,10,10),c(9,9,17),c(9,17,9),c(17,9,9),
c(7,10,17),c(10,17,7),c(17,7,10),c(7,17,10),c(17,10,7),c(10,7,17),
c(7,9,17),c(9,17,7),c(17,7,9),c(7,17,9),c(17,9,7),c(9,7,17),c(7,7,7))
rownames(performanceTable) <- c("a1","a2","a3","a4","a5","a6","a7","a8","a9","a10","a11","a12","a13","a14","a15","a16","a17","a18","a19","a20","a21","a22","a23","a24","a25")
colnames(performanceTable) <- c("c1","c2","c3")
assignments <-rbind(c("P","P","P","F","F","F","F","F","F","F","F","F","F","F","F","F","F","F","F","F","F","F","F","F","P"),
c("P","P","P","F","F","F","P","P","P","P","P","P","P","P","P","P","P","P","P","P","P","P","P","P","P"),
c("P","P","P","F","F","F","F","F","F","F","F","F","P","P","P","P","P","P","F","F","F","F","F","F","P"),
c("P","P","P","F","F","F","P","P","P","P","P","P","P","P","P","P","P","P","F","F","F","F","F","F","P"),
c("P","P","P","F","F","F","F","F","F","P","P","P","F","F","F","F","F","F","F","F","F","F","F","F","P"),
c("P","P","P","F","F","F","F","F","F","P","P","P","P","P","P","P","P","P","P","P","P","P","P","P","P"),
c("P","P","P","F","F","F","F","F","F","P","P","P","P","P","P","P","P","P","F","F","F","F","F","F","P"))
colnames(assignments) <- rownames(performanceTable)
categoriesRanks <-c(1,2)
names(categoriesRanks) <- c("P","F")
criteriaMinMax <- c("max","max","max")
names(criteriaMinMax) <- colnames(performanceTable)
majorityRules <- c("V","D","v","d","dV","Dv","dv")
for(i in 1:1)# change to 7 in order to perform all tests
{
incompatibleAssignmentsSets<-LPDMRSortIdentifyIncompatibleAssignments(performanceTable, assignments[i,], categoriesRanks, criteriaMinMax, majorityRule = majorityRules[i])
filteredAlternativesIDs <- setdiff(rownames(performanceTable),incompatibleAssignmentsSets[[1]][1])
x<-LPDMRSortInferenceExact(performanceTable, assignments[i,], categoriesRanks,
criteriaMinMax, majorityRule = majorityRules[i], readableWeights = TRUE, readableProfiles = TRUE, minmaxLPD = TRUE,
alternativesIDs = filteredAlternativesIDs)
ElectreAssignments<-LPDMRSort(performanceTable, x$profilesPerformances, categoriesRanks,
x$weights, criteriaMinMax, x$lambda, criteriaVetos=x$vetoPerformances, criteriaDictators=x$dictatorPerformances, majorityRule = majorityRules[i],
alternativesIDs = filteredAlternativesIDs)
expect_equal(ElectreAssignments, assignments[i,filteredAlternativesIDs])
expect_equal(assignments[i,filteredAlternativesIDs], ElectreAssignments)
}
})
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