tests/testthat/test-SURE.R

In MCDA: Support for the Multicriteria Decision Aiding Process

#library(MCDA)
test_that("SURE works", {
  performanceTableMin <- t(matrix(c(78,87,79,19,8,68,74,8,90,89,74.5,9,20,81,30),nrow=3,ncol=5, byrow=TRUE)) 
  performanceTable <- t(matrix(c(80,87,86,19,8,70,74,10,90,89,75,9,33,82,30),nrow=3,ncol=5, byrow=TRUE))
  performanceTableMax <- t(matrix(c(81,87,95,19,8,72,74,15,90,89,75.5,9,36,84,30),nrow=3,ncol=5, byrow=TRUE))  
  
  row.names(performanceTable) <- c("Yield","Toxicity","Cost","Separation","Odour")
  colnames(performanceTable) <- c("Route One","Route Two","Route Three")
  row.names(performanceTableMin) <- row.names(performanceTable)
  colnames(performanceTableMin) <- colnames(performanceTable)
  row.names(performanceTableMax) <- row.names(performanceTable)
  colnames(performanceTableMax) <- colnames(performanceTable)
  
  criteriaWeights <- c(0.339,0.077,0.434,0.127,0.023) 
  names(criteriaWeights) <- row.names(performanceTable)
  
  criteriaMinMax <- c("max", "max", "max", "max", "max")
  names(criteriaMinMax) <- row.names(performanceTable)
  
  overall1 <- SURE(performanceTableMin, performanceTable, performanceTableMax, 
                   criteriaWeights, criteriaMinMax, NoOfSimulations=10^4)
  expect_equal(colMeans(overall1), c(0.47, 0.25, 0.28), ignore_attr=TRUE, tolerance=0.01)
  
  overall2 <- SURE(performanceTableMin, performanceTable, performanceTableMax, 
                   criteriaWeights, criteriaMinMax, 
                   alternativesIDs = c("Route Two","Route Three"), 
                   criteriaIDs = c("Yield","Toxicity","Cost","Separation"), 
                   NoOfSimulations=10^4)
  expect_equal(colMeans(overall2), c(0.42, 0.56), ignore_attr=TRUE, tolerance=0.01)
})