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Running the tests in ‘tests/ls.sorting.treatment.R’ failed.
Complete output:
  >         library(kappalab)
  Loading required package: lpSolve
  Loading required package: quadprog
  Loading required package: kernlab
  > 	
  > 	## n : number of criteria, here 4
  > 	## k : search for a k-additive solution
  > 	## d : minimal distance between 2 classes
  > 	## t : number of prototypes        	
  > 	## n.var.alt.A : number of elements of A
  > 
  > 	## generate a random problem with "n.var.alt" alternatives and 4 criteria
  > 	## n.var.alt <- 30 ## alternatives
  > 	k <- 4
  > 	d <- 0.1
  > 	n.var.alt <- 10
  > 	n.var.alt.A <- 10
  >   	n <- 4 ## criteria
  > 
  > 	print("Number of prototypes: ")
  [1] "Number of prototypes: "
  > 	print(n.var.alt)
  [1] 10
  > 	print("Number of criteria: ")
  [1] "Number of criteria: "
  > 	print(n)
  [1] 4
  > 	print("Number of elements of A: ")
  [1] "Number of elements of A: "
  > 	print(n.var.alt.A)
  [1] 10
  >         print("Epsilon: ")
  [1] "Epsilon: "
  >         print(d)
  [1] 0.1
  >         print("k: ")
  [1] "k: "
  >         print(k)
  [1] 4
  >         
  > 	print("*** Generating the data for the prototypes")
  [1] "*** Generating the data for the prototypes"
  >   	P <- matrix(runif(n.var.alt*n,0,1),n.var.alt,n)
  >   	cl.proto<-numeric(n.var.alt)
  > 
  >   	## the corresponding global scores
  >   	glob.eval <- numeric(n.var.alt)
  >   	a <- capacity(c(0:(2^n-3),(2^n-3),(2^n-3))/(2^n-3))
  >   	for (i in 1:n.var.alt)
  +     		glob.eval[i] <- Choquet.integral(a,P[i,])
  > 
  >   	cl.proto[glob.eval <= 0.33] <- 1
  > 
  >         ## decomment here if there should be errors in the
  >         ## classification of the prototypees 
  >         # cl.proto[glob.eval > 0.33 & glob.eval<=0.44] <-2
  >   	# cl.proto[glob.eval > 0.44 & glob.eval<=0.55] <-1
  >   	# cl.proto[glob.eval > 0.55 & glob.eval<=0.66] <-2
  >   	
  > 	cl.proto[glob.eval>0.33 & glob.eval<=0.66] <-2
  >  
  > 	cl.proto[glob.eval > 0.66] <- 3
  > 
  >         ## a Shapley preorder constraint matrix
  >         ## Sh(1) > Sh(2)
  >         ## Sh(3) > Sh(4)
  >         delta.S <-0.01
  > 	Asp <- rbind(c(1,2,delta.S), c(3,4,delta.S))
  > 	# Asp <- NULL
  >         
  >         ## a Shapley interval constraint matrix
  >         ## 0.3 <= Sh(1) <= 0.9 
  >         # Asi <- rbind(c(1,0.1,0.2))
  >          Asi <- NULL
  >         
  >         ## an interaction preorder constraint matrix
  >         ## such that I(12) > I(34)
  >         delta.I <- 0.01
  >         Aip <- rbind(c(1,2,3,4,delta.I))
  >         # Aip <- NULL
  >         
  >         ## an interaction interval constraint matrix
  >         ## i.e. 0.2 <= I(12) <= 0.4 
  >         ## delta.I <- 0.01
  >         # Aii <- rbind(c(1,2,0.2,0.4))
  >          Aii <- NULL
  >         
  >         ## an inter-additive partition constraint
  >         ## criteria 1,2 and criteria 3,4 are indepedent 
  >         # Aiap <- c(1,1,2,2)
  >          Aiap <- NULL
  >         
  > 	print("*** Starting the calculations")
  [1] "*** Starting the calculations"
  > 	## search for a capacity which satisfies the constraints
  > 	lsc <- ls.sorting.capa.ident(n ,k, P, cl.proto, d,
  +                                    A.Shapley.preorder = Asp,
  +                                    A.Shapley.interval = Asi,
  +                                    A.interaction.preorder = Aip,
  +                                    A.interaction.interval = Aii,
  +                                    A.inter.additive.partition = Aiap)
  Error in ls.sorting.capa.ident(n, k, P, cl.proto, d, A.Shapley.preorder = Asp,  : 
    not enough classes
  Execution halted