Last updated on 2024-09-13 03:49:16 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 0.4-12 | 14.43 | 93.53 | 107.96 | OK | |
| r-devel-linux-x86_64-debian-gcc | 0.4-12 | 9.35 | 66.51 | 75.86 | OK | |
| r-devel-linux-x86_64-fedora-clang | 0.4-12 | 169.72 | ERROR | |||
| r-devel-linux-x86_64-fedora-gcc | 0.4-12 | 160.91 | NOTE | |||
| r-devel-windows-x86_64 | 0.4-12 | 18.00 | 115.00 | 133.00 | OK | |
| r-patched-linux-x86_64 | 0.4-12 | 15.23 | 86.59 | 101.82 | OK | |
| r-release-linux-x86_64 | 0.4-12 | 12.43 | 86.93 | 99.36 | OK | |
| r-release-macos-arm64 | 0.4-12 | 46.00 | OK | |||
| r-release-macos-x86_64 | 0.4-12 | 92.00 | OK | |||
| r-release-windows-x86_64 | 0.4-12 | 17.00 | 114.00 | 131.00 | OK | |
| r-oldrel-macos-arm64 | 0.4-12 | 55.00 | OK | |||
| r-oldrel-macos-x86_64 | 0.4-12 | 152.00 | OK | |||
| r-oldrel-windows-x86_64 | 0.4-12 | 18.00 | 139.00 | 157.00 | OK |
Version: 0.4-12
Check: compiled code
Result: NOTE
File ‘kappalab/libs/kappalab.so’:
Found no calls to: ‘R_registerRoutines’, ‘R_useDynamicSymbols’
It is good practice to register native routines and to disable symbol
search.
See ‘Writing portable packages’ in the ‘Writing R Extensions’ manual.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc
Version: 0.4-12
Check: tests
Result: ERROR
Running ‘Choquet.integral-methods.R’
Running ‘Mobius-methods.R’
Running ‘Mobius.capacity-class.R’
Running ‘Mobius.card.set.func-class.R’
Running ‘Mobius.game-class.R’
Running ‘Mobius.set.func-class.R’
Running ‘Shapley.value-methods.R’
Running ‘capacity-class.R’
Running ‘card.capacity-class.R’
Running ‘card.game-class.R’
Running ‘card.set.func-class.R’
Running ‘conjugate-methods.R’
Running ‘entropy-methods.R’
Running ‘entropy.capa.ident.R’
Running ‘heuristic.ls.capa.ident.R’
Running ‘interaction.indices-methods.R’
Running ‘is.cardinal-methods.R’
Running ‘is.kadditive-methods.R’
Running ‘is.monotone-methods.R’
Running ‘k.truncate.Mobius-methods.R’
Running ‘least.squares.capa.ident.R’
Running ‘lin.prog.capa.ident.R’
Running ‘ls.sorting.treatment.R’
Running ‘mini.dist.capa.ident.R’
Running ‘mini.var.capa.ident.R’
Running ‘orness-methods.R’
Running ‘set.func-class.R’
Running ‘to.data.frame-methods.R’
Running ‘variance-methods.R’
Running ‘veto-methods.R’
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
Flavor: r-devel-linux-x86_64-fedora-clang