CRAN Package Check Results for Package kappalab

Last updated on 2020-04-25 01:53:05 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.4-7 14.67 98.96 113.63 NOTE
r-devel-linux-x86_64-debian-gcc 0.4-7 10.63 77.49 88.12 NOTE
r-devel-linux-x86_64-fedora-clang 0.4-7 136.59 NOTE
r-devel-linux-x86_64-fedora-gcc 0.4-7 142.06 NOTE
r-devel-windows-ix86+x86_64 0.4-7 42.00 173.00 215.00 ERROR
r-patched-linux-x86_64 0.4-7 12.43 96.89 109.32 NOTE
r-patched-osx-x86_64 0.4-7 OK
r-patched-solaris-x86 0.4-7 195.80 NOTE
r-release-linux-x86_64 0.4-7 11.10 88.10 99.20 OK
r-release-windows-ix86+x86_64 0.4-7 49.00 251.00 300.00 OK
r-release-osx-x86_64 0.4-7 OK
r-oldrel-windows-ix86+x86_64 0.4-7 34.00 210.00 244.00 OK
r-oldrel-osx-x86_64 0.4-7 OK

Check Details

Version: 0.4-7
Check: for non-standard things in the check directory
Result: NOTE
    Found the following files/directories:
     'my.Mobius.set.func.csv' 'my.card.set.func.csv' 'my.set.func.csv'
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-linux-x86_64, r-patched-solaris-x86

Version: 0.4-7
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: 0.4-7
Check: running tests for arch ‘x64’
Result: ERROR
     Running 'Choquet.integral-methods.R' [1s]
     Running 'Mobius-methods.R' [1s]
     Running 'Mobius.capacity-class.R' [1s]
     Running 'Mobius.card.set.func-class.R' [1s]
     Running 'Mobius.game-class.R' [2s]
     Running 'Mobius.set.func-class.R' [1s]
     Running 'Shapley.value-methods.R' [1s]
     Running 'capacity-class.R' [1s]
     Running 'card.capacity-class.R' [1s]
     Running 'card.game-class.R' [1s]
     Running 'card.set.func-class.R' [1s]
     Running 'conjugate-methods.R' [1s]
     Running 'entropy-methods.R' [2s]
     Running 'entropy.capa.ident.R' [2s]
     Running 'heuristic.ls.capa.ident.R' [1s]
     Running 'interaction.indices-methods.R' [1s]
     Running 'is.cardinal-methods.R' [1s]
     Running 'is.kadditive-methods.R' [2s]
     Running 'is.monotone-methods.R' [1s]
     Running 'k.truncate.Mobius-methods.R' [1s]
     Running 'least.squares.capa.ident.R' [2s]
     Running 'lin.prog.capa.ident.R' [1s]
     Running 'ls.sorting.treatment.R' [1s]
     Running 'mini.dist.capa.ident.R' [1s]
     Running 'mini.var.capa.ident.R' [1s]
     Running 'orness-methods.R' [2s]
     Running 'set.func-class.R' [1s]
     Running 'to.data.frame-methods.R' [1s]
     Running 'variance-methods.R' [2s]
     Running 'veto-methods.R' [2s]
    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-windows-ix86+x86_64