CRAN Package Check Results for Package kappalab

Last updated on 2024-05-02 11:51:25 CEST.

Flavor	Version	Tinstall	Tcheck	Ttotal	Status	Flags
r-devel-linux-x86_64-debian-clang	0.4-12	14.31	120.55	134.86	ERROR
r-devel-linux-x86_64-debian-gcc	0.4-12	12.37	87.20	99.57	OK
r-devel-linux-x86_64-fedora-clang	0.4-12			166.68	NOTE
r-devel-linux-x86_64-fedora-gcc	0.4-12			159.91	NOTE
r-devel-windows-x86_64	0.4-12	17.00	112.00	129.00	OK
r-patched-linux-x86_64	0.4-12	17.33	112.25	129.58	OK
r-release-linux-x86_64	0.4-12	13.80	111.01	124.81	OK
r-release-macos-arm64	0.4-12			46.00	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	21.00	142.00	163.00	OK

Check Details

Version: 0.4-12
Check: tests
Result: ERROR Running ‘Choquet.integral-methods.R’ [1s/2s] Running ‘Mobius-methods.R’ [1s/2s] Running ‘Mobius.capacity-class.R’ [2s/2s] Running ‘Mobius.card.set.func-class.R’ [2s/2s] Running ‘Mobius.game-class.R’ [1s/2s] Running ‘Mobius.set.func-class.R’ [1s/2s] Running ‘Shapley.value-methods.R’ [1s/2s] Running ‘capacity-class.R’ [1s/2s] Running ‘card.capacity-class.R’ [2s/2s] Running ‘card.game-class.R’ [1s/2s] Running ‘card.set.func-class.R’ [1s/2s] Running ‘conjugate-methods.R’ [1s/2s] Running ‘entropy-methods.R’ [2s/2s] Running ‘entropy.capa.ident.R’ [2s/2s] Running ‘heuristic.ls.capa.ident.R’ [2s/3s] Running ‘interaction.indices-methods.R’ [2s/2s] Running ‘is.cardinal-methods.R’ [2s/2s] Running ‘is.kadditive-methods.R’ [1s/2s] Running ‘is.monotone-methods.R’ [1s/2s] Running ‘k.truncate.Mobius-methods.R’ [1s/2s] Running ‘least.squares.capa.ident.R’ [2s/3s] Running ‘lin.prog.capa.ident.R’ [1s/2s] Running ‘ls.sorting.treatment.R’ [2s/2s] Running ‘mini.dist.capa.ident.R’ [2s/2s] Running ‘mini.var.capa.ident.R’ [1s/2s] Running ‘orness-methods.R’ [1s/2s] Running ‘set.func-class.R’ [1s/2s] Running ‘to.data.frame-methods.R’ [1s/2s] Running ‘variance-methods.R’ [1s/2s] Running ‘veto-methods.R’ [2s/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-linux-x86_64-debian-clang

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