--- pkg/tests/indexing.R 2005/08/27 21:26:23 873 +++ pkg/tests/indexing.R 2008/04/28 12:37:01 2186 @@ -1,38 +1,76 @@ -#### For both 'Extract' ("[") and 'Replace' ("[<-") Method testing +## For both 'Extract' ("[") and 'Replace' ("[<-") Method testing library(Matrix) -identical3 <- function(x,y,z) identical(x,y) && identical (y,z) -identical4 <- function(a,b,c,d) identical(a,b) && identical3(b,c,d) +source(system.file("test-tools.R", package = "Matrix"))# identical3() etc + +if(interactive()) { + options(error = recover) +} else options(verbose = TRUE)# to show message()s ### Dense Matrices -m <- Matrix(1:28, nrow = 7) -validObject(m) ; m@x <- as.double(m@x) ; validObject(m) +m <- Matrix(1:28 +0, nrow = 7) +validObject(m) stopifnot(identical(m, m[]), identical(m[2, 3], 16), # simple number identical(m[2, 3:4], c(16,23))) # simple numeric of length 2 m[2, 3:4, drop=FALSE] # sub matrix of class 'dgeMatrix' -m[-(4:7), 3:4] # dito; the upper right corner of 'm' +m[-(4:7), 3:4] # ditto; the upper right corner of 'm' ## rows or columns only: m[1,] # first row, as simple numeric vector m[,2] # 2nd column m[,1:2] # sub matrix of first two columns m[-(1:6),, drop=FALSE] # not the first 6 rows, i.e. only the 7th +m[integer(0),] #-> 0 x 4 Matrix +m[2:4, numeric(0)] #-> 3 x 0 Matrix ## logical indexing stopifnot(identical(m[2,3], m[(1:nrow(m)) == 2, (1:ncol(m)) == 3]), identical(m[2,], m[(1:nrow(m)) == 2, ]), identical(m[,3:4], m[, (1:4) >= 3])) -## dimnames index (TODO) - -## TODO: more --- particularly once we have "m > 10" working! - +## dimnames indexing: +mn <- m +dimnames(mn) <- list(paste("r",letters[1:nrow(mn)],sep=""), + LETTERS[1:ncol(mn)]) +checkMatrix(mn) +mn["rd", "D"] +stopifnot(identical(mn["rc", "D"], mn[3,4]), mn[3,4] == 24, + identical(mn[, "A"], mn[,1]), mn[,1] == 1:7, + identical(mn[c("re", "rb"), "B"], mn[c(5,2), 2]) + ) + +mo <- m +m[2,3] <- 100 +m[1:2, 4] <- 200 +m[, 1] <- -1 +m[1:3,] + +m. <- as.matrix(m) + +## m[ cbind(i,j) ] indexing: +ij <- cbind(1:6, 2:3) +stopifnot(identical(m[ij], m.[ij])) + +## testing operations on logical Matrices rather more than indexing: +g10 <- m [ m > 10 ] +stopifnot(18 == length(g10)) +stopifnot(10 == length(m[ m <= 10 ])) +sel <- (20 < m) & (m < 150) +sel.<- (20 < m.)& (m.< 150) +nsel <-(20 >= m) | (m >= 150) +(ssel <- as(sel, "sparseMatrix")) +stopifnot(is(sel, "lMatrix"), is(ssel, "lsparseMatrix"), + identical3(as.mat(sel.), as.mat(sel), as.mat(ssel)), + identical3(!sel, !ssel, nsel), # ! is typically dense + identical3(m[ sel], m[ ssel], as.matrix(m)[as.matrix( ssel)]), + identical3(m[!sel], m[!ssel], as.matrix(m)[as.matrix(!ssel)]) + ) -### Sparse Matrices +## more sparse Matrices -------------------------------------- m <- 1:800 set.seed(101) ; m[sample(800, 600)] <- 0 @@ -46,17 +84,454 @@ mC[,1] mC[1:2,] -mC[7, drop = FALSE] +mC[7, drop = FALSE] +assert.EQ.mat(mC[1:2,], mm[1:2,]) -mT[,c(2,4)] -mT[1,] -mT[4, drop = FALSE] +## *repeated* (aka 'duplicated') indices - did not work at all ... +i <- rep(8:10,2) +j <- c(2:4, 4:3) +assert.EQ.mat(mC[i,], mm[i,]) +assert.EQ.mat(mC[,j], mm[,j]) +assert.EQ.mat(mC[i, 2:1], mm[i, 2:1]) +assert.EQ.mat(mC[c(4,1,2:1), j], mm[c(4,1,2:1), j]) +assert.EQ.mat(mC[i,j], mm[i,j]) +set.seed(7) +for(n in 1:50) { + i <- sample(sample(nrow(mC), 7), 20, replace = TRUE) + j <- sample(sample(ncol(mC), 6), 17, replace = TRUE) + assert.EQ.mat(mC[i,j], mm[i,j]) +} + +##---- Symmetric indexing of symmetric Matrix ---------- +m. <- mC; m.[, c(2, 7:12)] <- 0 +validObject(S <- crossprod(add.simpleDimnames(m.) %% 100)) +ss <- as(S, "matrix") +T <- as(S, "TsparseMatrix") +## non-repeated indices: +i <- c(7:5, 2:4);assert.EQ.mat(T[i,i], ss[i,i]) +N <- nrow(T) +set.seed(11) +for(n in 1:50) { + i <- sample(N, max(2, sample(N,1)), replace = FALSE) + validObject(Tii <- T[i,i]) + stopifnot(is(Tii, "dsTMatrix"), # remained symmetric Tsparse + identical(t(Tii), t(T)[i,i])) + assert.EQ.mat(Tii, ss[i,i]) +} + +## repeated ones ``the challenge'' (to do smartly): +j <- c(4, 4, 9, 12, 9, 4, 17, 3, 18, 4, 12, 18, 4, 9) +assert.EQ.mat(T[j,j], ss[j,j]) +## and another two sets (a, A) & (a., A.) : +a <- matrix(0, 6,6) +a[upper.tri(a)] <- (utr <- c(2, 0,-1, 0,0,5, 7,0,0,0, 0,0,-2,0,8)) +ta <- t(a); ta[upper.tri(a)] <- utr; a <- t(ta) +diag(a) <- c(0,3,0,4,6,0) +A <- as(Matrix(a), "TsparseMatrix") +A. <- A +diag(A.) <- 10 * (1:6) +a. <- as(A., "matrix") +## More testing {this was not working for a long time..} +set.seed(1) +for(n in 1:100) { + i <- sample(1:nrow(A), 3+2*rpois(1, lam=3), replace=TRUE) + Aii <- A[i,i] + A.ii <- A.[i,i] + stopifnot(class(Aii) == class(A), + class(A.ii) == class(A.)) + assert.EQ.mat(Aii , a [i,i]) + assert.EQ.mat(A.ii, a.[i,i]) + assert.EQ.mat(T[i,i], ss[i,i]) +} + + +stopifnot(all.equal(mC[,3], mm[,3]), + identical(mC[ij], mm[ij])) +assert.EQ.mat(mC[7, , drop=FALSE], mm[7, , drop=FALSE]) + +stopifnot(dim(mC[numeric(0), ]) == c(0,20), # used to give warnings + dim(mC[, integer(0)]) == c(40,0), + identical(mC[, integer(0)], mC[, FALSE]), + identical(mC[7, drop = FALSE], + mC[7,, drop = FALSE])) +validObject(print(mT[,c(2,4)])) +stopifnot(all.equal(mT[2,], mm[2,]), + ## row or column indexing in combination with t() : + identical(mT[2,], t(mT)[,2]), + identical(mT[-2,], t(t(mT)[,-2])), + identical(mT[c(2,5),], t(t(mT)[,c(2,5)])) + ) +assert.EQ.mat(mT[4,, drop = FALSE], mm[4,, drop = FALSE]) stopifnot(identical3(mm[,1], mC[,1], mT[,1]), identical3(mm[3,], mC[3,], mT[3,]), identical3(mT[2,3], mC[2,3], 0), identical(mT[], mT), - ## TODO: identical4() with m[c(3,7), 2:4] - identical3(as(mC[c(3,7), 2:4],"matrix"), mm[c(3,7), 2:4], - as(mT[c(3,7), 2:4],"matrix"))) + identical4( mm[c(3,7), 2:4], as.mat( m[c(3,7), 2:4]), + as.mat(mT[c(3,7), 2:4]), as.mat(mC[c(3,7), 2:4])) + ) + +x.x <- crossprod(mC) +stopifnot(class(x.x) == "dsCMatrix", + class(x.x. <- round(x.x / 10000)) == "dsCMatrix", + identical(x.x[cbind(2:6, 2:6)], + diag(x.x [2:6, 2:6]))) +head(x.x.) # Note the *non*-structural 0's printed as "0" +tail(x.x., -3) # all but the first three lines + +lx.x <- as(x.x, "lsCMatrix") # FALSE only for "structural" 0 +(l10 <- lx.x[1:10, 1:10])# "lsC" +(l3 <- lx.x[1:3, ]) +m.x <- as.mat(x.x) # as.mat() *drops* (NULL,NULL) dimnames +stopifnot(class(l10) == "lsCMatrix", # symmetric indexing -> symmetric ! + identical(as.mat(lx.x), m.x != 0), + identical(as.logical(lx.x), as.logical(m.x)), + identical(as.mat(l10), m.x[1:10, 1:10] != 0), + identical(as.mat(l3 ), m.x[1:3, ] != 0) + ) + +##-- Sub*assignment* with repeated / duplicated index: +A <- Matrix(0,4,3) ; A[c(1,2,1), 2] <- 1 ; A +B <- A; B[c(1,2,1), 2] <- 1:3; B; B. <- B +B.[3,] <- rbind(4:2) +diag(B.) <- 10 * diag(B.) +C <- B.; C[,2] <- C[,2]; C[1,] <- C[1,]; C[2:3,2:1] <- C[2:3,2:1] +stopifnot(identical(unname(as.matrix(A)), + local({a <- matrix(0,4,3); a[c(1,2,1), 2] <- 1 ; a})), + identical(unname(as.matrix(B)), + local({a <- matrix(0,4,3); a[c(1,2,1), 2] <- 1:3; a})), + identical(C, drop0(B.))) + + +## used to fail +n <- 5 ## or much larger +sm <- new("dsTMatrix", i=as.integer(1),j=as.integer(1), + Dim=as.integer(c(n,n)), x = 1) +(cm <- as(sm, "CsparseMatrix")) +sm[2,] +stopifnot(sm[2,] == c(0:1, rep.int(0,ncol(sm)-2)), + sm[2,] == cm[2,], + sm[,3] == sm[3,], + all(sm[,-(1:3)] == t(sm[-(1:3),])), # all() + all(sm[,-(1:3)] == 0) + ) + +m0 <- Diagonal(5) +stopifnot(identical(m0[2,], m0[,2]), + identical(m0[,1], c(1,0,0,0,0))) +### Diagonal -- Sparse: +(m1 <- as(m0, "sparseMatrix")) # dtTMatrix +(m2 <- as(m0, "CsparseMatrix")) # dtCMatrix (with an irrelevant warning) +m1g <- as(m1, "generalMatrix") +stopifnot(is(m1g, "dgTMatrix")) +assert.EQ.mat(m2[1:3,], diag(5)[1:3,]) +assert.EQ.mat(m2[,c(4,1)], diag(5)[,c(4,1)]) +stopifnot(identical(m2[1:3,], as(m1[1:3,], "CsparseMatrix")), + identical(Matrix:::uniqTsparse(m1[, c(4,2)]), + Matrix:::uniqTsparse(as(m2[, c(4,2)], "TsparseMatrix"))) + )## failed in 0.9975-11 + +(uTr <- new("dtTMatrix", Dim = c(3L,3L), diag="U")) +uTr[1,] <- 0 +assert.EQ.mat(uTr, cbind(0, rbind(0,diag(2)))) + +M <- m0; M[1,] <- 0 +stopifnot(identical(M, Diagonal(x=c(0, rep(1,4))))) +M <- m0; M[,3] <- 3 ; M ; stopifnot(is(M, "sparseMatrix"), M[,3] == 3) +checkMatrix(M) +M <- m0; M[1:3, 3] <- 0 ;M +T <- m0; T[1:3, 3] <- 10 +stopifnot(identical(M, Diagonal(x=c(1,1, 0, 1,1))), + is(T, "triangularMatrix"), identical(T[,3], c(10,10,10,0,0))) + +M <- m1; M[1,] <- 0 ; M ; assert.EQ.mat(M, diag(c(0,rep(1,4))), tol=0) +M <- m1; M[,3] <- 3 ; stopifnot(is(M,"sparseMatrix"), M[,3] == 3) +checkMatrix(M) +M <- m1; M[1:3, 3] <- 0 ;M +assert.EQ.mat(M, diag(c(1,1, 0, 1,1)), tol=0) +T <- m1; T[1:3, 3] <- 10; checkMatrix(T) +stopifnot(is(T, "dtTMatrix"), identical(T[,3], c(10,10,10,0,0))) + +M <- m2; M[1,] <- 0 ; M ; assert.EQ.mat(M, diag(c(0,rep(1,4))), tol=0) +M <- m2; M[,3] <- 3 ; stopifnot(is(M,"sparseMatrix"), M[,3] == 3) +checkMatrix(M) +M <- m2; M[1:3, 3] <- 0 ;M +assert.EQ.mat(M, diag(c(1,1, 0, 1,1)), tol=0) +T <- m2; T[1:3, 3] <- 10; checkMatrix(T) +stopifnot(is(T, "dtCMatrix"), identical(T[,3], c(10,10,10,0,0))) + + +## "Vector indices" ------------------- +D <- Diagonal(6) +M <- as(D,"dgeMatrix") +m <- as(D,"matrix") +s <- as(D,"TsparseMatrix") +S <- as(s,"CsparseMatrix") +i <- c(3,1,6); v <- c(10,15,20) +## (logical,value) which both are recycled: +L <- c(TRUE, rep(FALSE,8)) ; z <- c(50,99) + +## vector subassignment, both with integer & logical +## these now work correctly {though not very efficiently; hence warnings} +m[i] <- v # the role model: only first column is affected +M[i] <- v; assert.EQ.mat(M,m) # dge +D[i] <- v; assert.EQ.mat(D,m) # ddi -> dtT -> dgT +s[i] <- v; assert.EQ.mat(s,m) # dtT -> dgT +S[i] <- v; assert.EQ.mat(S,m); S # dtC -> dtT -> dgT -> dgC +## logical +m[L] <- z +M[L] <- z; assert.EQ.mat(M,m) +D[L] <- z; assert.EQ.mat(D,m) +s[L] <- z; assert.EQ.mat(s,m) +S[L] <- z; assert.EQ.mat(S,m) ; S + +## indexing [i] vs [i,] --- now ok +stopifnot(identical4(m[i], M[i], D[i], s[i]), identical(s[i],S[i])) +stopifnot(identical4(m[L], M[L], D[L], s[L]), identical(s[L],S[L])) +assert.EQ.mat(D[i,], m[i,]) +assert.EQ.mat(M[i,], m[i,]) +assert.EQ.mat(s[i,], m[i,]) +assert.EQ.mat(S[i,], m[i,]) + +assert.EQ.mat(D[,i], m[,i]) +assert.EQ.mat(M[,i], m[,i]) +assert.EQ.mat(s[,i], m[,i]) +assert.EQ.mat(S[,i], m[,i]) + + +## --- negative indices ---------- +mc <- mC[1:5, 1:7] +mt <- mT[1:5, 1:7] +## sub matrix +assert.EQ.mat(mC[1:2, 0:3], mm[1:2, 0:3]) # test 0-index +stopifnot(identical(mc[-(3:5), 0:2], mC[1:2, 0:2]), + identical(mt[-(3:5), 0:2], mT[1:2, 0:2]), + identical(mC[2:3, 4], mm[2:3, 4])) +assert.EQ.mat(mC[1:2,], mm[1:2,]) +## sub vector +stopifnot(identical4(mc[-(1:4), ], mC[5, 1:7], + mt[-(1:4), ], mT[5, 1:7])) +stopifnot(identical4(mc[-(1:4), -(2:4)], mC[5, c(1,5:7)], + mt[-(1:4), -(2:4)], mT[5, c(1,5:7)])) + +## mixing of negative and positive must give error +assertError(mT[-1:1,]) + +## Sub *Assignment* ---- now works (partially): +mt0 <- mt +mt[1, 4] <- -99 +mt[2:3, 1:6] <- 0 +mt +m2 <- mt+mt +m2[1,4] <- -200 +m2[c(1,3), c(5:6,2)] <- 1:6 +stopifnot(m2[1,4] == -200, + as.vector(m2[c(1,3), c(5:6,2)]) == 1:6) +mt[,3] <- 30 +mt[2:3,] <- 250 +mt[1:5 %% 2 == 1, 3] <- 0 +mt[3:1, 1:7 > 5] <- 0 +mt + +tt <- as(mt,"matrix") +ii <- c(0,2,5) +jj <- c(2:3,5) +tt[ii, jj] <- 1:6 # 0 is just "dropped" +mt[ii, jj] <- 1:6 +assert.EQ.mat(mt, tt) + +mt[1:5, 2:6] +as((mt0 - mt)[1:5,], "dsparseMatrix")# [1,5] and lines 2:3 + +mt[c(2,4), ] <- 0; stopifnot(as(mt[c(2,4), ],"matrix") == 0) +mt[2:3, 4:7] <- 33 +checkMatrix(mt) +mt + +mc[1,4] <- -99 ; stopifnot(mc[1,4] == -99) +mc[1,4] <- 00 ; stopifnot(mc[1,4] == 00) +mc[1,4] <- -99 ; stopifnot(mc[1,4] == -99) +mc[1:2,4:3] <- 4:1; stopifnot(as.matrix(mc[1:2,4:3]) == 4:1) + +mc[-1, 3] <- -2:1 # 0 should not be entered; 'value' recycled +mt[-1, 3] <- -2:1 +stopifnot(mc@x != 0, mt@x != 0, + mc[-1,3] == -2:1, mt[-1,3] == -2:1) ## failed earlier + +mc0 <- mc +mt0 <- as(mc0, "TsparseMatrix") +m0 <- as(mc0, "matrix") +set.seed(1) +for(i in 1:50) { + mc <- mc0; mt <- mt0 ; m <- m0 + ev <- 1:5 %% 2 == round(runif(1))# 0 or 1 + j <- sample(ncol(mc), 1 + round(runif(1))) + nv <- rpois(sum(ev) * length(j), lambda = 1) + mc[ev, j] <- nv + m[ev, j] <- nv + mt[ev, j] <- nv + if(i %% 10 == 1) print(mc[ev,j, drop = FALSE]) + stopifnot(as.vector(mc[ev, j]) == nv, ## failed earlier... + as.vector(mt[ev, j]) == nv) + validObject(mc) ; assert.EQ.mat(mc, m) + validObject(mt) ; assert.EQ.mat(mt, m) +} + +mc # no longer has non-structural zeros +mc[ii, jj] <- 1:6 +mc[c(2,5), c(3,5)] <- 3.2 +checkMatrix(mc) +m. <- mc +mc[4,] <- 0 +mc + +S <- as(Diagonal(5),"sparseMatrix") +H <- Hilbert(9) +Hc <- as(round(H, 3), "dsCMatrix")# a sparse matrix with no 0 ... +(trH <- tril(Hc[1:5, 1:5])) +stopifnot(is(trH, "triangularMatrix"), trH@uplo == "L", + is(S, "triangularMatrix")) + +## triangular assignment +## the slick (but inefficient in case of sparse!) way to assign sub-diagonals: +## equivalent to tmp <- `diag<-`(S[,-1], -2:1); S[,-1] <- tmp +## which dispatches to (x="TsparseMatrix", i="missing",j="index", value="replValue") +diag(S[,-1]) <- -2:1 # used to give a wrong warning +S <- as(S,"triangularMatrix") +assert.EQ.mat(S, local({s <- diag(5); diag(s[,-1]) <- -2:1; s})) + +trH[c(1:2,4), c(2:3,5)] <- 0 # gave an *error* upto Jan.2008 +trH[ lower.tri(trH) ] <- 0 # ditto, because of callNextMethod() + +m <- Matrix(0+1:28, nrow = 4) +m[-3,c(2,4:5,7)] <- m[ 3, 1:4] <- m[1:3, 6] <- 0 +mT <- as(m, "dgTMatrix") +stopifnot(identical(mT[lower.tri(mT)], + m [lower.tri(m) ])) +lM <- upper.tri(mT, diag=TRUE) +mT[lM] <- 0 + m[lM] <- 0 +assert.EQ.mat(mT, as(m,"matrix")) +mT[lM] <- -1:0 + m[lM] <- -1:0 +assert.EQ.mat(mT, as(m,"matrix")) +(mT <- drop0(mT)) + +i <- c(1:2, 4, 6:7); j <- c(2:4,6) +H[i,j] <- 0 +(H. <- round(as(H, "sparseMatrix"), 3)[ , 2:7]) +Hc. <- Hc +Hc.[i,j] <- 0 ## now "works", but setting "non-structural" 0s +stopifnot(as.matrix(Hc.[i,j]) == 0) +Hc.[, 1:6] + +## an example that failed for a long time +sy3 <- new("dsyMatrix", Dim = as.integer(c(2, 2)), x = c(14, -1, 2, -7)) +checkMatrix(dm <- kronecker(Diagonal(2), sy3))# now sparse with new kronecker +dm <- Matrix(as.matrix(dm))# -> "dsyMatrix" +(s2 <- as(dm, "sparseMatrix")) +checkMatrix(st <- as(s2, "TsparseMatrix")) +stopifnot(is(s2, "symmetricMatrix"), + is(st, "symmetricMatrix")) +checkMatrix(s.32 <- st[1:3,1:2]) ## 3 x 2 - and *not* dsTMatrix +checkMatrix(s2.32 <- s2[1:3,1:2]) +I <- c(1,4:3) +stopifnot(is(s2.32, "generalMatrix"), + is(s.32, "generalMatrix"), + identical(as.mat(s.32), as.mat(s2.32)), + identical3(dm[1:3,-1], asD(s2[1:3,-1]), asD(st[1:3,-1])), + identical4(2, dm[4,3], s2[4,3], st[4,3]), + identical3(diag(dm), diag(s2), diag(st)), + is((cI <- s2[I,I]), "dsCMatrix"), + is((tI <- st[I,I]), "dsTMatrix"), + identical4(as.mat(dm)[I,I], as.mat(dm[I,I]), as.mat(tI), as.mat(cI)) + ) + +## now sub-assign and check for consistency +## symmetric subassign should keep symmetry +st[I,I] <- 0; checkMatrix(st); stopifnot(is(st,"symmetricMatrix")) +s2[I,I] <- 0; checkMatrix(s2); stopifnot(is(s2,"symmetricMatrix")) +## +m <- as.mat(st) + m[2:1,2:1] <- 4:1 +st[2:1,2:1] <- 4:1 +s2[2:1,2:1] <- 4:1 +stopifnot(identical(m, as.mat(st)), + 1:4 == as.vector(s2[1:2,1:2]), + identical(m, as.mat(s2))) + +## now a slightly different situation for 's2' (had bug) +s2 <- as(dm, "sparseMatrix") +s2[I,I] <- 0; diag(s2)[2:3] <- -(1:2) +stopifnot(is(s2,"symmetricMatrix"), diag(s2) == c(0:-2,0)) +t2 <- as(s2, "TsparseMatrix") +m <- as.mat(s2) +s2[2:1,2:1] <- 4:1 +t2[2:1,2:1] <- 4:1 + m[2:1,2:1] <- 4:1 +assert.EQ.mat(t2, m) +assert.EQ.mat(s2, m) +## and the same (for a different s2 !) +s2[2:1,2:1] <- 4:1 +t2[2:1,2:1] <- 4:1 +assert.EQ.mat(t2, m)# ok +assert.EQ.mat(s2, m)# failed in 0.9975-8 + + +## m[cbind(i,j)] <- value: +m.[ cbind(3:5, 1:3) ] <- 1:3 +stopifnot(m.[3,1] == 1, m.[4,2] == 2) +x.x[ cbind(2:6, 2:6)] <- 12:16 +stopifnot(isValid(x.x, "dsCMatrix"), + 12:16 == as.mat(x.x)[cbind(2:6, 2:6)]) +(ne1 <- (mc - m.) != 0) +stopifnot(identical(ne1, 0 != abs(mc - m.))) +(ge <- m. >= mc) # contains "=" -> result is dense +ne. <- mc != m. # was wrong (+ warning) +stopifnot(identical(!(m. < mc), m. >= mc), + identical(m. < mc, as(!ge, "sparseMatrix")), + identical(ne., drop0(ne1))) + +(M3 <- Matrix(upper.tri(matrix(, 3, 3)))) # ltC; indexing used to fail +T3 <- as(M3, "TsparseMatrix") +stopifnot(identical(drop(M3), M3), + identical4(drop(M3[,2, drop = FALSE]), M3[,2, drop = TRUE], + drop(T3[,2, drop = FALSE]), T3[,2, drop = TRUE]), + is(T3, "triangularMatrix"), + !is(T3[,2, drop=FALSE], "triangularMatrix") + ) + +(T6 <- as(as(kronecker(Matrix(c(0,0,1,0),2,2), t(T3)), "lMatrix"), + "triangularMatrix")) +T6[1:4, -(1:3)] # failed (trying to coerce back to ltTMatrix) +stopifnot(identical(T6[1:4, -(1:3)][2:3, -3], + spMatrix(2,2, i=c(1,2,2), j=c(1,1,2), x=rep(TRUE,3)))) + +M <- Diagonal(4); M[1,2] <- 2 +M. <- as(M, "CsparseMatrix") +(R <- as(M., "RsparseMatrix")) +(Ms <- symmpart(M.)) +Rs <- as(Ms, "RsparseMatrix") +stopifnot(isValid(M, "triangularMatrix"), + isValid(M.,"triangularMatrix"), + isValid(Ms, "dsCMatrix"), + isValid(R, "dtRMatrix"), + isValid(Rs, "dsRMatrix") ) +stopifnot(dim(M[2:3, FALSE]) == c(2,0), + dim(R[2:3, FALSE]) == c(2,0), + identical(M [2:3,TRUE], M [2:3,]), + identical(M.[2:3,TRUE], M.[2:3,]), + identical(R [2:3,TRUE], R [2:3,]), + dim(R[FALSE, FALSE]) == c(0,0)) + +cat('Time elapsed: ', (.pt <- proc.time()),'\n') # "stats" +## +cat("checkMatrix() of all: \n---------\n") +Sys.setlocale("LC_COLLATE", "C")# to keep ls() reproducible +for(nm in ls()) if(is(.m <- get(nm), "Matrix")) { + cat(nm, "\n") + checkMatrix(.m, verbose = FALSE) +} +cat('Time elapsed: ', proc.time() - .pt,'\n') # "stats" +if(!interactive()) warnings()