--- pkg/tests/indexing.R 2006/11/03 23:18:07 1665 +++ pkg/tests/indexing.R 2010/02/04 17:09:33 2518 @@ -1,19 +1,29 @@ -#### For both 'Extract' ("[") and 'Replace' ("[<-") Method testing +## For both 'Extract' ("[") and 'Replace' ("[<-") Method testing library(Matrix) -source(system.file("test-tools.R", package = "Matrix"))# identical3() etc +source(system.file("test-tools.R", package = "Matrix"), keep.source = FALSE) +##-> identical3() etc + +if(interactive()) { + options(error = recover, warn = 1) +} else if(FALSE) { ## MM @ testing + options(error = recover, Matrix.verbose = TRUE, warn = 1) +} else +options(Matrix.verbose = TRUE, warn = 1) + ### 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 + identical(m[2, 3], 16), # simple number + identical(m[2, 3:4], c(16,23)), # simple numeric of length 2 + identical(m[NA,NA], as(Matrix(NA, 7,4), "dMatrix"))) 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 @@ -32,11 +42,21 @@ mn <- m dimnames(mn) <- list(paste("r",letters[1:nrow(mn)],sep=""), LETTERS[1:ncol(mn)]) +checkMatrix(mn) mn["rd", "D"] +## Printing sparse colnames: +ms <- as(mn,"sparseMatrix") +ms[sample(28, 20)] <- 0 +ms <- t(rbind2(ms, 3*ms)) +cnam1 <- capture.output(show(ms))[2] ; op <- options("sparse.colnames" = "abb3") +cnam2 <- capture.output(show(ms))[2] ; options(op) # revert 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]) - ) + identical(mn[c("re", "rb"), "B"], mn[c(5,2), 2]), + ## sparse printing + grep("^ +\$", cnam1) == 1, # cnam1 is empty + identical(cnam2, + paste(" ", paste(rep(rownames(mn), 2), collapse=" ")))) mo <- m m[2,3] <- 100 @@ -44,8 +64,15 @@ m[, 1] <- -1 m[1:3,] -## testing operations on logical Matrices rather more than indexing: m. <- as.matrix(m) + +## m[ cbind(i,j) ] indexing: +iN <- ij <- cbind(1:6, 2:3) +iN[2:3,] <- iN[5,2] <- NA +stopifnot(identical(m[ij], m.[ij]), + identical(m[iN], m.[iN])) + +## testing operations on logical Matrices rather more than indexing: g10 <- m [ m > 10 ] stopifnot(18 == length(g10)) stopifnot(10 == length(m[ m <= 10 ])) @@ -70,27 +97,122 @@ str(mC <- as(m, "dgCMatrix")) str(mT <- as(m, "dgTMatrix")) stopifnot(identical(mT, as(mC, "dgTMatrix")), - identical(mC, as(mT, "dgCMatrix"))) + identical(mC, as(mT, "dgCMatrix")), + identical(mC[0,0], new("dgCMatrix")), + identical(mT[0,0], new("dgTMatrix")), + identical(mT[0,], new("dgTMatrix", Dim = c(0L,20L))), + identical(mT[,0], new("dgTMatrix", Dim = c(40L,0L))), + identical(mC[0,], as(mT[FALSE,], "dgCMatrix")), + identical(mC[,0], as(mT[,FALSE], "dgCMatrix")), + TRUE) mC[,1] mC[1:2,] mC[7, drop = FALSE] assert.EQ.mat(mC[1:2,], mm[1:2,]) -stopifnot(all.equal(mC[,3], mm[,3])) + +## *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]) +## FIXME? assert.EQ.mat(mC[,NA], mm[,NA]) -- mC[,NA] is all 0 "instead" of all NA +## MM currently thinks we should NOT allow [ ] +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") +ds <- as(S, "denseMatrix") +## NA-indexing of *dense* Matrices: should work as traditionally +assert.EQ.mat(ds[NA,NA], ss[NA,NA]) +assert.EQ.mat(ds[NA, ], ss[NA,]) +assert.EQ.mat(ds[ ,NA], ss[,NA]) +T <- as(S, "TsparseMatrix") +stopifnot(identical(ds[2 ,NA], ss[2,NA]), + identical(ds[NA, 1], ss[NA, 1]), + identical(S, as(T, "CsparseMatrix")) ) + +## non-repeated indices: +i <- c(7:5, 2:4);assert.EQ.mat(T[i,i], ss[i,i]) +## NA in indices -- check that we get a helpful error message: +i[2] <- NA +er <- tryCatch(T[i,i], error = function(e)e) +stopifnot(as.logical(grep("indices.*sparse Matrices", er\$message))) + +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]) ; tTi <- t(T)[i,i] + stopifnot(is(Tii, "dsTMatrix"), # remained symmetric Tsparse + is(tTi, "dsTMatrix"), # may not be identical when *sorted* differently + identical(as(t(Tii),"CsparseMatrix"), as(tTi,"CsparseMatrix"))) + assert.EQ.mat(Tii, ss[i,i]) +} + +b <- diag(1:2)[,c(1,1,2,2)] +cb <- crossprod(b) +cB <- crossprod(Matrix(b, sparse=TRUE)) +a <- matrix(0, 6, 6) +a[1:4, 1:4] <- cb +A1 <- A2 <- Matrix(0, 6, 6)#-> sparse +A1[1:4, 1:4] <- cb +A2[1:4, 1:4] <- cB +assert.EQ.mat(A1, a)# indeed +stopifnot(identical(A1, A2), is(A1, "dsCMatrix")) + +## 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]), + identical(mC[iN], mm[iN])) + assert.EQ.mat(mC[7, , drop=FALSE], mm[7, , drop=FALSE]) +identical (mC[7, drop=FALSE], mm[7, drop=FALSE]) # *vector* indexing 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])) + identical(mC[, integer(0)], mC[, 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)])) - ) + ## row or column indexing in combination with t() : + Q.C.identical(mT[2,], t(mT)[,2]), + Q.C.identical(mT[-2,], t(t(mT)[,-2])), + Q.C.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,]), @@ -102,14 +224,16 @@ x.x <- crossprod(mC) stopifnot(class(x.x) == "dsCMatrix", - class(x.x. <- round(x.x / 10000)) == "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(x.x, "matrix") +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)), @@ -117,6 +241,132 @@ 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, "TsparseMatrix")) # dtTMatrix +(m2 <- as(m0, "CsparseMatrix")) # dtCMatrix +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))), + isValid(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(isValid(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" ------------------- +.iniDiag.example <- expression({ + D <- Diagonal(6) + M <- as(D,"dgeMatrix") + m <- as(D,"matrix") + s <- as(D,"TsparseMatrix") + S <- as(s,"CsparseMatrix") +}) +eval(.iniDiag.example) +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 +stopifnot(identical(s,D)) +## logical +eval(.iniDiag.example) +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 +eval(.iniDiag.example) +stopifnot(identical5(m[i], M[i], D[i], s[i], S[i])) +stopifnot(identical5(m[L], M[L], D[L], s[L], S[L])) +## bordercase ' drop = .' *vector* indexing {failed till 2009-04-..) +stopifnot(identical5(m[i,drop=FALSE], M[i,drop=FALSE], D[i,drop=FALSE], + s[i,drop=FALSE], S[i,drop=FALSE])) +stopifnot(identical5(m[L,drop=FALSE], M[L,drop=FALSE], D[L,drop=FALSE], + s[L,drop=FALSE], S[L,drop=FALSE])) +## using L for row-indexing should give an error +assertError(m[L,]); assertError(m[L,, drop=FALSE]) +## these did not signal an error, upto (including) 0.999375-30: +assertError(s[L,]); assertError(s[L,, drop=FALSE]) +assertError(S[L,]); assertError(S[L,, drop=FALSE]) + +## row indexing: +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,]) +## column indexing: +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] @@ -138,6 +388,7 @@ ## Sub *Assignment* ---- now works (partially): mt0 <- mt +nt <- as(mt, "nMatrix") mt[1, 4] <- -99 mt[2:3, 1:6] <- 0 mt @@ -164,7 +415,7 @@ mt[c(2,4), ] <- 0; stopifnot(as(mt[c(2,4), ],"matrix") == 0) mt[2:3, 4:7] <- 33 -validObject(mt) +checkMatrix(mt) mt mc[1,4] <- -99 ; stopifnot(mc[1,4] == -99) @@ -175,25 +426,66 @@ 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) ##--> BUG -- fixed + 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) +} -ev <- 1:5 %% 2 == 0 -mc[ev, 3] <- 0:1 -if(FALSE)## FIXME - stopifnot(mc[ev, 3] == 0:1) ##-> BUG {very peculiar; the 2nd time it works ...} -validObject(mc) -mc # now shows a non-structural zeros +mc # no longer has non-structural zeros mc[ii, jj] <- 1:6 mc[c(2,5), c(3,5)] <- 3.2 -validObject(mc) +checkMatrix(mc) m. <- mc mc[4,] <- 0 mc +S <- as(Diagonal(5),"TsparseMatrix") 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") +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 @@ -203,4 +495,204 @@ stopifnot(as.matrix(Hc.[i,j]) == 0) Hc.[, 1:6] -cat('Time elapsed: ', proc.time(),'\n') # for ``statistical reasons'' +## 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: (2-column matrix subassignment): +m.[ cbind(3:5, 1:3) ] <- 1:3 +stopifnot(m.[3,1] == 1, m.[4,2] == 2) +nt. <- nt ; nt[rbind(2:3, 3:4, c(3,3))] <- FALSE +s. <- m. ; m.[cbind(3:4,2:3)] <- 0 ## assigning 0 where there *is* 0 .. +stopifnot(identical(nt.,nt), ## should not have changed + identical(s., m.)) +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))) + +d6 <- Diagonal(6) +ii <- c(1:2, 4:5) +d6[cbind(ii,ii)] <- 7*ii +stopifnot(is(d6, "ddiMatrix"), identical(d6, Diagonal(x=c(7*1:2,1,7*4:5,1)))) + +for(j in 3:6) { ## even and odd j used to behave differently + M <- Matrix(0, j,j); m <- matrix(0, j,j) + T <- as(M, "TsparseMatrix") + TG <- as(T, "generalMatrix") + G <- as(M, "generalMatrix") + id <- cbind(1:j,1:j) + i2 <- cbind(1:j,j:1) + m[id] <- 1:j + M[id] <- 1:j ; stopifnot(is(M,"symmetricMatrix")) + T[id] <- 1:j ; stopifnot(is(T,"symmetricMatrix")) + G[id] <- 1:j + TG[id]<- 1:j + m[i2] <- 10 + M[i2] <- 10 ; stopifnot(is(M,"symmetricMatrix")) + T[i2] <- 10 ; stopifnot(is(T,"symmetricMatrix")) + G[i2] <- 10 + TG[i2]<- 10 + ## + assert.EQ.mat(M, m) + assert.EQ.mat(T, m) + assert.EQ.mat(G, m) + assert.EQ.mat(TG,m) +} + + +## drop, triangular, ... +(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)) + +n <- 50000L +Lrg <- new("dgTMatrix", Dim = c(n,n)) +diag(Lrg) <- 1:n +dLrg <- as(Lrg, "diagonalMatrix") +stopifnot(identical(Diagonal(x = 1:n), dLrg)) +diag(dLrg) <- 1 + diag(dLrg) +Clrg <- as(Lrg,"CsparseMatrix") +Ctrg <- as(Clrg, "triangularMatrix") +diag(Ctrg) <- 1 + diag(Ctrg) +stopifnot(identical(Diagonal(x = 1+ 1:n), dLrg), + identical(Ctrg, as(dLrg,"CsparseMatrix"))) + +cc <- capture.output(show(dLrg))# show() used to error for large n + +## Large Matrix indexing / subassignment +## ------------------------------------- (from ex. by Imran Rashid) +n <- 7000000 +m <- 100000 +nnz <- 20000 + +set.seed(12) +f <- sparseMatrix(i = sample(n, size=nnz, replace=TRUE), + j = sample(m, size=nnz, replace=TRUE)) +str(f) +dim(f) # 6999863 x 99992 +prod(dim(f)) # 699930301096 == 699'930'301'096 (~ 700'000 millions) +str(thisCol <- f[,5000])# logi [~ 7 mio....] +sv <- as(thisCol, "sparseVector") +str(sv) ## "empty" ! +validObject(spCol <- f[,5000, drop=FALSE]) +## ^^ FIXME slow Tsparse_to_Csparse from memory-hog +## cholmod_sparse *CHOLMOD(triplet_to_sparse) +## which has "workspace: Iwork (max (nrow,ncol))" +## in ../src/CHOLMOD/Core/cholmod_triplet.c *and* +## in ../src/CHOLMOD/Core/t_cholmod_triplet.c +## +## *not* identical(): as(spCol, "sparseVector")@length is "double"prec: +stopifnot(all.equal(as(spCol, "sparseVector"), + as(sv, "nsparseVector"), tol=0)) +f[,5762] <- thisCol # now "fine" <<<<<<<<<< FIXME uses LARGE objects +## is using replCmat() in ../R/Csparse.R, then +## replTmat() in ../R/Tsparse.R + +fx <- sparseMatrix(i = sample(n, size=nnz, replace=TRUE), + j = sample(m, size=nnz, replace=TRUE), + x = round(10*rnorm(nnz))) +class(fx)## dgCMatrix +fx[,6000] <- (tC <- rep(thisCol, length=nrow(fx))) +thCol <- fx[,2000] +fx[,5762] <- thCol +stopifnot(is(f, "ngCMatrix"), is(fx, "dgCMatrix"), + identical(thisCol, f[,5762]),# perfect + identical(as.logical(fx[,6000]), tC), + identical(thCol, fx[,5762])) + +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() +