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Diff of /pkg/tests/indexing.R

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revision 873, Sat Aug 27 21:26:23 2005 UTC revision 2120, Tue Mar 4 21:44:41 2008 UTC
# Line 1  Line 1 
1  #### For both 'Extract' ("[") and 'Replace' ("[<-") Method testing  ## For both 'Extract' ("[") and 'Replace' ("[<-") Method testing
2    
3  library(Matrix)  library(Matrix)
4    
5  identical3 <- function(x,y,z)   identical(x,y) && identical (y,z)  source(system.file("test-tools.R", package = "Matrix"))# identical3() etc
6  identical4 <- function(a,b,c,d) identical(a,b) && identical3(b,c,d)  
7    options(verbose = TRUE)# to show message()s
8    
9  ### Dense Matrices  ### Dense Matrices
10    
11  m <- Matrix(1:28, nrow = 7)  m <- Matrix(1:28 +0, nrow = 7)
12  validObject(m) ; m@x <- as.double(m@x) ; validObject(m)  validObject(m)
13  stopifnot(identical(m, m[]),  stopifnot(identical(m, m[]),
14            identical(m[2, 3],  16), # simple number            identical(m[2, 3],  16), # simple number
15            identical(m[2, 3:4], c(16,23))) # simple numeric of length 2            identical(m[2, 3:4], c(16,23))) # simple numeric of length 2
16    
17  m[2, 3:4, drop=FALSE] # sub matrix of class 'dgeMatrix'  m[2, 3:4, drop=FALSE] # sub matrix of class 'dgeMatrix'
18  m[-(4:7), 3:4]        # dito; the upper right corner of 'm'  m[-(4:7), 3:4]        # ditto; the upper right corner of 'm'
19    
20  ## rows or columns only:  ## rows or columns only:
21  m[1,]     # first row, as simple numeric vector  m[1,]     # first row, as simple numeric vector
22  m[,2]     # 2nd column  m[,2]     # 2nd column
23  m[,1:2]   # sub matrix of first two columns  m[,1:2]   # sub matrix of first two columns
24  m[-(1:6),, drop=FALSE] # not the first 6 rows, i.e. only the 7th  m[-(1:6),, drop=FALSE] # not the first 6 rows, i.e. only the 7th
25    m[integer(0),] #-> 0 x 4 Matrix
26    m[2:4, numeric(0)] #-> 3 x 0 Matrix
27    
28  ## logical indexing  ## logical indexing
29  stopifnot(identical(m[2,3], m[(1:nrow(m)) == 2, (1:ncol(m)) == 3]),  stopifnot(identical(m[2,3], m[(1:nrow(m)) == 2, (1:ncol(m)) == 3]),
30            identical(m[2,], m[(1:nrow(m)) == 2, ]),            identical(m[2,], m[(1:nrow(m)) == 2, ]),
31            identical(m[,3:4], m[, (1:4) >= 3]))            identical(m[,3:4], m[, (1:4) >= 3]))
32    
33  ## dimnames index (TODO)  ## dimnames indexing:
34    mn <- m
35  ## TODO: more --- particularly once we have "m > 10" working!  dimnames(mn) <- list(paste("r",letters[1:nrow(mn)],sep=""),
36                         LETTERS[1:ncol(mn)])
37    mn["rd", "D"]
38    stopifnot(identical(mn["rc", "D"], mn[3,4]), mn[3,4] == 24,
39              identical(mn[, "A"], mn[,1]), mn[,1] == 1:7,
40              identical(mn[c("re", "rb"), "B"], mn[c(5,2), 2])
41              )
42    
43    mo <- m
44    m[2,3] <- 100
45    m[1:2, 4] <- 200
46    m[, 1] <- -1
47    m[1:3,]
48    
49    m. <- as.matrix(m)
50    
51    ## m[ cbind(i,j) ] indexing:
52    ij <- cbind(1:6, 2:3)
53    stopifnot(identical(m[ij], m.[ij]))
54    
55    ## testing operations on logical Matrices rather more than indexing:
56    g10 <- m [ m > 10 ]
57    stopifnot(18 == length(g10))
58    stopifnot(10 == length(m[ m <= 10 ]))
59    sel <- (20 <  m) & (m <  150)
60    sel.<- (20 <  m.)& (m.<  150)
61    nsel <-(20 >= m) | (m >= 150)
62    (ssel <- as(sel, "sparseMatrix"))
63    stopifnot(is(sel, "lMatrix"), is(ssel, "lsparseMatrix"),
64              identical3(as.mat(sel.), as.mat(sel), as.mat(ssel)),
65              identical3(!sel, !ssel, nsel), # !<sparse> is typically dense
66              identical3(m[ sel],  m[ ssel], as.matrix(m)[as.matrix( ssel)]),
67              identical3(m[!sel],  m[!ssel], as.matrix(m)[as.matrix(!ssel)])
68              )
69    
70    ## more sparse Matrices --------------------------------------
 ### Sparse Matrices  
71    
72  m <- 1:800  m <- 1:800
73  set.seed(101) ; m[sample(800, 600)] <- 0  set.seed(101) ; m[sample(800, 600)] <- 0
# Line 47  Line 82 
82  mC[,1]  mC[,1]
83  mC[1:2,]  mC[1:2,]
84  mC[7, drop = FALSE]  mC[7, drop = FALSE]
85    assert.EQ.mat(mC[1:2,], mm[1:2,])
86    
87  mT[,c(2,4)]  ## *repeated* (aka 'duplicated') indices - did not work at all ...
88  mT[1,]  i <- rep(8:10,2)
89  mT[4, drop = FALSE]  j <- c(2:4, 4:3)
90    assert.EQ.mat(mC[i,], mm[i,])
91    assert.EQ.mat(mC[,j], mm[,j])
92    assert.EQ.mat(mC[i, 2:1], mm[i, 2:1])
93    assert.EQ.mat(mC[c(4,1,2:1), j], mm[c(4,1,2:1), j])
94    assert.EQ.mat(mC[i,j], mm[i,j])
95    set.seed(7)
96    for(n in 1:50) {
97        i <- sample(sample(nrow(mC), 7), 20, replace = TRUE)
98        j <- sample(sample(ncol(mC), 6), 17, replace = TRUE)
99        assert.EQ.mat(mC[i,j], mm[i,j])
100    }
101    
102    ##---- Symmetric indexing of symmetric Matrix ----------
103    m. <- mC; m.[, c(2, 7:12)] <- 0
104    validObject(S <- crossprod(add.simpleDimnames(m.) %% 100))
105    ss <- as(S, "matrix")
106    T <- as(S, "TsparseMatrix")
107    ## non-repeated indices:
108    i <- c(7:5, 2:4);assert.EQ.mat(T[i,i], ss[i,i])
109    N <- nrow(T)
110    set.seed(11)
111    for(n in 1:50) {
112        i <- sample(N, max(2, sample(N,1)), replace = FALSE)
113        validObject(Tii <- T[i,i])
114        stopifnot(is(Tii, "dsTMatrix"), # remained symmetric Tsparse
115                  identical(t(Tii), t(T)[i,i]))
116        assert.EQ.mat(Tii, ss[i,i])
117    }
118    
119    ## repeated ones ``the challenge'' (to do smartly):
120    j <- c(4, 4, 9, 12, 9, 4, 17, 3, 18, 4, 12, 18, 4, 9)
121    assert.EQ.mat(T[j,j], ss[j,j])
122    ## and another two sets  (a, A) &  (a., A.) :
123    a <- matrix(0, 6,6)
124    a[upper.tri(a)] <- (utr <- c(2, 0,-1, 0,0,5, 7,0,0,0, 0,0,-2,0,8))
125    ta <- t(a); ta[upper.tri(a)] <- utr; a <- t(ta)
126    diag(a) <- c(0,3,0,4,6,0)
127    A <- as(Matrix(a), "TsparseMatrix")
128    A. <- A
129    diag(A.) <- 10 * (1:6)
130    a. <- as(A., "matrix")
131    ## More testing {this was not working for a long time..}
132    set.seed(1)
133    for(n in 1:100) {
134        i <- sample(1:nrow(A), 3+2*rpois(1, lam=3), replace=TRUE)
135        Aii  <- A[i,i]
136        A.ii <- A.[i,i]
137        stopifnot(class(Aii) == class(A),
138                  class(A.ii) == class(A.))
139        assert.EQ.mat(Aii , a [i,i])
140        assert.EQ.mat(A.ii, a.[i,i])
141        assert.EQ.mat(T[i,i], ss[i,i])
142    }
143    
144    
145    stopifnot(all.equal(mC[,3], mm[,3]),
146              identical(mC[ij], mm[ij]))
147    assert.EQ.mat(mC[7, , drop=FALSE], mm[7, , drop=FALSE])
148    
149    stopifnot(dim(mC[numeric(0), ]) == c(0,20), # used to give warnings
150              dim(mC[, integer(0)]) == c(40,0),
151              identical(mC[, integer(0)], mC[, FALSE]),
152              identical(mC[7,  drop = FALSE],
153                        mC[7,, drop = FALSE]))
154    validObject(print(mT[,c(2,4)]))
155    stopifnot(all.equal(mT[2,], mm[2,]),
156              ## row or column indexing in combination with t() :
157              identical(mT[2,], t(mT)[,2]),
158              identical(mT[-2,], t(t(mT)[,-2])),
159              identical(mT[c(2,5),], t(t(mT)[,c(2,5)]))
160              )
161    assert.EQ.mat(mT[4,, drop = FALSE], mm[4,, drop = FALSE])
162  stopifnot(identical3(mm[,1], mC[,1], mT[,1]),  stopifnot(identical3(mm[,1], mC[,1], mT[,1]),
163            identical3(mm[3,], mC[3,], mT[3,]),            identical3(mm[3,], mC[3,], mT[3,]),
164            identical3(mT[2,3], mC[2,3], 0),            identical3(mT[2,3], mC[2,3], 0),
165            identical(mT[], mT),            identical(mT[], mT),
166            ## TODO: identical4() with  m[c(3,7), 2:4]            identical4(       mm[c(3,7), 2:4],  as.mat( m[c(3,7), 2:4]),
167            identical3(as(mC[c(3,7), 2:4],"matrix"), mm[c(3,7), 2:4],                       as.mat(mT[c(3,7), 2:4]), as.mat(mC[c(3,7), 2:4]))
168                       as(mT[c(3,7), 2:4],"matrix")))            )
169    
170    x.x <- crossprod(mC)
171    stopifnot(class(x.x) == "dsCMatrix",
172              class(x.x. <- round(x.x / 10000)) == "dsCMatrix",
173              identical(x.x[cbind(2:6, 2:6)],
174                        diag(x.x [2:6, 2:6])))
175    head(x.x.) # Note the *non*-structural 0's printed as "0"
176    tail(x.x., -3) # all but the first three lines
177    
178    lx.x <- as(x.x, "lsCMatrix") # FALSE only for "structural" 0
179    (l10 <- lx.x[1:10, 1:10])# "lsC"
180    (l3 <-  lx.x[1:3, ])
181    m.x <- as.mat(x.x) # as.mat() *drops* (NULL,NULL) dimnames
182    stopifnot(class(l10) == "lsCMatrix", # symmetric indexing -> symmetric !
183              identical(as.mat(lx.x), m.x != 0),
184              identical(as.logical(lx.x), as.logical(m.x)),
185              identical(as.mat(l10), m.x[1:10, 1:10] != 0),
186              identical(as.mat(l3 ), m.x[1:3, ] != 0)
187              )
188    
189    ##-- Sub*assignment* with repeated / duplicated index:
190    A <- Matrix(0,4,3) ; A[c(1,2,1), 2] <- 1 ; A
191    B <- A;              B[c(1,2,1), 2] <- 1:3; B; B. <- B
192    B.[3,] <- rbind(4:2)
193    diag(B.) <- 10 * diag(B.)
194    C <- B.; C[,2] <- C[,2];  C[1,] <- C[1,]; C[2:3,2:1] <- C[2:3,2:1]
195    stopifnot(identical(unname(as.matrix(A)),
196                        local({a <- matrix(0,4,3); a[c(1,2,1), 2] <-  1 ; a})),
197              identical(unname(as.matrix(B)),
198                        local({a <- matrix(0,4,3); a[c(1,2,1), 2] <- 1:3; a})),
199              identical(C, drop0(B.)))
200    
201    
202    ## used to fail
203    n <- 5 ## or much larger
204    sm <- new("dsTMatrix", i=as.integer(1),j=as.integer(1),
205              Dim=as.integer(c(n,n)), x = 1)
206    (cm <- as(sm, "CsparseMatrix"))
207    sm[2,]
208    stopifnot(sm[2,] == c(0:1, rep.int(0,ncol(sm)-2)),
209              sm[2,] == cm[2,],
210              sm[,3] == sm[3,],
211              all(sm[,-(1:3)] == t(sm[-(1:3),])), # all(<lge.>)
212              all(sm[,-(1:3)] == 0)
213              )
214    
215    m0 <- Diagonal(5)
216    stopifnot(identical(m0[2,], m0[,2]),
217              identical(m0[,1], c(1,0,0,0,0)))
218    ### Diagonal -- Sparse:
219    (m1 <- as(m0, "sparseMatrix"))  # dtTMatrix
220    (m2 <- as(m0, "CsparseMatrix")) # dtCMatrix (with an irrelevant warning)
221    m1g <- as(m1, "generalMatrix")
222    stopifnot(is(m1g, "dgTMatrix"))
223    assert.EQ.mat(m2[1:3,],    diag(5)[1:3,])
224    assert.EQ.mat(m2[,c(4,1)], diag(5)[,c(4,1)])
225    stopifnot(identical(m2[1:3,], as(m1[1:3,], "CsparseMatrix")),
226              identical(Matrix:::uniqTsparse(m1[, c(4,2)]),
227                        Matrix:::uniqTsparse(as(m2[, c(4,2)], "TsparseMatrix")))
228              )## failed in 0.9975-11
229    
230    (uTr <- new("dtTMatrix", Dim = c(3L,3L), diag="U"))
231    uTr[1,] <- 0
232    assert.EQ.mat(uTr, cbind(0, rbind(0,diag(2))))
233    
234    M <- m0; M[1,] <- 0
235    stopifnot(identical(M, Diagonal(x=c(0, rep(1,4)))))
236    M <- m0; M[,3] <- 3 ; M ; stopifnot(is(M, "sparseMatrix"), M[,3] == 3)
237    validObject(M)
238    M <- m0; M[1:3, 3] <- 0 ;M
239    T <- m0; T[1:3, 3] <- 10
240    stopifnot(identical(M, Diagonal(x=c(1,1, 0, 1,1))),
241              is(T, "triangularMatrix"), identical(T[,3], c(10,10,10,0,0)))
242    
243    M <- m1; M[1,] <- 0 ; M ; assert.EQ.mat(M, diag(c(0,rep(1,4))), tol=0)
244    M <- m1; M[,3] <- 3 ; stopifnot(is(M,"sparseMatrix"), M[,3] == 3)
245    validObject(M)
246    M <- m1; M[1:3, 3] <- 0 ;M
247    assert.EQ.mat(M, diag(c(1,1, 0, 1,1)), tol=0)
248    T <- m1; T[1:3, 3] <- 10; validObject(T)
249    stopifnot(is(T, "dtTMatrix"), identical(T[,3], c(10,10,10,0,0)))
250    
251    M <- m2; M[1,] <- 0 ; M ; assert.EQ.mat(M, diag(c(0,rep(1,4))), tol=0)
252    M <- m2; M[,3] <- 3 ; stopifnot(is(M,"sparseMatrix"), M[,3] == 3)
253    validObject(M)
254    M <- m2; M[1:3, 3] <- 0 ;M
255    assert.EQ.mat(M, diag(c(1,1, 0, 1,1)), tol=0)
256    T <- m2; T[1:3, 3] <- 10; validObject(T)
257    stopifnot(is(T, "dtCMatrix"), identical(T[,3], c(10,10,10,0,0)))
258    
259    
260    ## "Vector indices" -------------------
261    D <- Diagonal(6)
262    M <- as(D,"dgeMatrix")
263    m <- as(D,"matrix")
264    s <- as(D,"TsparseMatrix")
265    S <- as(s,"CsparseMatrix")
266    i <- c(3,1,6); v <- c(10,15,20)
267    ## (logical,value) which both are recycled:
268    L <- c(TRUE, rep(FALSE,8)) ; z <- c(50,99)
269    
270    ## vector subassignment, both with integer & logical
271    ## these now work correctly {though not very efficiently; hence warnings}
272    m[i] <- v # the role model: only first column is affected
273    M[i] <- v; assert.EQ.mat(M,m) # dge
274    D[i] <- v; assert.EQ.mat(D,m) # ddi -> dtT -> dgT
275    s[i] <- v; assert.EQ.mat(s,m) # dtT -> dgT
276    S[i] <- v; assert.EQ.mat(S,m); S # dtC -> dtT -> dgT -> dgC
277    ## logical
278    m[L] <- z
279    M[L] <- z; assert.EQ.mat(M,m)
280    D[L] <- z; assert.EQ.mat(D,m)
281    s[L] <- z; assert.EQ.mat(s,m)
282    S[L] <- z; assert.EQ.mat(S,m) ; S
283    
284    ## indexing [i]  vs  [i,] --- now ok
285    stopifnot(identical4(m[i], M[i], D[i], s[i]), identical(s[i],S[i]))
286    stopifnot(identical4(m[L], M[L], D[L], s[L]), identical(s[L],S[L]))
287    assert.EQ.mat(D[i,], m[i,])
288    assert.EQ.mat(M[i,], m[i,])
289    assert.EQ.mat(s[i,], m[i,])
290    assert.EQ.mat(S[i,], m[i,])
291    
292    assert.EQ.mat(D[,i], m[,i])
293    assert.EQ.mat(M[,i], m[,i])
294    assert.EQ.mat(s[,i], m[,i])
295    assert.EQ.mat(S[,i], m[,i])
296    
297    
298    ## --- negative indices ----------
299    mc <- mC[1:5, 1:7]
300    mt <- mT[1:5, 1:7]
301    ## sub matrix
302    assert.EQ.mat(mC[1:2, 0:3], mm[1:2, 0:3]) # test 0-index
303    stopifnot(identical(mc[-(3:5), 0:2], mC[1:2, 0:2]),
304              identical(mt[-(3:5), 0:2], mT[1:2, 0:2]),
305              identical(mC[2:3, 4],      mm[2:3, 4]))
306    assert.EQ.mat(mC[1:2,], mm[1:2,])
307    ## sub vector
308    stopifnot(identical4(mc[-(1:4), ], mC[5, 1:7],
309                         mt[-(1:4), ], mT[5, 1:7]))
310    stopifnot(identical4(mc[-(1:4), -(2:4)], mC[5, c(1,5:7)],
311                         mt[-(1:4), -(2:4)], mT[5, c(1,5:7)]))
312    
313    ## mixing of negative and positive must give error
314    assertError(mT[-1:1,])
315    
316    ## Sub *Assignment* ---- now works (partially):
317    mt0 <- mt
318    mt[1, 4] <- -99
319    mt[2:3, 1:6] <- 0
320    mt
321    m2 <- mt+mt
322    m2[1,4] <- -200
323    m2[c(1,3), c(5:6,2)] <- 1:6
324    stopifnot(m2[1,4] == -200,
325              as.vector(m2[c(1,3), c(5:6,2)]) == 1:6)
326    mt[,3] <- 30
327    mt[2:3,] <- 250
328    mt[1:5 %% 2 == 1, 3] <- 0
329    mt[3:1, 1:7 > 5] <- 0
330    mt
331    
332    tt <- as(mt,"matrix")
333    ii <- c(0,2,5)
334    jj <- c(2:3,5)
335    tt[ii, jj] <- 1:6 # 0 is just "dropped"
336    mt[ii, jj] <- 1:6
337    assert.EQ.mat(mt, tt)
338    
339    mt[1:5, 2:6]
340    as((mt0 - mt)[1:5,], "dsparseMatrix")# [1,5] and lines 2:3
341    
342    mt[c(2,4), ] <- 0; stopifnot(as(mt[c(2,4), ],"matrix") == 0)
343    mt[2:3, 4:7] <- 33
344    validObject(mt)
345    mt
346    
347    mc[1,4] <- -99 ; stopifnot(mc[1,4] == -99)
348    mc[1,4] <-  00 ; stopifnot(mc[1,4] ==  00)
349    mc[1,4] <- -99 ; stopifnot(mc[1,4] == -99)
350    mc[1:2,4:3] <- 4:1; stopifnot(as.matrix(mc[1:2,4:3]) == 4:1)
351    
352    mc[-1, 3] <- -2:1 # 0 should not be entered; 'value' recycled
353    mt[-1, 3] <- -2:1
354    stopifnot(mc@x != 0, mt@x != 0,
355              mc[-1,3] == -2:1, mt[-1,3] == -2:1) ## failed earlier
356    
357    mc0 <- mc
358    mt0 <- as(mc0, "TsparseMatrix")
359    m0  <- as(mc0, "matrix")
360    set.seed(1)
361    for(i in 1:50) {
362        mc <- mc0; mt <- mt0 ; m <- m0
363        ev <- 1:5 %% 2 == round(runif(1))# 0 or 1
364        j <- sample(ncol(mc), 1 + round(runif(1)))
365        nv <- rpois(sum(ev) * length(j), lambda = 1)
366        mc[ev, j] <- nv
367         m[ev, j] <- nv
368        mt[ev, j] <- nv
369        if(i %% 10 == 1) print(mc[ev,j, drop = FALSE])
370        stopifnot(as.vector(mc[ev, j]) == nv, ## failed earlier...
371                  as.vector(mt[ev, j]) == nv)
372        validObject(mc) ; assert.EQ.mat(mc, m)
373        validObject(mt) ; assert.EQ.mat(mt, m)
374    }
375    
376    mc # no longer has non-structural zeros
377    mc[ii, jj] <- 1:6
378    mc[c(2,5), c(3,5)] <- 3.2
379    validObject(mc)
380    m. <- mc
381    mc[4,] <- 0
382    mc
383    
384    S <- as(Diagonal(5),"sparseMatrix")
385    H <- Hilbert(9)
386    Hc <- as(round(H, 3), "dsCMatrix")# a sparse matrix with no 0 ...
387    (trH <- tril(Hc[1:5, 1:5]))
388    stopifnot(is(trH, "triangularMatrix"), trH@uplo == "L",
389              is(S, "triangularMatrix"))
390    
391    ## triangular assignment
392    ## the slick (but inefficient in case of sparse!) way to assign sub-diagonals:
393    ## equivalent to tmp <- `diag<-`(S[,-1], -2:1); S[,-1] <- tmp
394    ## which dispatches to (x="TsparseMatrix", i="missing",j="index", value="replValue")
395    diag(S[,-1]) <- -2:1 # used to give a wrong warning
396    S <- as(S,"triangularMatrix")
397    assert.EQ.mat(S, local({s <- diag(5); diag(s[,-1]) <- -2:1; s}))
398    
399    trH[c(1:2,4), c(2:3,5)] <- 0 # gave an *error* upto Jan.2008
400    trH[ lower.tri(trH) ] <- 0   # ditto, because of callNextMethod()
401    
402    m <- Matrix(0+1:28, nrow = 4)
403    m[-3,c(2,4:5,7)] <- m[ 3, 1:4] <- m[1:3, 6] <- 0
404    mT <- as(m, "dgTMatrix")
405    stopifnot(identical(mT[lower.tri(mT)],
406                        m [lower.tri(m) ]))
407    lM <- upper.tri(mT, diag=TRUE)
408    mT[lM] <- 0
409     m[lM] <- 0
410    assert.EQ.mat(mT, as(m,"matrix"))
411    mT[lM] <- -1:0
412     m[lM] <- -1:0
413    assert.EQ.mat(mT, as(m,"matrix"))
414    (mT <- drop0(mT))
415    
416    i <- c(1:2, 4, 6:7); j <- c(2:4,6)
417    H[i,j] <- 0
418    (H. <- round(as(H, "sparseMatrix"), 3)[ , 2:7])
419    Hc. <- Hc
420    Hc.[i,j] <- 0 ## now "works", but setting "non-structural" 0s
421    stopifnot(as.matrix(Hc.[i,j]) == 0)
422    Hc.[, 1:6]
423    
424    ## an example that failed for a long time
425    sy3 <- new("dsyMatrix", Dim = as.integer(c(2, 2)), x = c(14, -1, 2, -7))
426    validObject(dm <- kronecker(Diagonal(2), sy3))# now sparse with new kronecker
427    dm <- Matrix(as.matrix(dm))# -> "dsyMatrix"
428    (s2 <- as(dm, "sparseMatrix"))
429    validObject(st <- as(s2, "TsparseMatrix"))
430    stopifnot(is(s2, "symmetricMatrix"),
431              is(st, "symmetricMatrix"))
432    validObject(s.32  <- st[1:3,1:2]) ## 3 x 2 - and *not* dsTMatrix
433    validObject(s2.32 <- s2[1:3,1:2])
434    I <- c(1,4:3)
435    stopifnot(is(s2.32, "generalMatrix"),
436              is(s.32,  "generalMatrix"),
437              identical(as.mat(s.32), as.mat(s2.32)),
438              identical3(dm[1:3,-1], asD(s2[1:3,-1]), asD(st[1:3,-1])),
439              identical4(2, dm[4,3], s2[4,3], st[4,3]),
440              identical3(diag(dm), diag(s2), diag(st)),
441              is((cI <- s2[I,I]), "dsCMatrix"),
442              is((tI <- st[I,I]), "dsTMatrix"),
443              identical4(as.mat(dm)[I,I], as.mat(dm[I,I]), as.mat(tI), as.mat(cI))
444              )
445    
446    ## now sub-assign  and check for consistency
447    ## symmetric subassign should keep symmetry
448    st[I,I] <- 0; validObject(st); stopifnot(is(st,"symmetricMatrix"))
449    s2[I,I] <- 0; validObject(s2); stopifnot(is(s2,"symmetricMatrix"))
450    ##
451    m <- as.mat(st)
452     m[2:1,2:1] <- 4:1
453    st[2:1,2:1] <- 4:1
454    s2[2:1,2:1] <- 4:1
455    stopifnot(identical(m, as.mat(st)),
456              1:4 == as.vector(s2[1:2,1:2]),
457              identical(m, as.mat(s2)))
458    
459    ## now a slightly different situation for 's2' (had bug)
460    s2 <- as(dm, "sparseMatrix")
461    s2[I,I] <- 0; diag(s2)[2:3] <- -(1:2)
462    stopifnot(is(s2,"symmetricMatrix"), diag(s2) == c(0:-2,0))
463    t2 <- as(s2, "TsparseMatrix")
464    m <- as.mat(s2)
465    s2[2:1,2:1] <- 4:1
466    t2[2:1,2:1] <- 4:1
467     m[2:1,2:1] <- 4:1
468    assert.EQ.mat(t2, m)
469    assert.EQ.mat(s2, m)
470    ## and the same (for a different s2 !)
471    s2[2:1,2:1] <- 4:1
472    t2[2:1,2:1] <- 4:1
473    assert.EQ.mat(t2, m)# ok
474    assert.EQ.mat(s2, m)# failed in 0.9975-8
475    
476    
477    ## m[cbind(i,j)] <- value:
478    m.[ cbind(3:5, 1:3) ] <- 1:3
479    stopifnot(m.[3,1] == 1, m.[4,2] == 2)
480    x.x[ cbind(2:6, 2:6)] <- 12:16
481    validObject(x.x)
482    stopifnot(class(x.x) == "dsCMatrix",
483              12:16 == as.mat(x.x)[cbind(2:6, 2:6)])
484    (ne1 <- (mc - m.) != 0)
485    stopifnot(identical(ne1, 0 != abs(mc - m.)))
486    (ge <- m. >= mc) # contains "=" -> result is dense
487    ne. <- mc != m.  # was wrong (+ warning)
488    stopifnot(identical(!(m. < mc), m. >= mc),
489              identical(m. < mc, as(!ge, "sparseMatrix")),
490              identical(ne., drop0(ne1)))
491    
492    (M3 <- Matrix(upper.tri(matrix(, 3, 3)))) # ltC; indexing used to fail
493    T3 <- as(M3, "TsparseMatrix")
494    stopifnot(identical(drop(M3), M3),
495              identical4(drop(M3[,2, drop = FALSE]), M3[,2, drop = TRUE],
496                         drop(T3[,2, drop = FALSE]), T3[,2, drop = TRUE]),
497              is(T3, "triangularMatrix"),
498              !is(T3[,2, drop=FALSE], "triangularMatrix")
499              )
500    
501    M <- Diagonal(4); M[1,2] <- 2
502    M. <- as(M, "CsparseMatrix")
503    (R <- as(M., "RsparseMatrix"))
504    stopifnot(is(M, "triangularMatrix"),
505              is(M.,"triangularMatrix"),
506              is(R, "triangularMatrix"))
507    stopifnot(dim(M[2:3, FALSE]) == c(2,0),
508              dim(R[2:3, FALSE]) == c(2,0),
509              identical(M [2:3,TRUE], M [2:3,]),
510              identical(M.[2:3,TRUE], M.[2:3,]),
511              identical(R [2:3,TRUE], R [2:3,]),
512              dim(R[FALSE, FALSE]) == c(0,0))
513    
514    cat('Time elapsed: ', proc.time(),'\n') # for ``statistical reasons''

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