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Diff of /pkg/tests/indexing.R

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revision 1665, Fri Nov 3 23:18:07 2006 UTC revision 2096, Fri Dec 7 17:44:44 2007 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    
# Line 6  Line 6 
6    
7  ### Dense Matrices  ### Dense Matrices
8    
9  m <- Matrix(1:28, nrow = 7)  m <- Matrix(1:28 +0, nrow = 7)
10  validObject(m) ; m@x <- as.double(m@x) ; validObject(m)  validObject(m)
11  stopifnot(identical(m, m[]),  stopifnot(identical(m, m[]),
12            identical(m[2, 3],  16), # simple number            identical(m[2, 3],  16), # simple number
13            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
# Line 44  Line 44 
44  m[, 1] <- -1  m[, 1] <- -1
45  m[1:3,]  m[1:3,]
46    
 ## testing operations on logical Matrices rather more than indexing:  
47  m. <- as.matrix(m)  m. <- as.matrix(m)
48    
49    ## m[ cbind(i,j) ] indexing:
50    ij <- cbind(1:6, 2:3)
51    stopifnot(identical(m[ij], m.[ij]))
52    
53    ## testing operations on logical Matrices rather more than indexing:
54  g10 <- m [ m > 10 ]  g10 <- m [ m > 10 ]
55  stopifnot(18 == length(g10))  stopifnot(18 == length(g10))
56  stopifnot(10 == length(m[ m <= 10 ]))  stopifnot(10 == length(m[ m <= 10 ]))
# Line 76  Line 81 
81  mC[1:2,]  mC[1:2,]
82  mC[7,  drop = FALSE]  mC[7,  drop = FALSE]
83  assert.EQ.mat(mC[1:2,], mm[1:2,])  assert.EQ.mat(mC[1:2,], mm[1:2,])
84  stopifnot(all.equal(mC[,3],   mm[,3]))  
85    ## *repeated* (aka 'duplicated') indices - did not work at all ...
86    i <- rep(8:10,2)
87    j <- c(2:4, 4:3)
88    assert.EQ.mat(mC[i,], mm[i,])
89    assert.EQ.mat(mC[,j], mm[,j])
90    assert.EQ.mat(mC[i, 2:1], mm[i, 2:1])
91    assert.EQ.mat(mC[c(4,1,2:1), j], mm[c(4,1,2:1), j])
92    assert.EQ.mat(mC[i,j], mm[i,j])
93    set.seed(7)
94    for(n in 1:50) {
95        i <- sample(sample(nrow(mC), 7), 20, replace = TRUE)
96        j <- sample(sample(ncol(mC), 6), 17, replace = TRUE)
97        assert.EQ.mat(mC[i,j], mm[i,j])
98    }
99    
100    ##---- Symmetric indexing of symmetric Matrix ----------
101    m. <- mC; m.[, c(2, 7:12)] <- 0
102    validObject(S <- crossprod(add.simpleDimnames(m.) %% 100))
103    ss <- as(S, "matrix")
104    T <- as(S, "TsparseMatrix")
105    ## non-repeated indices:
106    i <- c(7:5, 2:4);assert.EQ.mat(T[i,i], ss[i,i])
107    N <- nrow(T)
108    set.seed(11)
109    for(n in 1:50) {
110        i <- sample(N, max(2, sample(N,1)), replace = FALSE)
111        validObject(Tii <- T[i,i])
112        stopifnot(is(Tii, "dsTMatrix"), # remained symmetric Tsparse
113                  identical(t(Tii), t(T)[i,i]))
114        assert.EQ.mat(Tii, ss[i,i])
115    }
116    
117    ## repeated ones ``the challenge'' (to do smartly):
118    j <- c(4, 4, 9, 12, 9, 4, 17, 3, 18, 4, 12, 18, 4, 9)
119    assert.EQ.mat(T[j,j], ss[j,j])
120    ## and another two sets  (a, A) &  (a., A.) :
121    a <- matrix(0, 6,6)
122    a[upper.tri(a)] <- (utr <- c(2, 0,-1, 0,0,5, 7,0,0,0, 0,0,-2,0,8))
123    ta <- t(a); ta[upper.tri(a)] <- utr; a <- t(ta)
124    diag(a) <- c(0,3,0,4,6,0)
125    A <- as(Matrix(a), "TsparseMatrix")
126    A. <- A
127    diag(A.) <- 10 * (1:6)
128    a. <- as(A., "matrix")
129    ## More testing {this was not working for a long time..}
130    set.seed(1)
131    for(n in 1:100) {
132        i <- sample(1:nrow(A), 3+2*rpois(1, lam=3), replace=TRUE)
133        Aii  <- A[i,i]
134        A.ii <- A.[i,i]
135        stopifnot(class(Aii) == class(A),
136                  class(A.ii) == class(A.))
137        assert.EQ.mat(Aii , a [i,i])
138        assert.EQ.mat(A.ii, a.[i,i])
139        assert.EQ.mat(T[i,i], ss[i,i])
140    }
141    
142    
143    stopifnot(all.equal(mC[,3], mm[,3]),
144              identical(mC[ij], mm[ij]))
145  assert.EQ.mat(mC[7, , drop=FALSE], mm[7, , drop=FALSE])  assert.EQ.mat(mC[7, , drop=FALSE], mm[7, , drop=FALSE])
146    
147  stopifnot(dim(mC[numeric(0), ]) == c(0,20), # used to give warnings  stopifnot(dim(mC[numeric(0), ]) == c(0,20), # used to give warnings
# Line 102  Line 167 
167    
168  x.x <- crossprod(mC)  x.x <- crossprod(mC)
169  stopifnot(class(x.x) == "dsCMatrix",  stopifnot(class(x.x) == "dsCMatrix",
170            class(x.x. <- round(x.x / 10000)) == "dsCMatrix")            class(x.x. <- round(x.x / 10000)) == "dsCMatrix",
171              identical(x.x[cbind(2:6, 2:6)],
172                        diag(x.x [2:6, 2:6])))
173  head(x.x.) # Note the *non*-structural 0's printed as "0"  head(x.x.) # Note the *non*-structural 0's printed as "0"
174  tail(x.x., -3) # all but the first three lines  tail(x.x., -3) # all but the first three lines
175    
# Line 117  Line 184 
184            identical(as.mat(l3 ), m.x[1:3, ] != 0)            identical(as.mat(l3 ), m.x[1:3, ] != 0)
185            )            )
186    
187    ##-- Sub*assignment* with repeated / duplicated index:
188    A <- Matrix(0,4,3) ; A[c(1,2,1), 2] <- 1 ; A
189    B <- A;              B[c(1,2,1), 2] <- 1:3; B; B. <- B
190    B.[3,] <- rbind(4:2)
191    diag(B.) <- 10 * diag(B.)
192    C <- B.; C[,2] <- C[,2];  C[1,] <- C[1,]; C[2:3,2:1] <- C[2:3,2:1]
193    stopifnot(identical(unname(as.matrix(A)),
194                        local({a <- matrix(0,4,3); a[c(1,2,1), 2] <-  1 ; a})),
195              identical(unname(as.matrix(B)),
196                        local({a <- matrix(0,4,3); a[c(1,2,1), 2] <- 1:3; a})),
197              identical(C, drop0(B.)))
198    
199    
200    ## used to fail
201    n <- 5 ## or much larger
202    sm <- new("dsTMatrix", i=as.integer(1),j=as.integer(1),
203              Dim=as.integer(c(n,n)), x = 1)
204    (cm <- as(sm, "CsparseMatrix"))
205    sm[2,]
206    stopifnot(sm[2,] == c(0:1, rep.int(0,ncol(sm)-2)),
207              sm[2,] == cm[2,],
208              sm[,3] == sm[3,],
209              all(sm[,-(1:3)] == t(sm[-(1:3),])), # all(<lge.>)
210              all(sm[,-(1:3)] == 0)
211              )
212    
213    ### Diagonal -- Sparse:
214    m0 <- Diagonal(5)
215    (m1 <- as(m0, "sparseMatrix"))  # dtTMatrix
216    (m2 <- as(m0, "CsparseMatrix")) # dtCMatrix (with an irrelevant warning)
217    m1g <- as(m1, "generalMatrix")
218    stopifnot(is(m1g, "dgTMatrix"))
219    assert.EQ.mat(m2[1:3,],    diag(5)[1:3,])
220    assert.EQ.mat(m2[,c(4,1)], diag(5)[,c(4,1)])
221    stopifnot(identical(m2[1:3,], as(m1[1:3,], "CsparseMatrix")),
222              identical(Matrix:::uniqTsparse(m1[, c(4,2)]),
223                        Matrix:::uniqTsparse(as(m2[, c(4,2)], "TsparseMatrix")))
224              )## failed in 0.9975-11
225    
226    M <- m0; M[1,] <- 0
227    stopifnot(identical(M, Diagonal(x=c(0, rep(1,4)))))
228    M <- m0; M[,3] <- 3 ; M ; stopifnot(is(M, "sparseMatrix"), M[,3] == 3)
229    validObject(M)
230    M <- m0; M[1:3, 3] <- 0 ;M
231    T <- m0; T[1:3, 3] <- 10
232    stopifnot(identical(M, Diagonal(x=c(1,1, 0, 1,1))),
233              is(T, "triangularMatrix"), identical(T[,3], c(10,10,10,0,0)))
234    
235    M <- m1; M[1,] <- 0 ; M ; assert.EQ.mat(M, diag(c(0,rep(1,4))), tol=0)
236    M <- m1; M[,3] <- 3 ; stopifnot(is(M,"sparseMatrix"), M[,3] == 3)
237    validObject(M)
238    M <- m1; M[1:3, 3] <- 0 ;M
239    assert.EQ.mat(M, diag(c(1,1, 0, 1,1)), tol=0)
240    T <- m1; T[1:3, 3] <- 10; validObject(T)
241    stopifnot(is(T, "dtTMatrix"), identical(T[,3], c(10,10,10,0,0)))
242    
243    M <- m2; M[1,] <- 0 ; M ; assert.EQ.mat(M, diag(c(0,rep(1,4))), tol=0)
244    M <- m2; M[,3] <- 3 ; stopifnot(is(M,"sparseMatrix"), M[,3] == 3)
245    validObject(M)
246    M <- m2; M[1:3, 3] <- 0 ;M
247    assert.EQ.mat(M, diag(c(1,1, 0, 1,1)), tol=0)
248    T <- m2; T[1:3, 3] <- 10; validObject(T)
249    stopifnot(is(T, "dtCMatrix"), identical(T[,3], c(10,10,10,0,0)))
250    
251    
252    ## "Vector indices" --- now ``work'' but wrongly __FIXME__
253    i <- c(1,3,6); v <- c(10,15,20)
254    D <- Diagonal(6)
255    m <- as(D,"matrix")
256    s <- as(D,"sparseMatrix")
257    
258    D[i] <- v; D
259    s[i] <- v; s
260    m[i] <- v; m
261    
262    
263  ## --- negative indices ----------  ## --- negative indices ----------
264  mc <- mC[1:5, 1:7]  mc <- mC[1:5, 1:7]
# Line 175  Line 317 
317  mc[-1, 3] <- -2:1 # 0 should not be entered; 'value' recycled  mc[-1, 3] <- -2:1 # 0 should not be entered; 'value' recycled
318  mt[-1, 3] <- -2:1  mt[-1, 3] <- -2:1
319  stopifnot(mc@x != 0, mt@x != 0,  stopifnot(mc@x != 0, mt@x != 0,
320            mc[-1,3] == -2:1, mt[-1,3] == -2:1) ##--> BUG -- fixed            mc[-1,3] == -2:1, mt[-1,3] == -2:1) ## failed earlier
321    
322  ev <- 1:5 %% 2 == 0  mc0 <- mc
323  mc[ev, 3] <- 0:1  mt0 <- as(mc0, "TsparseMatrix")
324  if(FALSE)## FIXME  m0  <- as(mc0, "matrix")
325   stopifnot(mc[ev, 3] == 0:1) ##-> BUG  {very peculiar; the 2nd time it works ...}  set.seed(1)
326  validObject(mc)  for(i in 1:50) {
327  mc # now shows a non-structural zeros      mc <- mc0; mt <- mt0 ; m <- m0
328        ev <- 1:5 %% 2 == round(runif(1))# 0 or 1
329        j <- sample(ncol(mc), 1 + round(runif(1)))
330        nv <- rpois(sum(ev) * length(j), lambda = 1)
331        mc[ev, j] <- nv
332         m[ev, j] <- nv
333        mt[ev, j] <- nv
334        if(i %% 10 == 1) print(mc[ev,j, drop = FALSE])
335        stopifnot(as.vector(mc[ev, j]) == nv, ## failed earlier...
336                  as.vector(mt[ev, j]) == nv)
337        validObject(mc) ; assert.EQ.mat(mc, m)
338        validObject(mt) ; assert.EQ.mat(mt, m)
339    }
340    
341    mc # no longer has non-structural zeros
342  mc[ii, jj] <- 1:6  mc[ii, jj] <- 1:6
343  mc[c(2,5), c(3,5)] <- 3.2  mc[c(2,5), c(3,5)] <- 3.2
344  validObject(mc)  validObject(mc)
# Line 203  Line 359 
359  stopifnot(as.matrix(Hc.[i,j]) == 0)  stopifnot(as.matrix(Hc.[i,j]) == 0)
360  Hc.[, 1:6]  Hc.[, 1:6]
361    
362    ## an example that failed for a long time
363    sy3 <- new("dsyMatrix", Dim = as.integer(c(2, 2)), x = c(14, -1, 2, -7))
364    validObject(dm <- kronecker(Diagonal(2), sy3))# now sparse with new kronecker
365    dm <- Matrix(as.matrix(dm))# -> "dsyMatrix"
366    (s2 <- as(dm, "sparseMatrix"))
367    validObject(st <- as(s2, "TsparseMatrix"))
368    stopifnot(is(s2, "symmetricMatrix"),
369              is(st, "symmetricMatrix"))
370    validObject(s.32  <- st[1:3,1:2]) ## 3 x 2 - and *not* dsTMatrix
371    validObject(s2.32 <- s2[1:3,1:2])
372    I <- c(1,4:3)
373    stopifnot(is(s2.32, "generalMatrix"),
374              is(s.32,  "generalMatrix"),
375              identical(as.mat(s.32), as.mat(s2.32)),
376              identical3(dm[1:3,-1], asD(s2[1:3,-1]), asD(st[1:3,-1])),
377              identical4(2, dm[4,3], s2[4,3], st[4,3]),
378              identical3(diag(dm), diag(s2), diag(st)),
379              is((cI <- s2[I,I]), "dsCMatrix"),
380              is((tI <- st[I,I]), "dsTMatrix"),
381              identical4(as.mat(dm)[I,I], as.mat(dm[I,I]), as.mat(tI), as.mat(cI))
382              )
383    
384    ## now sub-assign  and check for consistency
385    ## symmetric subassign should keep symmetry
386    st[I,I] <- 0; validObject(st); stopifnot(is(st,"symmetricMatrix"))
387    s2[I,I] <- 0; validObject(s2); stopifnot(is(s2,"symmetricMatrix"))
388    ##
389    m <- as.mat(st)
390     m[2:1,2:1] <- 4:1
391    st[2:1,2:1] <- 4:1
392    s2[2:1,2:1] <- 4:1
393    stopifnot(identical(m, as.mat(st)),
394              1:4 == as.vector(s2[1:2,1:2]),
395              identical(m, as.mat(s2)))
396    
397    ## now a slightly different situation for 's2' (had bug)
398    s2 <- as(dm, "sparseMatrix")
399    s2[I,I] <- 0; diag(s2)[2:3] <- -(1:2)
400    stopifnot(is(s2,"symmetricMatrix"), diag(s2) == c(0:-2,0))
401    t2 <- as(s2, "TsparseMatrix")
402    m <- as.mat(s2)
403    s2[2:1,2:1] <- 4:1
404    t2[2:1,2:1] <- 4:1
405     m[2:1,2:1] <- 4:1
406    assert.EQ.mat(t2, m)
407    assert.EQ.mat(s2, m)
408    ## and the same (for a different s2 !)
409    s2[2:1,2:1] <- 4:1
410    t2[2:1,2:1] <- 4:1
411    assert.EQ.mat(t2, m)# ok
412    assert.EQ.mat(s2, m)# failed in 0.9975-8
413    
414    
415    ## m[cbind(i,j)] <- value:
416    m.[ cbind(3:5, 1:3) ] <- 1:3
417    stopifnot(m.[3,1] == 1, m.[4,2] == 2)
418    x.x[ cbind(2:6, 2:6)] <- 12:16
419    validObject(x.x)
420    stopifnot(class(x.x) == "dsCMatrix",
421              12:16 == as.mat(x.x)[cbind(2:6, 2:6)])
422    (ne1 <- (mc - m.) != 0)
423    stopifnot(identical(ne1, 0 != abs(mc - m.)))
424    (ge <- m. >= mc) # contains "=" -> result is dense
425    ne. <- mc != m.  # was wrong (+ warning)
426    stopifnot(identical(!(m. < mc), m. >= mc),
427              identical(m. < mc, as(!ge, "sparseMatrix")),
428              identical(ne., Matrix:::drop0(ne1)))
429    
430    (M3 <- Matrix(upper.tri(matrix(, 3, 3)))) # ltC; indexing used to fail
431    T3 <- as(M3, "TsparseMatrix")
432    stopifnot(identical(drop(M3), M3),
433              identical4(drop(M3[,2, drop = FALSE]), M3[,2, drop = TRUE],
434                         drop(T3[,2, drop = FALSE]), T3[,2, drop = TRUE]),
435              is(T3, "triangularMatrix"),
436              !is(T3[,2, drop=FALSE], "triangularMatrix")
437              )
438    
439  cat('Time elapsed: ', proc.time(),'\n') # for ``statistical reasons''  cat('Time elapsed: ', proc.time(),'\n') # for ``statistical reasons''

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