| drop0 {Matrix} | R Documentation |
Returns a sparse matrix with no “explicit zeroes”, i.e., all
zero or FALSE entries are dropped from the explicitly indexed
matrix entries.
drop0(x, tol = 0, is.Csparse = NA)
x |
a Matrix, typically sparse, i.e., inheriting from
|
tol |
non-negative number to be used as tolerance for checking if an entry x[i,j] should be considered to be zero. |
is.Csparse |
logical indicating prior knowledge about the
“Csparseness” of |
a Matrix like x but with no explicit zeros, i.e.,
!any(x@x == 0), always inheriting from
CsparseMatrix.
When a sparse matrix is the result of matrix multiplications, you
may want to consider combining drop0() with
zapsmall(),
see the example.
spMatrix, class
sparseMatrix; nnzero
m <- spMatrix(10,20, i= 1:8, j=2:9, x = c(0:2,3:-1))
m
drop0(m)
## A larger example:
t5 <- new("dtCMatrix", Dim = c(5L, 5L), uplo = "L",
x = c(10, 1, 3, 10, 1, 10, 1, 10, 10),
i = c(0L,2L,4L, 1L, 3L,2L,4L, 3L, 4L),
p = c(0L, 3L, 5L, 7:9))
TT <- kronecker(t5, kronecker(kronecker(t5,t5), t5))
IT <- solve(TT)
I. <- TT %*% IT ; nnzero(I.) # 697 ( = 625 + 72 )
I.0 <- drop0(zapsmall(I.))
## which actually can be more efficiently achieved by
I.. <- drop0(I., tol = 1e-15)
stopifnot(all(I.0 == Diagonal(625)),
nnzero(I..) == 625)