| spam {spam} | R Documentation |
This group of functions evaluates and coerces changes in class structure.
spam(x, nrow = 1, ncol = 1, eps = .Spam$eps) as.spam(x, eps = .Spam$eps) is.spam(x)
x |
is a matrix (of either dense or sparse form), a list, vector object or a distance object |
nrow |
number of rows of matrix |
ncol |
number of columns of matrix |
eps |
A tolerance parameter: elements of |
The functions spam and as.spam act like matrix
and as.matrix
to coerce an object to a sparse matrix object of class spam.
If x is a list, it should contain either two or three elements.
In case of the former, the list should contain a n by two
matrix of indicies (called ind) and the values.
In case of the latter, the list should contain three vectors
containing the row, column indices (called i and
j) and the values. In both cases partial matching is done.
In case there are several triplets with the same i, j,
the values are added.
eps should be at least as large as .Machine$double.eps.
A valid spam object.
is.spam returns TRUE if x is a spam object.
The zero matrix has the element zero stored in (1,1).
The functions do not test the presence of NA/NaN/Inf. Virtually
all call a Fortran routine with the NAOK=!.Spam$safemode[3]
argument, which defaults to FALSE resulting in an error.
Hence, the NaN do not always properly propagate through (i.e.
spam is not IEEE-754 compliant).
Reinhard Furrer
http://en.wikipedia.org/wiki/Sparse_matrix as a start.
SPAM for a general overview of the package;
spam.options for details about the safemode flag;
read.MM and foreign to create spam
matrices from MatrixMarket
files and from certain Matrix or SparseM formats.
# old message, do not loop, when you create a large sparse matrix
set.seed(13)
nz <- 128
ln <- nz^2
smat <- spam(0,ln,ln)
is <- sample(ln,nz)
js <- sample(ln,nz)
system.time(for (i in 1:nz) smat[is[i], js[i]] <- i)
system.time(smat[cbind(is,js)] <- 1:nz)
getClass("spam")
try(as.spam.numeric(NA))