Class

The spam class is a representation of sparse matrices.

Objects from the Class

Objects can be created by calls of the form new("spam", entries, colindices, rowpointes, dimension). The standard "old Yale sparse format" is used to store sparse matrices.
The matrix x is stored in row form. The first element of row i is x@rowpointers[i]. The length of row i is determined by x@rowpointers[i+1]-x@rowpointers[i]. The column indices of x are stored in the x@colindices vector. The column index for element x@entries[k] is x@colindices[k].

Slots

entries:: Object of class "numeric" contains the nonzero values.
colindices:: Object of class "integer" ordered indices of the nonzero values.
rowpointers:: Object of class "integer" pointer to the beginning of each row in the arrays entries and colindices.
dimension:: Object of class "integer" specifying the dimension of the matrix.

Methods

as.matrix: signature(x = "spam"): transforming a sparse matrix into a regular matrix.
as.vector: signature(x = "spam"): transforming a sparse matrix into a vector (dependings on structurebased) see as.vector.spam for details.
as.spam: signature(x = "spam"): cleaning of a sparse matrix.
[<-: signature(x = "spam", i,j, value): assigning a sparse matrix. The negative vectors are not implemented yet.
[: signature(x = "spam", i, j): subsetting a sparse matrix. The negative vectors are not implemented yet.
%*%: signature(x, y): matrix multiplication, all combinations of sparse with full matrices or vectors are implemented.
c: signature(x = "spam"): vectorizes the sparse matrix and takes account of the zeros. Hence the lenght of the result is prod(dim(x)).
cbind: signature(x = "spam"): binds sparse matrices, see cbind for details.
chol: signature(x = "spam"): see chol for details.
diag: signature(x = "spam"): see diag for details.
dim<-: signature(x = "spam"): rearranges the matrix to reflect a new dimension.
dim: signature(x = "spam"): gives the dimension of the sparse matrix.
pad<-: signature(x = "spam"): truncates or augments the matrix see dim for details.
image: signature(x = "spam"): see image for details.
display: signature(x = "spam"): see display for details.
length<-: signature(x = "spam"): Is not implemented and causes an error.
length: signature(x = "spam"): gives the number of non-zero elements.
lower.tri: signature(x = "spam"): see lower.tri for details.
Math: signature(x = "spam"): see Math for details.
Math2: signature(x = "spam"): see Math2 for details.
norm: signature(x = "spam"): calculates the norm of a matrix.
plot: signature(x = "spam", y): same functionality as the ordinary plot.
print: signature(x = "spam"): see print for details.
rbind: signature(x = "spam"): binds sparse matrices, see cbind for details.
solve: signature(a = "spam"): see solve for details.
summary: signature(object = "spam"): small summary statement of the sparse matrix.
Summary: signature(x = "spam"): All functions of the Summary class (like min, max, range...) operate on the vector x@entries and return the result thereof. See Examples or Summary for details.
t: signature(x = "spam"): transpose of a sparse matrix.
upper.tri: signature(x = "spam"): see lower.tri for details.

Details

The compressed sparse row (CSR) format is often described with the vectors a, ia, ja. To be a bit more comprehensive, we have chosen longer slot names.

Note

The slots colindices and rowpointers are tested for proper integer assignments. This is not true for entries.

Author

Reinhard Furrer, some of the Fortran code is based on A. George, J. Liu, E. S. Ng, B.W Peyton and Y. Saad (alphabetical)

Examples

showMethods("as.spam")
#> Function: as.spam (package spam)
#> x="ANY"
#> x="dist"
#> x="integer"
#>     (inherited from: x="numeric")
#> x="list"
#> x="matrix"
#> x="numeric"
#> x="spam"
#> x="spam.chol.NgPeyton"
#> 


smat <- diag.spam(runif(15))
range(smat)
#> [1] 0.000000 0.785562
cos(smat)
#>   [1] 0.9464291 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#>   [8] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#>  [15] 1.0000000 1.0000000 0.7069909 1.0000000 1.0000000 1.0000000 1.0000000
#>  [22] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#>  [29] 1.0000000 1.0000000 1.0000000 1.0000000 0.9231173 1.0000000 1.0000000
#>  [36] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#>  [43] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 0.8883847
#>  [50] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#>  [57] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#>  [64] 1.0000000 0.9847193 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#>  [71] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#>  [78] 1.0000000 1.0000000 1.0000000 0.7696644 1.0000000 1.0000000 1.0000000
#>  [85] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#>  [92] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 0.9243212 1.0000000
#>  [99] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> [106] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> [113] 0.8929796 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> [120] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> [127] 1.0000000 1.0000000 0.9543847 1.0000000 1.0000000 1.0000000 1.0000000
#> [134] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> [141] 1.0000000 1.0000000 1.0000000 1.0000000 0.9953006 1.0000000 1.0000000
#> [148] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> [155] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 0.9979787
#> [162] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> [169] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> [176] 1.0000000 0.8867794 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> [183] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> [190] 1.0000000 1.0000000 1.0000000 0.9471237 1.0000000 1.0000000 1.0000000
#> [197] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> [204] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 0.9719185 1.0000000
#> [211] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> [218] 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000 1.0000000
#> [225] 0.9857374
#> Class 'spam' (32-bit)

Class "spam"