Sparse Vector Classes

Description

Sparse Vector Classes: The virtual mother class "sparseVector" has the five actual daughter classes "dsparseVector", "isparseVector", "lsparseVector", "nsparseVector", and "zsparseVector", where we've mainly implemented methods for the d*, l* and n* ones.

Slots

length:

class "integer" - the length of the sparse vector.

i:

class "integer" - the (1-based) indices of the non-zero entries.

x:

(for all but "nsparseVector"): the non-zero entries. This is of class "numeric" for class "dsparseVector", "logical" for class "lsparseVector", etc.

Note that "nsparseVector"s have no x slot. Further, mainly for ease of method definitions, we've defined the class union (see setClassUnion) of all sparse vector classes which have an x slot, as class "xsparseVector".

Methods

length

signature(x = "sparseVector"): simply extracts the length slot.

show

signature(object = "sparseVector"): The show method for sparse vectors prints “structural” zeroes as "." using the non-exported prSpVector function which allows further customization such as replacing "." by " " (blank).

Note that options(max.print) will influence how many entries of large sparse vectors are printed at all.

as.vector

signature(x = "sparseVector", mode = "character") coerces sparse vectors to “regular”, i.e., atomic vectors. This is the same as as(x, "vector").

dim<-

signature(x = "sparseVector", value = "integer") coerces a sparse vector to a sparse Matrix, i.e., an object inheriting from sparseMatrix, of the appropriate dimension.

rep

signature(x = "sparseVector") repeat x, with the same argument list (x, times, length.out, each, ...) as the default method for rep().

Examples

getClass("sparseVector")
getClass("dsparseVector")
getClass("xsparseVector")# those with an 'x' slot

sx <- c(0,0,3, 3.2, 0,0,0,-3:1,0,0,2,0,0,5,0,0)
(ss <- as(sx, "sparseVector"))

ix <- as.integer(round(sx))
(is <- as(ix, "sparseVector"))
## an "isparseVector" (!)

## rep() works too:
rep(is, length.out= 25)

## Using `dim<-`  as in base R :
r <- ss
dim(r) <- c(4,5) # becomes a sparse Matrix:
r