COO_SparseArray objects
COO_SparseArray-class.RdThe COO_SparseArray class is a container for efficient in-memory representation of multidimensional sparse arrays. It uses the COO layout to represent the nonzero data internally.
A COO_SparseMatrix object is a COO_SparseArray object of 2 dimensions.
IMPORTANT NOTE: COO_SparseArray and COO_SparseMatrix objects are now superseded by the new and more efficient SVT_SparseArray and SVT_SparseMatrix objects.
Usage
## Constructor function:
COO_SparseArray(dim, nzcoo=NULL, nzdata=NULL, dimnames=NULL, check=TRUE)
## Getters (in addition to dim(), length(), and dimnames()):
nzcoo(x)
nzdata(x)Arguments
- dim
The dimensions (supplied as an integer vector) of the COO_SparseArray or COO_SparseMatrix object to construct.
- nzcoo
A matrix containing the array coordinates of the nonzero elements.
This must be an integer matrix of array coordinates like one returned by
base::arrayIndorS4Arrays::Lindex2Mindex, that is, a matrix withlength(dim)columns and where each row is an n-tuple representing the coordinates of an array element.- nzdata
A vector (atomic or list) of length
nrow(nzcoo)containing the nonzero elements.- dimnames
The dimnames of the object to construct. Must be
NULLor a list of length the number of dimensions. Each list element must be eitherNULLor a character vector along the corresponding dimension.- check
Should the object be validated upon construction?
- x
A COO_SparseArray or COO_SparseMatrix object.
Value
For
COO_SparseArray(): A COO_SparseArray or COO_SparseMatrix object.For
nzcoo(): A matrix with one column per dimension containing the array coordinates of the nonzero elements.For
nzdata(): A vector parallel tonzcoo(x)(i.e. with one element per row innzcoo(x)) containing the nonzero elements.
See also
The new SVT_SparseArray class for a replacement of of the COO_SparseArray class.
The SparseArray class for the virtual parent class of COO_SparseArray and SVT_SparseArray.
dgCMatrix-class and lgCMatrix-class in the Matrix package, for the de facto standard for sparse matrix representations in the R ecosystem.
base::arrayIndin the base package.S4Arrays::Lindex2Mindexin the S4Arrays package for an improved (faster) version ofbase::arrayInd.Ordinary array objects in base R.
Examples
## ---------------------------------------------------------------------
## EXAMPLE 1
## ---------------------------------------------------------------------
dim1 <- 5:3
nzcoo1 <- Lindex2Mindex(sample(60, 8), 5:3)
nzdata1 <- 11.11 * seq_len(nrow(nzcoo1))
coo1 <- COO_SparseArray(dim1, nzcoo1, nzdata1)
coo1
#> <5 x 4 x 3 SparseArray> of type "double" [nzcount=8 (13%)]:
#> ,,1
#> [,1] [,2] [,3] [,4]
#> [1,] 0.00 0.00 0.00 0.00
#> [2,] 0.00 0.00 33.33 0.00
#> [3,] 0.00 0.00 0.00 0.00
#> [4,] 0.00 0.00 0.00 0.00
#> [5,] 0.00 0.00 0.00 0.00
#>
#> ,,2
#> [,1] [,2] [,3] [,4]
#> [1,] 0.00 0.00 88.88 0.00
#> [2,] 0.00 0.00 0.00 44.44
#> [3,] 22.22 0.00 0.00 55.55
#> [4,] 0.00 0.00 0.00 0.00
#> [5,] 0.00 0.00 0.00 0.00
#>
#> ,,3
#> [,1] [,2] [,3] [,4]
#> [1,] 0.00 0.00 0.00 0.00
#> [2,] 0.00 66.66 0.00 0.00
#> [3,] 0.00 0.00 0.00 0.00
#> [4,] 0.00 0.00 0.00 0.00
#> [5,] 11.11 0.00 77.77 0.00
#>
nzcoo(coo1)
#> [,1] [,2] [,3]
#> [1,] 5 1 3
#> [2,] 3 1 2
#> [3,] 2 3 1
#> [4,] 2 4 2
#> [5,] 3 4 2
#> [6,] 2 2 3
#> [7,] 5 3 3
#> [8,] 1 3 2
nzdata(coo1)
#> [1] 11.11 22.22 33.33 44.44 55.55 66.66 77.77 88.88
type(coo1)
#> [1] "double"
sparsity(coo1)
#> [1] 0.8666667
as.array(coo1) # back to a dense representation
#> , , 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0 0 0.00 0
#> [2,] 0 0 33.33 0
#> [3,] 0 0 0.00 0
#> [4,] 0 0 0.00 0
#> [5,] 0 0 0.00 0
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.00 0 88.88 0.00
#> [2,] 0.00 0 0.00 44.44
#> [3,] 22.22 0 0.00 55.55
#> [4,] 0.00 0 0.00 0.00
#> [5,] 0.00 0 0.00 0.00
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.00 0.00 0.00 0
#> [2,] 0.00 66.66 0.00 0
#> [3,] 0.00 0.00 0.00 0
#> [4,] 0.00 0.00 0.00 0
#> [5,] 11.11 0.00 77.77 0
#>
#as.matrix(coo1) # error!
## ---------------------------------------------------------------------
## EXAMPLE 2
## ---------------------------------------------------------------------
m2 <- matrix(c(5:-2, rep.int(c(0L, 99L), 11)), ncol=6)
coo2 <- as(m2, "COO_SparseArray")
class(coo2)
#> [1] "COO_SparseMatrix"
#> attr(,"package")
#> [1] "SparseArray"
dim(coo2)
#> [1] 5 6
length(coo2)
#> [1] 30
nzcoo(coo2)
#> [,1] [,2]
#> [1,] 1 1
#> [2,] 2 1
#> [3,] 3 1
#> [4,] 4 1
#> [5,] 5 1
#> [6,] 2 2
#> [7,] 3 2
#> [8,] 5 2
#> [9,] 2 3
#> [10,] 4 3
#> [11,] 1 4
#> [12,] 3 4
#> [13,] 5 4
#> [14,] 2 5
#> [15,] 4 5
#> [16,] 1 6
#> [17,] 3 6
#> [18,] 5 6
nzdata(coo2)
#> [1] 5 4 3 2 1 -1 -2 99 99 99 99 99 99 99 99 99 99 99
type(coo2)
#> [1] "integer"
sparsity(coo2)
#> [1] 0.4
stopifnot(identical(as.matrix(coo2), m2))
t(coo2)
#> <6 x 5 SparseMatrix> of type "integer" [nzcount=18 (60%)]:
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 5 4 3 2 1
#> [2,] 0 -1 -2 0 99
#> [3,] 0 99 0 99 0
#> [4,] 99 0 99 0 99
#> [5,] 0 99 0 99 0
#> [6,] 99 0 99 0 99
stopifnot(identical(as.matrix(t(coo2)), t(as.matrix(coo2))))
## ---------------------------------------------------------------------
## COERCION FROM/TO dg[C|R]Matrix OR lg[C|R]Matrix OBJECTS
## ---------------------------------------------------------------------
## dg[C|R]Matrix and lg[C|R]Matrix objects are defined in the Matrix
## package.
## dgCMatrix/dgRMatrix:
M2C <- as(coo2, "dgCMatrix")
stopifnot(identical(M2C, as(m2, "dgCMatrix")))
coo2C <- as(M2C, "COO_SparseArray")
## 'coo2C' is the same as 'coo2' except that 'nzdata(coo2C)' has
## type "double" instead of "integer":
stopifnot(all.equal(coo2, coo2C))
typeof(nzdata(coo2C)) # double
#> [1] "double"
typeof(nzdata(coo2)) # integer
#> [1] "integer"
M2R <- as(coo2, "dgRMatrix")
stopifnot(identical(M2R, as(m2, "dgRMatrix")))
coo2R <- as(M2R, "COO_SparseArray")
stopifnot(all.equal(as.matrix(coo2), as.matrix(coo2R)))
## lgCMatrix/lgRMatrix:
m3 <- m2 == 99 # logical matrix
coo3 <- as(m3, "COO_SparseArray")
class(coo3)
#> [1] "COO_SparseMatrix"
#> attr(,"package")
#> [1] "SparseArray"
type(coo3)
#> [1] "logical"
M3C <- as(coo3, "lgCMatrix")
stopifnot(identical(M3C, as(m3, "lgCMatrix")))
coo3C <- as(M3C, "COO_SparseArray")
identical(as.matrix(coo3), as.matrix(coo3C))
#> [1] TRUE
M3R <- as(coo3, "lgRMatrix")
#stopifnot(identical(M3R, as(m3, "lgRMatrix")))
coo3R <- as(M3R, "COO_SparseArray")
identical(as.matrix(coo3), as.matrix(coo3R))
#> [1] TRUE
## ---------------------------------------------------------------------
## A BIG COO_SparseArray OBJECT
## ---------------------------------------------------------------------
nzcoo4 <- cbind(sample(25000, 600000, replace=TRUE),
sample(195000, 600000, replace=TRUE))
nzdata4 <- runif(600000)
coo4 <- COO_SparseArray(c(25000, 195000), nzcoo4, nzdata4)
coo4
#> <25000 x 195000 SparseMatrix> of type "double" [nzcount=599974 (0.012%)]:
#> [,1] [,2] [,3] ... [,194999] [,195000]
#> [1,] 0 0 0 . 0 0
#> [2,] 0 0 0 . 0 0
#> [3,] 0 0 0 . 0 0
#> [4,] 0 0 0 . 0 0
#> [5,] 0 0 0 . 0 0
#> ... . . . . . .
#> [24996,] 0 0 0 . 0 0
#> [24997,] 0 0 0 . 0 0
#> [24998,] 0 0 0 . 0 0
#> [24999,] 0 0 0 . 0 0
#> [25000,] 0 0 0 . 0 0
sparsity(coo4)
#> [1] 0.9998769