nsparseMatrix-classes | R Documentation |

The `nsparseMatrix`

class is a virtual class of sparse
*“pattern”* matrices, i.e., binary matrices conceptually
with `TRUE`

/`FALSE`

entries. Only the positions of the
elements that are `TRUE`

are stored.

These can be stored in the “triplet” form
(`TsparseMatrix`

, subclasses `ngTMatrix`

,
`nsTMatrix`

, and `ntTMatrix`

which really contain pairs, not
triplets) or in compressed column-oriented form (class
`CsparseMatrix`

, subclasses `ngCMatrix`

,
`nsCMatrix`

, and `ntCMatrix`

) or–*rarely*–in
compressed row-oriented form (class `RsparseMatrix`

,
subclasses `ngRMatrix`

, `nsRMatrix`

, and `ntRMatrix`

).
The second letter in the name of these non-virtual classes indicates
`g`

eneral, `s`

ymmetric, or `t`

riangular.

Objects can be created by calls of the form ```
new("ngCMatrix",
...)
```

and so on. More frequently objects are created by coercion of
a numeric sparse matrix to the pattern form for use in
the symbolic analysis phase
of an algorithm involving sparse matrices. Such algorithms often
involve two phases: a symbolic phase wherein the positions of the
non-zeros in the result are determined and a numeric phase wherein the
actual results are calculated. During the symbolic phase only the
positions of the non-zero elements in any operands are of interest,
hence numeric sparse matrices can be treated as sparse pattern
matrices.

`uplo`

:Object of class

`"character"`

. Must be either "U", for upper triangular, and "L", for lower triangular. Present in the triangular and symmetric classes but not in the general class.`diag`

:Object of class

`"character"`

. Must be either`"U"`

, for unit triangular (diagonal is all ones), or`"N"`

for non-unit. The implicit diagonal elements are not explicitly stored when`diag`

is`"U"`

. Present in the triangular classes only.`p`

:Object of class

`"integer"`

of pointers, one for each column (row), to the initial (zero-based) index of elements in the column. Present in compressed column-oriented and compressed row-oriented forms only.`i`

:Object of class

`"integer"`

of length nnzero (number of non-zero elements). These are the row numbers for each TRUE element in the matrix. All other elements are FALSE. Present in triplet and compressed column-oriented forms only.`j`

:Object of class

`"integer"`

of length nnzero (number of non-zero elements). These are the column numbers for each TRUE element in the matrix. All other elements are FALSE. Present in triplet and compressed row-oriented forms only.`Dim`

:Object of class

`"integer"`

- the dimensions of the matrix.

- coerce
`signature(from = "dgCMatrix", to = "ngCMatrix")`

, and many similar ones; typically you should coerce to`"nsparseMatrix"`

(or`"nMatrix"`

). Note that coercion to a sparse pattern matrix records all the potential non-zero entries, i.e., explicit (“non-structural”) zeroes are coerced to`TRUE`

, not`FALSE`

, see the example.- t
`signature(x = "ngCMatrix")`

: returns the transpose of`x`

- which
`signature(x = "lsparseMatrix")`

, semantically equivalent to base function`which(x, arr.ind)`

; for details, see the`lMatrix`

class documentation.

the class `dgCMatrix`

(m <- Matrix(c(0,0,2:0), 3,5, dimnames=list(LETTERS[1:3],NULL))) ## ``extract the nonzero-pattern of (m) into an nMatrix'': nm <- as(m, "nsparseMatrix") ## -> will be a "ngCMatrix" str(nm) # no 'x' slot nnm <- !nm # no longer sparse ## consistency check: stopifnot(xor(as( nm, "matrix"), as(nnm, "matrix"))) ## low-level way of adding "non-structural zeros" : nnm <- as(nnm, "lsparseMatrix") # "lgCMatrix" nnm@x[2:4] <- c(FALSE, NA, NA) nnm as(nnm, "nMatrix") # NAs *and* non-structural 0 |---> 'TRUE' data(KNex) nmm <- as(KNex $ mm, "nMatrix") str(xlx <- crossprod(nmm))# "nsCMatrix" stopifnot(isSymmetric(xlx)) image(xlx, main=paste("crossprod(nmm) : Sparse", class(xlx)))

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