DelayedNaryIsoOp-class {DelayedArray} | R Documentation

## DelayedNaryIsoOp objects

### Description

NOTE: This man page is about DelayedArray internals and is provided for developers and advanced users only.

The DelayedNaryIsoOp class provides a formal representation of a delayed N-ary isometric operation. It is a concrete subclass of the DelayedNaryOp virtual class, which itself is a subclass of the DelayedOp virtual class:

                              DelayedOp
                                  ^
                                  |
                            DelayedNaryOp
                                  ^
                                  |
                           DelayedNaryIsoOp

DelayedNaryIsoOp objects are used inside a DelayedArray object to represent the delayed N-ary isometric operation carried by the object. They're never exposed to the end user and are not intended to be manipulated directly.

### Usage

    ## S4 method for signature 'DelayedNaryIsoOp'
    summary(object, ...)

    ## ~ ~ ~ Seed contract ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~

    ## S4 method for signature 'DelayedNaryIsoOp'
    dim(x)

    ## S4 method for signature 'DelayedNaryIsoOp'
    dimnames(x)

    ## S4 method for signature 'DelayedNaryIsoOp'
    extract_array(x, index)

    ## ~ ~ ~ Propagation of sparsity ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~

    ## S4 method for signature 'DelayedNaryIsoOp'
    is_sparse(x)

    ## S4 method for signature 'DelayedNaryIsoOp'
    extract_sparse_array(x, index)

### Arguments

`x, object` | A DelayedNaryIsoOp object.
`index` | See `?extract_array` for a description of the `index` argument.
`...` | Not used.

### See Also

- DelayedOp objects.

- `showtree` to visualize the nodes and access the leaves in the tree of delayed operations carried by a DelayedArray object.

- `extract_array` and `extract_sparse_array`.

### Examples

    ## DelayedNaryIsoOp extends DelayedNaryOp which extends DelayedOp:
    extends("DelayedNaryIsoOp")

    ## ---------------------------------------------------------------------
    ## BASIC EXAMPLE
    ## ---------------------------------------------------------------------
    m1 <- matrix(101:130, ncol=5)
    m2 <- matrix(runif(30), ncol=5)
    M1 <- DelayedArray(m1)
    M2 <- DelayedArray(m2)
    showtree(M1)
    showtree(M2)

    M <- M1 / M2
    showtree(M)
    class(M@seed)        # a DelayedNaryIsoOp object

    ## ---------------------------------------------------------------------
    ## PROPAGATION OF SPARSITY
    ## ---------------------------------------------------------------------
    sm1 <- sparseMatrix(i=c(1, 6), j=c(1, 4), x=c(11, 64), dims=6:5)
    SM1 <- DelayedArray(sm1)
    sm2 <- sparseMatrix(i=c(2, 6), j=c(1, 5), x=c(21, 65), dims=6:5)
    SM2 <- DelayedArray(sm2)
    showtree(SM1)
    showtree(SM2)
    is_sparse(SM1)       # TRUE
    is_sparse(SM2)       # TRUE

    SM3 <- SM1 - SM2
    showtree(SM3)
    class(SM3@seed)      # a DelayedNaryIsoOp object
    is_sparse(SM3@seed)  # TRUE

    M4 <- SM1 / SM2
    showtree(M4)
    class(M4@seed)       # a DelayedNaryIsoOp object
    is_sparse(M4@seed)   # FALSE

    ## ---------------------------------------------------------------------
    ## SANITY CHECKS
    ## ---------------------------------------------------------------------
    stopifnot(class(M@seed) == "DelayedNaryIsoOp")
    stopifnot(class(SM3@seed) == "DelayedNaryIsoOp")
    stopifnot(is_sparse(SM3@seed))
    stopifnot(class(M4@seed) == "DelayedNaryIsoOp")
    stopifnot(!is_sparse(M4@seed))

[Package DelayedArray version 0.18.0 Index]