DelayedUnaryIsoOpWithArgs-class: DelayedUnaryIsoOpWithArgs objects

In Bioconductor/DelayedArray: A unified framework for working transparently with on-disk and in-memory array-like datasets

DelayedUnaryIsoOpWithArgs objects

Description

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

The DelayedUnaryIsoOpWithArgs class provides a formal representation of a delayed unary isometric operation with vector-like arguments going along the dimensions of the input array. It is a concrete subclass of the DelayedUnaryIsoOp virtual class, which itself is a subclass of the DelayedUnaryOp virtual class, which itself is a subclass of the DelayedOp virtual class:

                          DelayedOp
                              ^
                              |
                       DelayedUnaryOp
                              ^
                              |
                      DelayedUnaryIsoOp
                              ^
                              |
                  DelayedUnaryIsoOpWithArgs
  

DelayedUnaryIsoOpWithArgs objects are used inside a DelayedArray object to represent the delayed unary isometric operations with vector-like arguments going along the dimensions of the input array 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 'DelayedUnaryIsoOpWithArgs'
summary(object, ...)

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

## DelayedUnaryIsoOpWithArgs objects inherit the default dim()
## and dimnames() methods defined for DelayedUnaryIsoOp
## derivatives, but overwite their extract_array() method.

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

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

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

## S4 method for signature 'DelayedUnaryIsoOpWithArgs'
OLD_extract_sparse_array(x, index)

Arguments

x, object	A DelayedUnaryIsoOpWithArgs object.
index	See ?extract_array in the S4Arrays package for a description of the index argument.
...	Not used.

Details

A DelayedUnaryIsoOpWithArgs object is used to represent the delayed version of an operation of the form:

    out <- OP(L1, L2, ..., a, R1, R2, ...)
  

where:

• OP is an isometric array transformation i.e. a transformation that returns an array with the same dimensions as the input array.

• a is the input array.

• L1, L2, etc... are the left arguments.

• R1, R2, etc... are the right arguments.

• The output (out) is an array of same dimensions as a.

Some of the arguments (left or right) can go along the dimensions of the input array. For example if a is a 12 x 150 x 5 array, argument L2 is considered to go along the 3rd dimension if its length is 5 and if the result of:

    OP(L1, L2[k], ..., a[ , , k, drop=FALSE], R1, R2, ...)
  

is the same as out[ , , k, drop=FALSE] for any index k.

More generally speaking, if, say, arguments L2, L3, R1, and R2 go along the 3rd, 1st, 2nd, and 1st dimensions, respectively, then each value in the output array (a[i, j, k]) must be determined solely by the corresponding values in the input array (a[i, j, k]) and arguments (L2[k], L3[i], R1[j], R2[i]). In other words, out[i, j, k] must be equal to:

    OP(L1, L2[k], L3[i], ..., a[i, j, k], R1[j], R2[i], ...)
  

for any 1 <= i <= 12, 1 <= j <= 150, and 1 <= k <= 5.

We refer to this property as the locality principle.

Concrete examples:

1. Addition (or any operation in the Ops group) of an array a and an atomic vector v of length dim(a)[[1]]:

   • `+`(a, v): OP is `+`, right argument goes along the 1st dimension.

   • `<=`(a, v): OP is `<=`, right argument goes along the 1st dimension.

   • `&`(v, a): OP is `&`, left argument goes along the 1st dimension.

2. scale(x, center=v1, scale=v2): OP is scale, right arguments center and scale go along the 2nd dimension.

Note that if OP has no argument that goes along a dimension of the input array, then the delayed operation is better represented with a DelayedUnaryIsoOpStack object.

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 in the S4Arrays package.

• OLD_extract_sparse_array.

Examples

## DelayedUnaryIsoOpWithArgs extends DelayedUnaryIsoOp, which extends
## DelayedUnaryOp, which extends DelayedOp:
extends("DelayedUnaryIsoOpWithArgs")

## ---------------------------------------------------------------------
## BASIC EXAMPLE
## ---------------------------------------------------------------------
m0 <- matrix(runif(12), ncol=3)
M0 <- DelayedArray(m0)
showtree(M0)

M <- M0 + 101:104
showtree(M)
class(M@seed)        # a DelayedUnaryIsoOpWithArgs object

## ---------------------------------------------------------------------
## PROPAGATION OF SPARSITY
## ---------------------------------------------------------------------
sm0 <- sparseMatrix(i=c(1, 4), j=c(1, 3), x=c(11, 43), dims=4:3)
SM0 <- DelayedArray(sm0)
showtree(SM0)
is_sparse(SM0)       # TRUE

M1 <- SM0 + 101:104
showtree(M1)
class(M1@seed)       # a DelayedUnaryIsoOpWithArgs object
is_sparse(M1@seed)   # FALSE

SM2 <- SM0 * 101:104
showtree(SM2)
class(SM2@seed)      # a DelayedUnaryIsoOpWithArgs object
is_sparse(SM2@seed)  # TRUE

SM3 <- SM0 * c(101:103, 0)
showtree(SM3)
class(SM3@seed)      # a DelayedUnaryIsoOpWithArgs object
is_sparse(SM3@seed)  # TRUE

M4 <- SM0 * c(101:103, NA)
showtree(M4)
class(M4@seed)       # a DelayedUnaryIsoOpWithArgs object
is_sparse(M4@seed)   # FALSE

M5 <- SM0 * c(101:103, Inf)
showtree(M5)
class(M5@seed)       # a DelayedUnaryIsoOpWithArgs object
is_sparse(M5@seed)   # FALSE

SM6 <- SM0 / 101:104
showtree(SM6)
class(SM6@seed)      # a DelayedUnaryIsoOpWithArgs object
is_sparse(SM6@seed)  # TRUE

M7 <- SM0 / c(101:103, 0)
showtree(M7)
class(M7@seed)       # a DelayedUnaryIsoOpWithArgs object
is_sparse(M7@seed)   # FALSE

M8 <- SM0 / c(101:103, NA)
showtree(M8)
class(M8@seed)       # a DelayedUnaryIsoOpWithArgs object
is_sparse(M8@seed)   # FALSE

SM9 <- SM0 / c(101:103, Inf)
showtree(SM9)
class(SM9@seed)      # a DelayedUnaryIsoOpWithArgs object
is_sparse(SM9@seed)  # TRUE

M10 <- 101:104 / SM0
showtree(M10)
class(M10@seed)      # a DelayedUnaryIsoOpWithArgs object
is_sparse(M10@seed)  # FALSE

## ---------------------------------------------------------------------
## ADVANCED EXAMPLE
## ---------------------------------------------------------------------
## Not ready yet!
#op <- DelayedArray:::new_DelayedUnaryIsoOpWithArgs(m0,
#          scale,
#          Rargs=list(center=c(1, 0, 100), scale=c(10, 1, 1)),
#          Ralong=c(2, 2))

## ---------------------------------------------------------------------
## SANITY CHECKS
## ---------------------------------------------------------------------
stopifnot(class(M@seed) == "DelayedUnaryIsoOpWithArgs")
stopifnot(class(M1@seed) == "DelayedUnaryIsoOpWithArgs")
stopifnot(!is_sparse(M1@seed))
stopifnot(class(SM2@seed) == "DelayedUnaryIsoOpWithArgs")
stopifnot(is_sparse(SM2@seed))
stopifnot(class(SM3@seed) == "DelayedUnaryIsoOpWithArgs")
stopifnot(is_sparse(SM3@seed))
stopifnot(class(M4@seed) == "DelayedUnaryIsoOpWithArgs")
stopifnot(!is_sparse(M4@seed))
stopifnot(class(M5@seed) == "DelayedUnaryIsoOpWithArgs")
stopifnot(!is_sparse(M5@seed))
stopifnot(class(SM6@seed) == "DelayedUnaryIsoOpWithArgs")
stopifnot(is_sparse(SM6@seed))
stopifnot(class(M7@seed) == "DelayedUnaryIsoOpWithArgs")
stopifnot(!is_sparse(M7@seed))
stopifnot(class(M8@seed) == "DelayedUnaryIsoOpWithArgs")
stopifnot(!is_sparse(M8@seed))
stopifnot(class(SM9@seed) == "DelayedUnaryIsoOpWithArgs")
stopifnot(is_sparse(SM9@seed))
stopifnot(class(M10@seed) == "DelayedUnaryIsoOpWithArgs")
stopifnot(!is_sparse(M10@seed))

Bioconductor/DelayedArray documentation built on March 4, 2024, 9:12 p.m.