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### =========================================================================
### DelayedOp objects
### -------------------------------------------------------------------------
###
### In a DelayedArray object the delayed operations are stored as a tree of
### DelayedOp objects. Each node in the tree is represented by a DelayedOp
### object. 8 types of nodes are currently supported. Each type is a concrete
### DelayedOp subclass:
###
### Node type Represented operation
### -------------------------------------------------------------------
### DelayedOp (VIRTUAL)
### -------------------------------------------------------------------
### * DelayedUnaryOp (VIRTUAL)
### o DelayedSubset Multi-dimensional single bracket
### subsetting.
### o DelayedAperm Extended aperm() (can drop and/or
### add ineffective dimensions).
### o DelayedUnaryIsoOp (VIRTUAL) Unary op that preserves the
### geometry.
### - DelayedUnaryIsoOpStack Simple ops stacked together.
### - DelayedUnaryIsoOpWithArgs One op with vector-like arguments
### along the dimensions of the input.
### - DelayedSubassign Multi-dimensional single bracket
### subassignment.
### - DelayedSetDimnames Set/replace the dimnames.
### -------------------------------------------------------------------
### * DelayedNaryOp (VIRTUAL)
### o DelayedNaryIsoOp N-ary op that preserves the
### geometry.
### o DelayedAbind abind()
### -------------------------------------------------------------------
###
### All DelayedOp objects must comply with the "seed contract" i.e. they must
### support dim(), dimnames(), and extract_array(). This makes them de facto
### array-like objects. However, end users will never interact with them
### directly, except for the root of the tree which is the DelayedArray
### object itself and the only node in the tree that they are able to see
### and touch.
###
### This virtual class and its 8 concrete subclasses are for internal use
### only and never exposed to the end user.
setClass("DelayedOp", contains="Array", representation("VIRTUAL"))
### NOT exported for now.
setGeneric("is_noop", function(x) standardGeneric("is_noop"))
### S3/S4 combo for summary.DelayedOp
.DelayedOp_summary <- function(object) sprintf("%s object", class(object))
summary.DelayedOp <- function(object, ...) .DelayedOp_summary(object, ...)
setMethod("summary", "DelayedOp", summary.DelayedOp)
### - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
### DelayedUnaryOp objects
###
setClass("DelayedUnaryOp",
contains="DelayedOp",
representation(
"VIRTUAL",
seed="ANY" # The input array-like object. Expected to comply
# with the "seed contract".
),
prototype(
seed=new("array")
)
)
.validate_DelayedUnaryOp <- function(x)
{
if (length(dim(x@seed)) == 0L)
return("the supplied seed must have dimensions")
res <- try(S4Arrays:::extract_empty_array(x@seed), silent=TRUE)
if (inherits(res, "try-error"))
return("the supplied seed must support extract_array()")
TRUE
}
setValidity2("DelayedUnaryOp", .validate_DelayedUnaryOp)
### - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
### DelayedUnaryIsoOp objects
###
### Representation of a delayed unary isometric operation.
###
setClass("DelayedUnaryIsoOp",
contains="DelayedUnaryOp",
representation("VIRTUAL")
)
### Seed contract.
### The 3 default methods below give DelayedUnaryIsoOp derivatives a no-op
### semantic by default.
### DelayedUnaryIsoOpStack and DelayedUnaryIsoOpWithArgs objects overwrite
### this default "extract_array" method.
### DelayedSetDimnames objects overwrite this default "dimnames" method.
### Note that a DelayedArray object is also a DelayedUnaryIsoOp derivative
### and is considered to be the root node of the tree of DelayedOp objects
### contained in it. From a DelayedOp point of view, this root node must
### represent a no-op so DelayedArray objects inherit the 3 default methods
### below.
setMethod("dim", "DelayedUnaryIsoOp", function(x) dim(x@seed))
setMethod("dimnames", "DelayedUnaryIsoOp", function(x) dimnames(x@seed))
setMethod("extract_array", "DelayedUnaryIsoOp",
function(x, index) extract_array(x@seed, index)
)
### is_sparse() and extract_sparse_array().
### Like the 3 default methods above (seed contract), the 2 default methods
### below also implement a no-op semantic and are also inherited by
### DelayedArray objects.
setMethod("is_sparse", "DelayedUnaryIsoOp", function(x) is_sparse(x@seed))
### 'is_sparse(x)' is assumed to be TRUE and 'index' is assumed to
### not contain duplicates. See "extract_sparse_array() contract"
### in SparseArray/R/extract_sparse_array.R (SparseArray package).
setMethod("extract_sparse_array", "DelayedUnaryIsoOp",
function(x, index) extract_sparse_array(x@seed, index)
)
### 'is_sparse(x)' is assumed to be TRUE and 'index' is assumed to
### not contain duplicates. See "OLD_extract_sparse_array() Terms of Use"
### in SparseArraySeed-class.R
setMethod("OLD_extract_sparse_array", "DelayedUnaryIsoOp",
function(x, index) OLD_extract_sparse_array(x@seed, index)
)
### - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
### DelayedNaryOp objects
###
setClass("DelayedNaryOp",
contains="DelayedOp",
representation(
"VIRTUAL",
seeds="list" # The input array-like objects. Each object is
# expected to comply with the "seed contract".
),
prototype(
seeds=list(new("array"))
)
)
.validate_DelayedNaryOp <- function(x)
{
if (!is.list(x@seeds))
return("'x@seeds' must be a list")
if (length(x@seeds) == 0L)
return("'x@seeds' cannot be empty")
for (i in seq_along(x@seeds)) {
seed <- x@seeds[[i]]
if (length(dim(seed)) == 0L)
return(paste0("x@seeds[[", i, "]] has no dimensions ",
"(all the supplied seeds must have dimensions)"))
res <- try(S4Arrays:::extract_empty_array(seed), silent=TRUE)
if (inherits(res, "try-error"))
return(paste0("x@seeds[[", i, "]] does not support ",
"extract_array() (all the supplied seeds ",
"must support extract_array())"))
}
TRUE
}
setValidity2("DelayedNaryOp", .validate_DelayedNaryOp)
### - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
### updateObject()
###
setMethod("updateObject", "DelayedOp",
function(object, ..., verbose=FALSE)
{
if (.hasSlot(object, "seed")) {
object@seed <- updateObject(object@seed, ..., verbose=verbose)
}
if (.hasSlot(object, "seeds")) {
object@seeds <- lapply(object@seeds,
function(seed) updateObject(seed, ..., verbose=verbose))
}
object
}
)
|
