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#' Resample an array
#'
#' The \code{resample} function uses a kernel function to resample a target
#' array. This can be thought of as a generalisation of array indexing which
#' allows fractional indices. It is (S3) generic. The \code{rescale} function
#' is an alternative interface for the common case where the image is being
#' scaled to a new size.
#'
#' @param x Any object. For the default method, this must be coercible to an
#' array.
#' @param points Either a matrix giving the points to sample at, one per row,
#' or a list giving the locations on each axis, which will be made into a grid.
#' @param kernel A kernel function object, used to provide coefficients for
#' each resampled value, or the name of one.
#' @param pointType A string giving the type of the point specification being
#' used. Usually can be left as \code{"auto"}.
#' @param factor A vector of scale factors, which will be recycled to the
#' dimensionality of \code{x}.
#' @param \dots Additional options, such as kernel parameters.
#' @return If a generalised sampling scheme is used (i.e. with \code{points} a
#' matrix), the result is a vector of sampled values. For a grid scheme (i.e.
#' with \code{points} a list, including for \code{rescale}), it is a
#' resampled array.
#'
#' @examples
#' resample(c(0,0,1,0,0), seq(0.75,5.25,0.5), triangleKernel())
#' @author Jon Clayden <code@@clayden.org>
#' @seealso \code{\link{kernels}} for kernel-generating functions.
#' @export
resample <- function (x, points, kernel, ...)
{
UseMethod("resample")
}
#' @rdname resample
#' @export
resample.default <- function (x, points, kernel, pointType = c("auto","general","grid"), ...)
{
x <- as.array(x)
if (!is.numeric(x) && !is.logical(x))
stop("Target array must be numeric")
if (!isKernelFunction(kernel))
kernel <- kernelFunction(kernel, ...)
nDims <- length(dim(x))
if (nDims == 1 && !is.matrix(points) && !is.list(points))
points <- list(points)
pointType <- match.arg(pointType)
if (pointType == "general" && (!is.matrix(points) || ncol(points) != nDims))
stop("Points must be specified as a matrix with #{nDims} columns")
else if (pointType == "grid" && (!is.list(points) || length(points) != nDims))
stop("Points must be specified as a list of length #{nDims}")
else if (pointType == "auto")
{
if (is.matrix(points) && ncol(points) == nDims)
pointType <- "general"
else if (is.list(points) && length(points) == nDims)
pointType <- "grid"
else
stop("Point specification is not valid")
}
if (is.matrix(points))
points <- points - 1
else if (is.list(points))
points <- lapply(points, "-", 1)
result <- .Call(C_resample, x, kernel, list(type=pointType,points=points))
if (is.list(points) && nDims > 1)
dim(result) <- sapply(points, length)
return (result)
}
#' @rdname resample
#' @export
rescale <- function (x, factor, kernel, ...)
{
x <- as.array(x)
dims <- dim(x)
nDims <- length(dims)
if (length(factor) < nDims)
factor <- rep(factor, length.out=nDims)
points <- lapply(seq_len(nDims), function(i) {
newLength <- ceiling(dims[i] * factor[i])
locs <- seq(0.5, dims[i]+0.5, length.out=newLength+1)
locs <- locs + diff(locs[1:2]) / 2
locs <- locs[1:newLength]
})
resample(x, points, kernel, ...)
}
#' Get neighbourhood information for an array
#'
#' This function provides information about the structure of a neighbourhood of
#' a given width within a specified array.
#'
#' @param x An object that can be coerced to an array.
#' @param width A vector giving the width of the neighbourhood in each
#' dimension, which will be recycled if necessary. Must not be greater than
#' the size of the array. Even values are rounded up to the next odd integer.
#' @return A list with the following elements.
#' \item{widths}{The width of the neighbourhood along each dimension.
#' Currently all elements of this vector will be the same.}
#' \item{size}{The number of pixels within the neighbourhood.}
#' \item{locs}{A matrix giving the coordinates of each neighbourhood pixel
#' relative to the centre pixel, one per row.}
#' \item{offsets}{Vector offsets of the neighbourhood values within
#' \code{x}.}
#'
#' @author Jon Clayden <code@@clayden.org>
#' @export
neighbourhood <- function (x, width)
{
x <- as.array(x)
nDims <- length(dim(x))
if (length(width) < nDims)
width <- rep(width, length.out=nDims)
if (any(width > dim(x)))
stop("Requested neighbourhood is larger than the data")
return (.Call(C_get_neighbourhood, x, as.integer(width)))
}
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