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#' Apply a univariate transformation to a \code{"xifti"} or pair of \code{"xifti"}s.
#'
#' Apply a univariate transformation to each value in a \code{"xifti"} or pair of
#' \code{"xifti"}s. If a pair, they must share the same dimensions (brainstructures)
#' and number of measurements.
#'
#' If the \code{"xifti"} had the dlabel intent, and the transformation creates
#' any value that is not a label value (e.g. a non-integer), then it is converted
#' to a dscalar.
#'
#' Technically, the function does not have to be univariate: it only has to return the
#' same number of values as the input. The function will be applied to the matrix
#' for each brain structure separately. For example, the function
#' \code{function(q){(q - mean(q)) / sd(q)}} will scale each brainstructure, while
#' \code{scale} will scale each column of each brainstructure.
#'
#' @inheritParams xifti_Param
#' @param FUN The function. If \code{xifti2} is not provided, it should be
#' a univariate function like \code{log} or \code{sqrt}. If
#' \code{xifti2} is provided, it should take in two arguments, like \code{`+`}
#' or \code{pmax}.
#' @param xifti2 The second xifti, if applicable. Otherwise, \code{NULL} (default)
#' @param idx The column indices for which to apply the transformation.
#' If \code{NULL} (default), apply to all columns. If two \code{"xifti"} objects,
#' were provided, the values in the first (\code{xifti}) will be retained for columns
#' that are not transformed.
#' @param ... Additional arguments to \code{FUN}
#' @return A \code{"xifti"} storing the result of applying \code{FUN} to the input(s).
#' The data dimensions will be the same. The metadata of \code{xifti} will be retained,
#' and the metadata of \code{xifti2} will be discarded (if provided).
#'
#' @export
#' @family manipulating xifti
#' @importFrom utils capture.output
#'
transform_xifti <- function(xifti, FUN, xifti2=NULL, idx=NULL, ...) {
if (!is.xifti(xifti, messages=FALSE) && (!is.null(xifti2) && !is.xifti(xifti2, messages=FALSE))) {
stop("Neither argument is a xifti.")
}
# Check function.
if (!is.function(FUN)) {stop("`FUN` is not a function.")}
badFUNs <- c("sum", "min", "max")
FUN_char <- paste(as.character(substitute(FUN)), collapse="")
if (FUN_char %in% badFUNs) {
newFUN <- switch(FUN_char, sum=`+`, min=pmin, max=pmax)
warning(
"Replacing ", FUN_char, " with: ",
capture.output(print(substitute(newFUN)))
)
# Not working...
# warning(
# paste("Use", substitute(newFUN), "instead of", FUN_char, "\n")
# )
FUN <- newFUN
}
try_apply <- function(x, x2=NULL, FUN, ...) {
if (is.null(x2)) {
out <- FUN(x, ...)
} else {
out <- FUN(x, x2, ...)
}
if (length(out) != max(length(x), length(x2))) {
stop(
"`FUN` does not properly vectorize. ",
"It needs to return a vector the same length as its arguments. ",
"For example, `+` should be used instead of `sum`, and ",
"`pmin` should be used instead of `min`."
)
}
out
}
tapp_wrap <- function(x, x2, FUN, idx, ...) {
if (is.null(idx)) {
return(try_apply(x, x2=x2, FUN=FUN, ...))
} else {
x_ <- if (is.matrix(x)) { x[,idx,drop=FALSE] } else { x }
x2_ <- if (is.matrix(x2)) { x2[,idx,drop=FALSE] } else { x2 }
if (is.matrix(x)) {
x[,idx] <- try_apply(x_, x2=x2_, FUN=FUN, ...)
return(x)
} else {
x2[,idx] <- try_apply(x_, x2=x2_, FUN=FUN, ...)
return(x2)
}
}
}
# Unary
if (is.null(xifti2)) {
if (!is.xifti(xifti)) { stop("`xifti` is invalid.") }
if (!is.null(idx)) { stopifnot(all(idx %in% seq(ncol(xifti)))) }
for (bs in names(xifti$data)) {
if (!is.null(xifti$data[[bs]])) {
xifti$data[[bs]][] <- tapp_wrap(xifti$data[[bs]], x2=NULL, FUN=FUN, idx=idx, ...)
}
}
# xifti + unary
} else if (is.numeric(xifti2) && length(xifti2)==1){
for (bs in names(xifti$data)) {
if (!is.null(xifti$data[[bs]])) {
xifti$data[[bs]][] <- tapp_wrap(xifti$data[[bs]], x2=xifti2, FUN=FUN, idx=idx, ...)
}
}
# unary + xifti
} else if (is.numeric(xifti) && length(xifti)==1 && is.xifti(xifti2, messages=FALSE)) {
for (bs in names(xifti2$data)) {
if (!is.null(xifti2$data[[bs]])) {
xifti2$data[[bs]][] <- tapp_wrap(xifti, x2=xifti2$data[[bs]], FUN=FUN, idx=idx, ...)
}
}
xifti <- xifti2
# xifti + matrix
} else if (is.numeric(xifti2) && length(dim(xifti2))==2 && all(dim(xifti) == dim(xifti2))){
xifti2 <- newdata_xifti(xifti, xifti2)
for (bs in names(xifti$data)) {
if (!is.null(xifti$data[[bs]])) {
xifti$data[[bs]][] <- tapp_wrap(xifti$data[[bs]], x2=xifti2$data[[bs]], FUN=FUN, idx=idx, ...)
}
}
# matrix + xifti
} else if (is.numeric(xifti) && length(dim(xifti))==2 && is.xifti(xifti2, messages=FALSE && all(dim(xifti) == dim(xifti2)))) {
xifti <- newdata_xifti(xifti2, xifti)
for (bs in names(xifti2$data)) {
if (!is.null(xifti2$data[[bs]])) {
xifti2$data[[bs]][] <- tapp_wrap(xifti$data[[bs]], x2=xifti2$data[[bs]], FUN=FUN, idx=idx, ...)
}
}
xifti <- xifti2
# xifti + xifti
} else {
if (!is.xifti(xifti2, messages=FALSE)) { stop('`xifti2` is not a `"xifti"` object, single number, or of same dimensions as "xifti".') }
# Checks
bs1 <- names(xifti$data)[!vapply(xifti$data, is.null, FALSE)]
bs2 <- names(xifti2$data)[!vapply(xifti2$data, is.null, FALSE)]
if (!identical(sort(bs1), sort(bs2))) {
stop(
"The first xifti had brainstructures ", paste(bs1, collapse=", "), ".\n",
"But, the second xifti had brainstructures ", paste(bs2, collapse=", "), ".\n"
)
}
T1 <- ncol(xifti$data[[bs1[1]]])
T2 <- ncol(xifti2$data[[bs2[1]]])
if (T1 != T2) {
stop(
"The first xifti had ", T1, " measurements.\n",
"But, the second xifti had ", T2, " measurements.\n"
)
}
if (!identical(xifti$meta$cifti$names, xifti2$meta$cifti$names)) {
ciftiTools_warn("The xiftis have different column names.\n")
}
for (bs in names(xifti$data)) {
if (!is.null(xifti$data[[bs]])) {
if (nrow(xifti$data[[bs]]) != nrow(xifti2$data[[bs]])) {
if (grepl("cortex", bs)) {
len_mwall1 <- length(xifti$meta$cortex$medial_wall_mask[[gsub("cortex_", "", bs)]])
len_mwall2 <- length(xifti2$meta$cortex$medial_wall_mask[[gsub("cortex_", "", bs)]])
if (!is.null(len_mwall1) && len_mwall1 == len_mwall2) {
stop("The xiftis have the same resolution but different medial wall masks in the ", bs, " brainstructure.")
} else {
stop("The xiftis have different number of vertices/voxels for the ", bs, " brainstructure.")
}
} else {
stop("The xiftis have different number of vertices/voxels for the ", bs, " brainstructure.")
}
}
xifti$data[[bs]][] <- tapp_wrap(xifti$data[[bs]], x2=xifti2$data[[bs]], FUN=FUN, idx=idx, ...)
}
}
}
# Convert from dlabel to dscalar if non-label values were introduced by
# the transformation function.
if (!is.null(xifti$meta$cifti$intent) && xifti$meta$cifti$intent == 3007) {
v <- as.matrix(xifti)
for (T_ in seq(ncol(xifti))) {
if (!all(unique(v[,T_]) %in% xifti$meta$cifti$labels[[T_]]$Key)) {
warning(
"New data values outside the label table for column ", T_,
" were introduced. Changing the xifti intent from dlabel to dscalar."
)
xifti$meta$cifti$intent <- 3006
xifti$meta$cifti$labels <- NULL
break
}
}
}
xifti
}
#' \code{"xifti"} S3 Math methods
#'
#' Math methods for \code{"xifti"} objects.
#'
#' Uses \code{\link{transform_xifti}}.
#' @param x The \code{"xifti"}
#' @param ... Additional arguments to the function
#' @name S3_Math
#' @method Math xifti
#' @export
Math.xifti <- function(x, ...) {
transform_xifti(x, function(q){do.call(.Generic, c(list(q), ...))})
}
#' \code{"xifti"} S3 Ops methods
#'
#' Ops methods for \code{"xifti"} objects.
#'
#' Uses \code{\link{transform_xifti}}.
#' @param e1,e2 The arguments to the operation. \code{"xifti"} objects will be converted to matrices temporarily
#' @name S3_Ops
#' @method Ops xifti
#' @export
Ops.xifti <- function(e1, e2=NULL) {
transform_xifti(e1, function(q1, q2){do.call(.Generic, list(q1, q2))}, e2)
}
#' \code{"xifti"} S3 Summary methods
#'
#' Summary methods for \code{"xifti"} objects.
#' @param ... The \code{"xifti"} and additional numeric arguments will be converted to matrices
#' @param na.rm Remove \code{NA} values? Default: \code{FALSE}.
#' @name S3_Summary
#' @method Summary xifti
#' @export
Summary.xifti <- function(..., na.rm=FALSE) {
args <- list(...)
args <- lapply(args, as.matrix)
do.call(.Generic, c(args, na.rm=na.rm))
}
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