R/neurohypervec.R

In bbuchsbaum/neuroim2: Data Structures and IO for Neuroimaging Data with an Emphasis on Functional Magnetic Resonance Imaging (FMRI)

# #' Create an \code{NeuroHyperVec} instance from a variable length list of \code{NeuroVec} objects.
# #'
# #' @param ... one or more instances of type \code{NeuroVec}
# #' @export
# #'
# #' @examples
# #'
# #' v1 <- NeuroVec(array(0,c(5,5,5,4)), space=NeuroSpace(dim=c(5,5,5,4)))
# #' v2 <- NeuroVec(array(0,c(5,5,5,4)), space=NeuroSpace(dim=c(5,5,5,4)))
# #' v3 <- NeuroVec(array(0,c(5,5,5,4)), space=NeuroSpace(dim=c(5,5,5,4)))
# #' hv <- NeuroHyperVec(v1,v2,v3)
# #'
# #' @note
# #'
# #' This class is experimental.
# NeuroHyperVec <- function(...) {
#   vecs <- list(...)
#   assert_that(all(map_lgl(vecs, ~ inherits(., "NeuroVec"))))
#   sp <- space(vecs[[1]])
#   lens <- map_dbl(vecs, function(x) dim(x)[4])
#   assert_that(length(lens) > 1)
#   assert_that(all(lens == lens[1]))
#
#   sp <- add_dim(sp, lens[1])
#
#   new("NeuroHyperVec", space=sp, vecs=vecs)
# }
#
#
# # @rdname series-methods
# # @export
# setMethod("series", signature(x="NeuroHyperVec", i="matrix"),
#           def=function(x,i) {
#             out <- array(0, c(dim(x)[4], nrow(i), length(x@vecs)))
#             for (j in seq_along(x@vecs)) {
#               out[,,j] <- series(x@vecs[[j]], i)
#             }
#
#             out
#             #do.call(cbind, map(x@vecs, ~ series(., i)))
#           })