# dct.R
# Copyright (C) 2020 Geert van Boxtel <gjmvanboxtel@gmail.com>
# Original Octave code:
# Copyright (C) 2001 Paul Kienzle <pkienzle@users.sf.net>
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 3
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#
# Version history
# 20201015 GvB setup for gsignal v0.1.0
# 20210506 GvB use matrix() instead of as.matrix()
# 20220328 GvB copy dimnames of x to output object
#------------------------------------------------------------------------------
#' Discrete Cosine Transform
#'
#' Compute the unitary discrete cosine transform of a signal.
#'
#' The discrete cosine transform (DCT) is closely related to the discrete
#' Fourier transform. You can often reconstruct a sequence very accurately from
#' only a few DCT coefficients. This property is useful for applications
#' requiring data reduction.
#'
#' The DCT has four standard variants. This function implements the DCT-II
#' according to the definition in [1], which is the most common variant, and
#' the original variant first proposed for image processing.
#'
#' @note The transform is faster if \code{x} is real-valued and has even length.
#'
#' @param x input data, specified as a numeric vector or matrix. In case of a
#' vector it represents a single signal; in case of a matrix each column is a
#' signal.
#' @param n transform length, specified as a positive integer scalar. Default:
#' \code{NROW(x)}.
#'
#' @return Discrete cosine transform, returned as a vector or matrix.
#'
#' @examples
#' x <- matrix(seq_len(100) + 50 * cos(seq_len(100) * 2 * pi / 40))
#' X <- dct(x)
#'
#' # Find which cosine coefficients are significant (approx.)
#' # zero the rest
#' nsig <- which(abs(X) < 1)
#' N <- length(X) - length(nsig) + 1
#' X[nsig] <- 0
#'
#' # Reconstruct the signal and compare it to the original signal.
#' xx <- idct(X)
#' plot(x, type = "l")
#' lines(xx, col = "red")
#' legend("bottomright", legend = c("Original", paste("Reconstructed, N =", N)),
#' lty = 1, col = 1:2)
#'
#' @author Paul Kienzle, \email{pkienzle@@users.sf.net}.\cr
#' Conversion to R by Geert van Boxtel, \email{G.J.M.vanBoxtel@@gmail.com}.
#'
#' @references [1] \url{https://en.wikipedia.org/wiki/Discrete_cosine_transform}
#'
#' @seealso \code{\link{idct}}
#'
#' @export
dct <- function(x, n = NROW(x)) {
# check parameters
if (!(is.vector(x) || is.matrix(x)) || !(is.numeric(x) || is.complex(x))) {
stop("x must be a numeric or complex vector or matrix")
} else {
realx <- is.numeric(x)
}
if (is.vector(x)) {
vec <- TRUE
x <- matrix(x, ncol = 1)
} else {
vec <- FALSE
}
nr <- nrow(x)
nc <- ncol(x)
if (!isPosscal(n) || !isWhole(n)) {
stop("n must be a positive integer")
}
if (n != nr) {
x <- postpad(x, n)
}
if (n == 1) {
w <- 1 / 2
} else {
w <- c(sqrt(1 / 4 / n),
sqrt(1 / 2 / n) * exp((-1i * pi / 2 / n) * seq_len(n - 1))) %o%
rep(1, nc)
}
if (realx && n %% 2 == 0) {
y <- stats::mvfft(rbind(matrix(x[seq(1, n, 2), ], ncol = nc),
matrix(x[seq(n, 1, -2), ], ncol = nc)))
y <- 2 * Re(w * y)
} else {
y <- stats::mvfft(rbind(x, matrix(pracma::flipud(x), ncol = nc)))
y <- w * y[1:n, ]
}
if (realx) {
y <- Re(y)
}
if (vec) {
y <- as.vector(y)
}
dimnames(y) <- dimnames(x)
y
}
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