################################################################################
# Copyright 2017-2018 Gabriele Valentini, Douglas G. Moore. All rights reserved.
# Use of this source code is governed by a MIT license that can be found in the
# LICENSE file.
################################################################################
################################################################################
#' Conditional Entropy
#'
#' Compute the average or the local conditional entropy between two time series.
#' This function expects the \strong{condition} to be the first argument.
#'
#' @param xs Vector specifying a time series drawn from
#' the conditional distribution.
#' @param ys Vector specifying a time series drawn from
#' the target distribution.
#' @param local Boolean specifying whether to compute the local conditional
#' entropy.
#'
#' @return Numeric giving the average conditional entropy or a vector giving the
#' local conditional entropy.
#'
#' @example inst/examples/ex_conditionalentropy.R
#'
#' @export
#'
#' @useDynLib rinform r_conditional_entropy_
#' @useDynLib rinform r_local_conditional_entropy_
################################################################################
conditional_entropy <- function(xs, ys, local = FALSE) {
n <- 0
ce <- 0
err <- 0
.check_series(xs)
.check_series(ys)
.check_local(local)
# Extract number of series and length
if (is.vector(xs) & is.vector(ys)) {
if (length(xs) != length(ys)) {
stop("<", deparse(substitute(xs)), "> and <", deparse(substitute(ys)), "> differ in length")
}
n <- length(xs)
} else {
stop("<", deparse(substitute(xs)), "> or/and <", deparse(substitute(ys)), "> are not vectors")
}
# Convert to integer vector suitable for C
xs <- as.integer(xs)
ys <- as.integer(ys)
# Compute the value of <bx>
bx <- max(2, max(xs) + 1)
# Compute the value of <by>
by <- max(2, max(ys) + 1)
if (!local) {
x <- .C("r_conditional_entropy_",
ys = as.integer(xs),
xs = as.integer(ys),
n = as.integer(n),
bx = as.integer(bx),
by = as.integer(by),
rval = as.double(ce),
err = as.integer(err))
if (.check_inform_error(x$err) == 0) {
ce <- x$rval
}
} else {
ce <- rep(0, n)
x <- .C("r_local_conditional_entropy_",
ys = as.integer(xs),
xs = as.integer(ys),
n = as.integer(n),
bx = as.integer(bx),
by = as.integer(by),
rval = as.double(ce),
err = as.integer(err))
if (.check_inform_error(x$err) == 0) {
ce <- x$rval
}
}
ce
}
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