# R/conditionalentropy.R In rinform: An R Wrapper of the 'Inform' C Library for Information Analysis of Complex Systems

#### Documented in conditional_entropy

```################################################################################
# Use of this source code is governed by a MIT license that can be found in the
################################################################################

################################################################################
#' 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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rinform documentation built on April 1, 2018, 12:12 p.m.