#' findNbounds
#'
#' Find the bins for the colour grid
#'
#' @param data Dataset from which bounds are to be determined.
#' @param estimate Name of the estimate column.
#' @param error Name of the error column.
#' @param terciles Should terciles be calculated? (Default: FALSE).
#' @param expertR_est A vector consisting of the range of expert values for the
#' estimate (Default: NA).
#' @param expertR_err A vector consisting of the range of expert values for the
#' error (Default: NA).
#'
#' @details Expert ranges for the estimate and error can be supplied to assist
#' with the comparison of multiple figures. By default these are set to NA,
#' which will result in the bounds being directly computed from the data.
#' Note, if the expert values do not span the range of the data, this function
#' will default to finding the bounds of the data.
#'
#' @export
findNbounds <-
function (data,
estimate,
error,
terciles,
expertR_est = NA,
expertR_err = NA)
{
max_estimate <- max(c(expertR_est, data[, estimate]), na.rm = TRUE)
min_estimate <-
min(c(expertR_est, data[, estimate]), na.rm = TRUE)
max_error <- max(c(expertR_err, data[, error]), na.rm = TRUE)
min_error <- min(c(expertR_err, data[, error]), na.rm = TRUE)
width_estimate <- (max_estimate - min_estimate) / 3
width_error <- (max_error - min_error) / 3
estimate_bin1 <- calcbin(
terciles = terciles,
data = data,
x = estimate,
q = 1 / 3,
bin = 1,
width = width_estimate,
min = min_estimate
)
estimate_bin2 <- calcbin(
terciles = terciles,
data = data,
x = estimate,
q = 2 / 3,
bin = 2,
width = width_estimate,
min = min_estimate
)
estimate_bin3 <- calcbin(
terciles = terciles,
data = data,
x = estimate,
q = 1,
bin = 3,
width = width_estimate,
min = min_estimate
)
error_bin1 <-
calcbin(
terciles = terciles,
data = data,
x = error,
q = 1 / 3,
bin = 1,
width = width_error,
min = min_error
)
error_bin2 <-
calcbin(
terciles = terciles,
data = data,
x = error,
q = 2 / 3,
bin = 2,
width = width_error,
min = min_error
)
error_bin3 <-
calcbin(
terciles = terciles,
data = data,
x = error,
q = 1,
bin = 3,
width = width_error,
min = min_error
)
bound <- c(
min_estimate,
estimate_bin1,
estimate_bin2,
estimate_bin3,
min_error,
error_bin1,
error_bin2,
error_bin3
)
bound
}
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