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(v0.6.1.9044) first_isolate fix for species

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dr. M.S. (Matthijs) Berends
2019-05-31 14:25:11 +02:00
parent 1f8ee3ec3e
commit 493ae2ba0c
121 changed files with 586 additions and 521 deletions
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33
R/age.R
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@ -24,15 +24,22 @@
#' Calculates age in years based on a reference date, which is the sytem date at default.
#' @param x date(s), will be coerced with \code{\link{as.POSIXlt}}
#' @param reference reference date(s) (defaults to today), will be coerced with \code{\link{as.POSIXlt}} and cannot be lower than \code{x}
#' @return Integer (no decimals)
#' @param exact a logical to indicate whether age calculation should be exact, i.e. with decimals
#' @return An integer (no decimals) if \code{exact = FALSE}, a double (with decimals) otherwise
#' @seealso \code{\link{age_groups}} to split age into age groups
#' @importFrom dplyr if_else
#' @inheritSection AMR Read more on our website!
#' @export
#' @examples
#' df <- data.frame(birth_date = Sys.Date() - runif(100) * 25000)
#' # 10 random birth dates
#' df <- data.frame(birth_date = Sys.Date() - runif(10) * 25000)
#' # add ages
#' df$age <- age(df$birth_date)
age <- function(x, reference = Sys.Date()) {
#' # add exact ages
#' df$age_exact <- age(df$birth_date, exact = TRUE)
#'
#' df
age <- function(x, reference = Sys.Date(), exact = FALSE) {
if (length(x) != length(reference)) {
if (length(reference) == 1) {
reference <- rep(reference, length(x))
@ -49,17 +56,33 @@ age <- function(x, reference = Sys.Date()) {
as.integer(years_gap - 1),
as.integer(years_gap))
# add decimals
if (exact == TRUE) {
# get dates of `x` when `x` would have the year of `reference`
x_in_reference_year <- base::as.POSIXlt(paste0(format(reference, "%Y"), format(x, "-%m-%d")))
# get differences in days
n_days_x_rest <- base::as.double(base::difftime(reference, x_in_reference_year, units = "days"))
# get numbers of days the years of `reference` has for a reliable denominator
n_days_reference_year <- base::as.POSIXlt(paste0(format(reference, "%Y"), "-12-31"))$yday + 1
# add decimal parts of year
ages <- ages + (n_days_x_rest / n_days_reference_year)
}
if (any(ages < 0, na.rm = TRUE)) {
ages[ages < 0] <- NA_integer_
ages[ages < 0] <- NA
warning("NAs introduced for ages below 0.")
}
if (any(ages > 120, na.rm = TRUE)) {
warning("Some ages are > 120.")
warning("Some ages are above 120.")
}
ages
}
age_to_toDate <- function(age) {
}
#' Split ages into age groups
#'
#' Split ages into age groups defined by the \code{split} parameter. This allows for easier demographic (antimicrobial resistance) analysis.