growth_rate.R

#' Calculate growth/decay rate
#'
#' @author Tim Taylor
#'
#' @param x The output of `fit_curve()`.
#' @param alpha Value of alpha used to calculate confidence intervals; defaults
#'   to 0.05 which corresponds to a 95% confidence interval.
#' @param growth_decay_time Should a doubling/halving time and corresponding
#'   confidence intervals be added to the output. Default TRUE.
#' @param include_warnings Include models in output that triggered warnings but
#'   not errors.  Defaults to `FALSE`.
#' @param ... Not currently used.
#'
#' @export
growth_rate <- function(x, ...) {
    UseMethod("growth_rate")
}

#' @rdname growth_rate
#' @aliases growth_rate.default
#' @export
growth_rate.default <- function(x, ...) {
    not_implemented(x)
}

#' @rdname growth_rate
#' @aliases growth_rate.incidence2_fit
#' @export
growth_rate.incidence2_fit <- function(x, alpha = 0.05,
                                       growth_decay_time = TRUE,
                                       include_warnings = FALSE, ...) {

    dat <- is_ok(x, include_warnings = include_warnings)
    model_var <- attr(dat, "model")

    r <- vapply(
        dat[[model_var]],
        function(x) x$coefficients[2],
        double(1)
    )

    r_lower <- vapply(
        dat[[model_var]],
        function(x) suppressMessages(confint(x, 2, 1 - alpha)[1]),
        double(1)
    )

    r_upper <- vapply(
        dat[[model_var]],
        function(x) suppressMessages(confint(x, 2, 1 - alpha)[2]),
        double(1)
    )

    res <- tibble(
        model = dat[[model_var]],
        r,
        r_lower,
        r_upper
    )

    groups <- attr(dat, "groups")
    if (!is.null(groups)) res <- bind_cols(dat[groups], res)

    count_variable <- attr(dat, "count_variable")
    res <- bind_cols(dat[count_variable], res)

    if (growth_decay_time) add_two_time(res) else res

}

add_two_time <- function(dat, r = "r", r_lower = "r_lower", r_upper = "r_upper") {
    condition <- dat[[r]] < 0
    dat$growth_or_decay <- ifelse(condition, "halving", "doubling")
    dat$time <- ifelse(condition, log(0.5)/dat[[r]], log(2)/dat[[r]])
    dat$time_lower <- ifelse(condition, log(0.5)/dat[[r_lower]], log(2)/dat[[r_upper]])
    dat$time_upper <- ifelse(condition, log(0.5)/dat[[r_upper]], log(2)/dat[[r_lower]])
    dat
}