fix issues with examples

DESCRIPTION

@@ -8,12 +8,11 @@ Authors@R:
            comment = c(ORCID = "0000-0002-0380-1503")),
       person("Lucy", "Goodfellow", , "lucy.goodfellow@lshtm.ac.uk", role = c("aut"),
            comment = c(ORCID = "0009-0004-0434-5863")))
-Description: A convenient framework for aggregating
-    and disaggregating continuously varying parameters (for example, case fatality
-    ratio, with age) for proper parametrization of lower-resolution compartmental
-    models (for example, with broad age categories) and subsequent upscaling of
-    model outputs to high resolution (for example, as needed when calculating
-    age-sensitive measures like years-life-lost).
+Description: A convenient framework for aggregating and disaggregating continuously
+    varying parameters (for example, case fatality ratio, with age) for proper
+    parametrization of lower-resolution compartmental models (for example, with
+    broad age categories) and subsequent upscaling of model outputs to high resolution
+    (for example, as needed when calculating age-sensitive measures like years-life-lost).
 License: MIT + file LICENSE
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)

R/aggregate.R

@@ -39,11 +39,13 @@ utils::globalVariables(c(
 #' ifr_levin <- function(age_in_years) {
 #'   (10^(-3.27 + 0.0524 * age_in_years))/100
 #' }
-#' age_limits <- c(seq(0, 69, by = 5), 70, 80, 100)
+#' age_limits <- c(seq(0, 69, by = 5), 70, 80, 101)
 #' age_pyramid <- data.frame(
-#'   from = 0:100, weight = ifelse(0:100 < 65, 1, .99^(0:100-64))
-#' ) # flat age distribution, then 1% annual deaths
-#' ifr_alembic <- alembic(ifr_levin, age_pyramid, age_limits, 0:100)
+#'   from = 0:101, weight = ifelse(0:101 < 65, 1, .99^(0:101-64))
+#' )
+#' age_pyramid$weight[102] <- 0
+#' # flat age distribution, then 1% annual deaths, no one lives past 101
+#' ifr_alembic <- alembic(ifr_levin, age_pyramid, age_limits, 0:101)
 #'
 #' @importFrom utils head tail
 #' @importFrom stats integrate
@@ -115,11 +117,15 @@ alembic <- function(
 #' ifr_levin <- function(age_in_years) {
 #'   (10^(-3.27 + 0.0524 * age_in_years))/100
 #' }
-#' age_limits <- c(seq(0, 69, by = 5), 70, 80, 100)
+#'
+#' age_limits <- c(seq(0, 69, by = 5), 70, 80, 101)
 #' age_pyramid <- data.frame(
-#'   from = 0:99, weight = ifelse(0:99 < 65, 1, .99^(0:99-64))
-#' ) # flat age distribution, then 1% annual deaths
-#' alembic_dt <- alembic(ifr_levin, age_pyramid, age_limits, 0:100)
+#'   from = 0:101, weight = ifelse(0:101 < 65, 1, .99^(0:101-64))
+#' )
+#' age_pyramid$weight[102] <- 0
+#' # flat age distribution, then 1% annual deaths, no one lives past 101
+#'
+#' alembic_dt <- alembic(ifr_levin, age_pyramid, age_limits, 0:101)
 #'
 #' ifr_blend <- blend(alembic_dt)
 #' # the actual function
@@ -140,7 +146,8 @@ alembic <- function(
 #' )
 #' # properly aggregated, but not accounting for age distribution
 #' bad_alembic_dt <- alembic(
-#'   ifr_levin, within(age_pyramid, weight <- 1), age_limits, 0:100
+#'   ifr_levin,
+#'   within(age_pyramid, weight <- c(rep(1, 101), 0)), age_limits, 0:101
 #' )
 #' ifr_unif <- blend(bad_alembic_dt)
 #' lines(
@@ -188,13 +195,18 @@ blend <- function(
 #' ifr_levin <- function(age_in_years) {
 #'   (10^(-3.27 + 0.0524 * age_in_years))/100
 #' }
-#' age_limits <- c(seq(0, 69, by = 5), 70, 80, 100)
-#' age_pyramid <- data.table(
-#'   from = 0:99, weight = ifelse(0:99 < 65, 1, .99^(0:99-64))
-#' ) # flat age distribution, then 1% annual deaths
-#' alembic_dt <- alembic(ifr_levin, age_pyramid, age_limits, 0:100)
 #'
-#' results <- data.table(model_partition = head(age_limits, -1))[, value := 10]
+#' age_limits <- c(seq(0, 69, by = 5), 70, 80, 101)
+#' age_pyramid <- data.frame(
+#'   from = 0:101, weight = ifelse(0:101 < 65, 1, .99^(0:101-64))
+#' )
+#' age_pyramid$weight[102] <- 0
+#' # flat age distribution, then 1% annual deaths, no one lives past 101
+#'
+#' alembic_dt <- alembic(ifr_levin, age_pyramid, age_limits, 0:101)
+#'
+#' results <- data.frame(model_partition = head(age_limits, -1))
+#' results$value <- 10
 #' distill(alembic_dt, results)
 distill <- function(
   alembic_dt, outcomes_dt, groupcol = names(outcomes_dt)[1]