Merge pull request #26 from ssi-dk/telkamp7/issue24

Telkamp7/issue24

NAMESPACE

@@ -13,6 +13,7 @@ export(epi_calendar)
 export(fit_growth_rate)
 export(tsd)
 importFrom(ggplot2,autoplot)
+importFrom(grDevices,devAskNewPage)
 importFrom(graphics,plot)
 importFrom(lifecycle,deprecated)
 importFrom(magrittr,"%>%")

NEWS.md

@@ -5,3 +5,5 @@
 
 
 * Added a new function `epi_calendar()` that determines the epidemiological season based on a given date, allowing users to easily categorize dates within or outside specified seasons.
+
+* Introduced additional visualizations in the `autoplot()` method, enhancing the capabilities of the `plot()` method with new displays of observed cases and growth rates.

R/autoplot.R

@@ -9,8 +9,11 @@
 #'
 #' @param object An `aedseo_tsd` or `aedseo` object
 #' @param linewidth Numeric, the width of the line for the growth rate
-#' @param alpha Numeric, the alpha (transparency) for the confidence interval
-#' ribbon
+#' @param size Numeric, size of observational points.
+#' @param width Numeric, the width of the error bar employed to show the
+#' confidence interval of the growth rate estimate.
+#' @param alpha Numeric, the alpha (transparency) for the observations with a
+#' significantly positive growth rate.
 #' @param ... Additional arguments (not used).
 #'
 #' @return A 'ggplot' object for visualizing the time series data.
@@ -65,19 +68,58 @@ autoplot.aedseo_tsd <- function(object, ...) {
     ggplot2::geom_point() +
     ggplot2::geom_line()
 }
+#' @importFrom grDevices devAskNewPage
 #' @rdname autoplot
 #' @method autoplot aedseo
 #' @export
-autoplot.aedseo <- function(object, linewidth = 0.7, alpha = 0.3, ...) {
-  object %>%
-    ggplot2::ggplot(
-      mapping = ggplot2::aes(
-        x = .data$reference_time,
-        y = .data$growth_rate,
-        ymin = .data$lower_growth_rate,
-        ymax = .data$upper_growth_rate
-      )
-    ) +
-    ggplot2::geom_line(linewidth = linewidth) +
-    ggplot2::geom_ribbon(alpha = alpha)
+autoplot.aedseo <- function(
+    object,
+    linewidth = 0.7,
+    size = 2,
+    alpha = 0.3,
+    width = 0.2,
+    ...) {
+  # Construct the observed cases plot
+  # NOTE: We use print to show plots sequentially
+  suppressWarnings(
+    print(
+      object %>%
+        ggplot2::ggplot(
+          mapping = ggplot2::aes(
+            x = .data$reference_time,
+            y = .data$observed
+          )
+        ) +
+        ggplot2::geom_point(
+          mapping = ggplot2::aes(alpha = .data$seasonal_onset_alarm),
+          size = size
+        ) +
+        ggplot2::geom_line(linewidth = linewidth)
+    )
+  )
+  # Set 'ask' for plotting device to TRUE
+  oask <- devAskNewPage(ask = TRUE)
+  # ... and clean-up on exit
+  on.exit(devAskNewPage(oask))
+  # ... and the growth rate plots
+  print(
+    object %>%
+      ggplot2::ggplot(
+        mapping = ggplot2::aes(
+          x = .data$reference_time,
+          y = .data$growth_rate,
+          ymin = .data$lower_growth_rate,
+          ymax = .data$upper_growth_rate
+        )
+      ) +
+      ggplot2::geom_point(
+        mapping = ggplot2::aes(alpha = .data$growth_warning),
+        size = size
+      ) +
+      ggplot2::geom_errorbar(
+        mapping = ggplot2::aes(alpha = .data$growth_warning),
+        width = width
+      ) +
+      ggplot2::geom_hline(yintercept = 0, linetype = "dashed")
+  )
 }

R/epi_calendar.R

@@ -34,11 +34,11 @@
 #'
 #' epi_calendar(as.Date("2023-12-01"), start = 40, end = 20)
 #' # Expected output: "2023/2024"
-epi_calendar <- function(date, start = 40, end = 20) {
+epi_calendar <- Vectorize(function(date, start = 40, end = 20) {
   # Compute the current week
-  current_week <- as.integer(format(x = date, "%V"))
+  current_week <- as.integer(format(x = date, "%U"))
 
-  if (current_week <= start && end <= current_week) {
+  if (current_week <= start & end <= current_week) {
     return("out_of_season")
   }
 
@@ -54,4 +54,4 @@ epi_calendar <- function(date, start = 40, end = 20) {
   }
 
   return(ans)
-}
+})