Merge pull request #17 from ssi-dk:telkamp7/issue12

Telkamp7/issue12

DESCRIPTION

@@ -12,7 +12,6 @@ RoxygenNote: 7.2.3
 URL: https://github.com/telkamp7/aedseo, https://telkamp7.github.io/aedseo/
 BugReports: https://github.com/telkamp7/aedseo/issues
 Suggests: 
-    ggplot2,
     ISOweek,
     kableExtra,
     knitr,
@@ -23,6 +22,7 @@ Config/testthat/edition: 3
 Imports: 
     base,
     dplyr,
+    ggplot2,
     lifecycle,
     magrittr,
     purrr,

NAMESPACE

@@ -1,11 +1,17 @@
 # Generated by roxygen2: do not edit by hand
 
+S3method(autoplot,aedseo)
+S3method(autoplot,aedseo_tsd)
+S3method(plot,aedseo)
+S3method(plot,aedseo_tsd)
 S3method(predict,aedseo)
 S3method(summary,aedseo)
 export("%>%")
 export(aedseo)
 export(fit_growth_rate)
 export(tsd)
+importFrom(ggplot2,autoplot)
+importFrom(graphics,plot)
 importFrom(lifecycle,deprecated)
 importFrom(magrittr,"%>%")
 importFrom(rlang,.data)

R/autoplot.R

@@ -0,0 +1,78 @@
+#' Create a complete ggplot appropriate to a particular data type
+#'
+#' @description
+#' `r lifecycle::badge("experimental")`
+#'
+#'  This function generates a complete ggplot object suitable for
+#'  visualizing time series data in an `aedseo_tsd` object. It creates a line
+#'  plot connecting the observations and adds points at each data point.
+#'
+#' @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 ... Additional arguments (not used).
+#'
+#' @return A ggplot object for visualizing the time series data.
+#'
+#' @aliases autoplot
+#'
+#' @examples
+#' # Create an example aedseo_tsd object
+#' aedseo_tsd_object <- tsd(
+#'   observed = c(100, 120, 150, 180, 220, 270),
+#'   time = as.Date(c(
+#'     "2023-01-01",
+#'     "2023-01-02",
+#'     "2023-01-03",
+#'     "2023-01-04",
+#'     "2023-01-05",
+#'     "2023-01-06"
+#'   )),
+#'   time_interval = "day"
+#' )
+#'
+#' # Create a ggplot visualization for the aedseo_tsd object
+#' # autoplot(aedseo_tsd_object)
+#'
+#' # Create an aedseo object
+#' aedseo_object <- aedseo(
+#'   tsd = aedseo_tsd_object,
+#'   k = 3,
+#'   level = 0.95,
+#'   family = "quasipoisson"
+#' )
+#'
+#' # Create a ggplot visualization of growth rates with confidence intervals
+#' # autoplot(aedseo_object, linewidth = 1, alpha = 0.2)
+#' @importFrom ggplot2 autoplot
+#' @rdname autoplot
+#' @method autoplot aedseo_tsd
+#' @export
+autoplot.aedseo_tsd <- function(object, ...) {
+  object %>%
+    ggplot2::ggplot(
+      mapping = ggplot2::aes(
+        x = .data$time,
+        y = .data$observed
+      )
+    ) +
+    ggplot2::geom_point() +
+    ggplot2::geom_line()
+}
+#' @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)
+}

R/plot.R

@@ -0,0 +1,59 @@
+#' Create a complete ggplot appropriate to a particular data type
+#'
+#' @description
+#' `r lifecycle::badge("experimental")`
+#'
+#'  This function generates a complete ggplot object suitable for
+#'  visualizing time series data in an `aedseo_tsd` object. It creates a line
+#'  plot connecting the observations and adds points at each data point.
+#'
+#' @param x An `aedseo_tsd` or `aedseo` object
+#' @param ... Additional arguments passed to specific methods.
+#'
+#' @return A ggplot object for visualizing the time series data.
+#'
+#' @aliases plot
+#'
+#' @seealso [autoplot()]
+#'
+#' @examples
+#' # Create an example aedseo_tsd object
+#' aedseo_tsd_object <- tsd(
+#'   observed = c(100, 120, 150, 180, 220, 270),
+#'   time = as.Date(c(
+#'     "2023-01-01",
+#'     "2023-01-02",
+#'     "2023-01-03",
+#'     "2023-01-04",
+#'     "2023-01-05",
+#'     "2023-01-06"
+#'   )),
+#'   time_interval = "day"
+#' )
+#'
+#' # Create a ggplot visualization for the aedseo_tsd object
+#' plot(aedseo_tsd_object)
+#'
+#' # Create an aedseo object
+#' aedseo_object <- aedseo(
+#'   tsd = aedseo_tsd_object,
+#'   k = 3,
+#'   level = 0.95,
+#'   family = "quasipoisson"
+#' )
+#'
+#' # Create a ggplot visualization of growth rates with confidence intervals
+#' plot(aedseo_object, linewidth = 1, alpha = 0.2)
+#' @importFrom graphics plot
+#' @rdname plot
+#' @method plot aedseo_tsd
+#' @export
+plot.aedseo_tsd <- function(x, ...) {
+  print(autoplot(x, ...))
+}
+#' @rdname plot
+#' @method plot aedseo
+#' @export
+plot.aedseo <- function(x, ...) {
+  print(autoplot(object = x, ...))
+}

vignettes/aedseo_introduction.Rmd

@@ -107,12 +107,8 @@ n <- years * weeks
 # ... and a vector containing the overall time passed
 time_overall <- 1:n
 # Create arbitrary dates
-dates <- as.POSIXct(
-  x = time_overall * 86400 * 7,
-  origin = "2010-01-01",
-  tz = "UTC",
-  format = "%F"
-)
+dates <- seq.Date(from = as.Date("2010-01-01"), by = "week", length.out = n)
+
 
 # Simulate the data
 simulation <- simulate_from_nbinom(t = time_overall, theta = log(1000), phi = 5)