Update Docs

Author: ndevln

DESCRIPTION

@@ -12,7 +12,9 @@ Description: Create epicurves or epigantt charts in 'ggplot2'. Prepare
     (A) seasonal date alignment for respiratory disease surveillance, 
     (B) date-based case binning based on specified time intervals like
     isoweek, epiweek, month and more, (C) automated detection and marking
-    of the new year based on the date/datetime axis of the 'ggplot2'.
+    of the new year based on the date/datetime axis of the 'ggplot2'. 
+    An introduction on how to use epicurves can be found on the US CDC website 
+    (2012, <https://www.cdc.gov/training/quicklearns/epimode/index.html>).
 License: GPL (>= 3)
 URL: https://ggsurveillance.biostats.dev,
     https://github.com/biostats-dev/ggsurveillance

R/align_dates_seasonal.R

@@ -144,6 +144,13 @@ align_dates_seasonal <- function(
 
 #' @rdname align_dates_seasonal
 #' @importFrom tsibble as_tsibble fill_gaps
+#' @import dplyr
+#' @import lubridate
+#' @import ISOweek
+#' @import rlang
+#' @importFrom tidyselect eval_select
+#' @importFrom stringr str_pad
+#' @importFrom utils tail
 #' @export
 
 align_and_bin_dates_seasonal <- function(
@@ -196,14 +203,6 @@ align_and_bin_dates_seasonal <- function(
     )
 }
 
-#' @import dplyr
-#' @import lubridate
-#' @import ISOweek
-#' @import rlang
-#' @importFrom tidyselect eval_select
-#' @importFrom stringr str_pad
-#' @importFrom utils tail
-
 .is_current_season <- function(season) (season == (sort(season) |> utils::tail(n = 1)))
 
 .check_align_df <- function(df, dates_from) {
@@ -321,7 +320,6 @@ align_and_bin_dates_seasonal <- function(
     )
 }
 
-
 .coerce_to_date <- function(dates) {
   date_iso_pattern <- "^\\d{4}-\\d{2}-\\d{2}$"
   year_month_pattern <- "^\\d{4}-\\d{2}$"

R/geom_epicurve.R

@@ -39,7 +39,7 @@
 #' @details
 #' Epi Curves are a public health tool for outbreak investigation. For more details see the references.
 #'
-#' @return A ggplot2 layer that can be added to a plot
+#' @return A `ggplot2` geom layer that can be added to a plot
 #' @seealso [scale_y_cases_5er()], [geom_vline_year()]
 #' @export
 #'
@@ -65,6 +65,7 @@
 #'   labs(title = "Epicurve Example") +
 #'   scale_y_cases_5er() +
 #'   scale_x_date(date_breaks = "4 weeks", date_labels = "W%V'%g") + # Correct ISOWeek labels week'year
+#'   coord_equal(ratio = 7) + # Use coord_equal for square boxes. 'ratio' are the days per week.
 #'   theme_bw()
 #'
 #' # Categorical epicurve

R/geom_epigantt.R

@@ -4,6 +4,7 @@
 #' `xmin` and `xmax`. Each case draws a single graphical object.
 #'
 #' @inheritParams ggplot2::geom_linerange
+#' @return A `ggplot2` geom layer that can be added to a plot
 #'
 #' @export
 geom_epigantt <- function(mapping = NULL, data = NULL,

R/reexport-tidyr.R

@@ -12,7 +12,7 @@
 #'
 #' @inheritParams tidyr::uncount
 #'
-#' @return A data frame with rows duplicated according to weights.
+#' @return A `data.frame` with rows duplicated according to weights.
 #' @examples
 #' df <- data.frame(x = c("a", "b"), n = c(2, 3))
 #' df |> uncount(n)

R/scale_cases_5er.R

@@ -13,18 +13,16 @@
 #' or [ggplot2::expansion()] to modify
 #' @param ... Additional arguments passed on to [base::pretty()].
 #'
-#' @return A **ggplot2** scale object that can be added to a plot.
+#' @return A `ggplot2` scale object that can be added to a plot.
 #' @seealso [geom_epicurve()], [ggplot2::scale_y_continuous()], [base::pretty()]
 #'
 #' @examples
-#' \dontrun{
 #' library(ggplot2)
 #'
 #' data <- data.frame(date = as.Date("2024-01-01") + 0:30)
 #' ggplot(data, aes(x = date)) +
 #'   geom_epicurve(date_resolution = "week") +
 #'   scale_y_cases_5er()
-#' }
 #' @importFrom scales censor
 #' @export
 

data-raw/figures.R

@@ -47,4 +47,3 @@ ggplot(df_flu_aligned, aes(x = date_aligned, y = Incidence)) +
   theme(legend.position = c(0.2, 0.8))
 
 ggsave("man/figures/seasonal_plot_readme.png", width = 6, height = 3.5, dpi = 600)
-