R/ggpackets.R

In ggpackets: Package Plot Layers for Easier Portability and Modularization

#' @description
#' Create groups of ggplot layers that can be easily migrated from one plot to
#' another, reducing redundant code and improving the ability to format many
#' plots that draw from the same source ggpacket layers.
#'
#' @examples
#' library(ggplot2)
#'
#' # Prep a tidy data.frame to plot with
#' airquality_long <- rbind(
#'   data.frame(
#'     airquality[,c("Month", "Day")],
#'     Variable = "Temp",
#'     Measurement = airquality$Temp),
#'   data.frame(
#'     airquality[,c("Month", "Day")],
#'     Variable = "Ozone",
#'     Measurement = airquality$Ozone))
#'
#' # Build our new composite ggplot geom
#' geom_error_line <- ggpacket() %+%
#'   geom_ribbon(
#'     .id = "box",
#'     mapping = aes(fill = ..color..),
#'     stat = 'summary',
#'     fun = mean,
#'     fun.min = ~mean(.) - sd(.),
#'     fun.max = ~mean(.) + sd(.),
#'     alpha = 0.15,
#'     color = NA) %+%
#'   geom_line(
#'     .id = "line",
#'     stat = 'summary',
#'     fun = mean,
#'     alpha = 0.8)
#'
#' # Try it out!
#' ggplot(airquality_long) +
#'   aes(x = round((Month * 30 + Day) / 4), y = Measurement, color = Variable) +
#'   geom_error_line(na.rm = TRUE, line.size = 1.5) +
#'   scale_y_log10() +
#'   labs(x = "Week")
#'
#' # for further examples, check out the vignettes
#' vignette(package = "ggpackets")
#'
"_PACKAGE"