R/plot.r

Defines functions print.gganimintplot is.ggplot a_plot_clone ggplot.data.frame ggplot.default ggplot

Documented in ggplot ggplot.data.frame ggplot.default is.ggplot print.gganimintplot

#' Create a new ggplot plot.
#'
#' \code{ggplot()} initializes a ggplot object. It can be used to
#' declare the input data frame for a graphic and to specify the
#' set of plot aesthetics intended to be common throughout all
#' subsequent layers unless specifically overridden.
#'
#' \code{ggplot()} is typically used to construct a plot
#' incrementally, using the + operator to add layers to the
#' existing ggplot object. This is advantageous in that the
#' code is explicit about which layers are added and the order
#' in which they are added. For complex graphics with multiple
#' layers, initialization with \code{ggplot} is recommended.
#'
#' There are three common ways to invoke \code{ggplot}:
#' \itemize{
#'    \item \code{ggplot(df, aes(x, y, <other aesthetics>))}
#'    \item \code{ggplot(df)}
#'    \item \code{ggplot()}
#'   }
#' The first method is recommended if all layers use the same
#' data and the same set of aesthetics, although this method
#' can also be used to add a layer using data from another
#' data frame. See the first example below. The second
#' method specifies the default data frame to use for the plot,
#' but no aesthetics are defined up front. This is useful when
#' one data frame is used predominantly as layers are added,
#' but the aesthetics may vary from one layer to another. The
#' third method initializes a skeleton \code{ggplot} object which
#' is fleshed out as layers are added. This method is useful when
#' multiple data frames are used to produce different layers, as
#' is often the case in complex graphics.
#'
#' @param data Default dataset to use for plot. If not already a data.frame,
#'   will be converted to one by \code{\link{fortify}}. If not specified,
#'   must be suppled in each layer added to the plot.
#' @param mapping Default list of aesthetic mappings to use for plot.
#'   If not specified, must be suppled in each layer added to the plot.
#' @param ... Other arguments passed on to methods. Not currently used.
#' @param environment If an variable defined in the aesthetic mapping is not
#'   found in the data, ggplot will look for it in this environment. It defaults
#'   to using the environment in which \code{ggplot()} is called.
#' @export
#' @examples
#' df <- data.frame(gp = factor(rep(letters[1:3], each = 10)),
#'                  y = rnorm(30))
#' # Compute sample mean and standard deviation in each group
#' ds <- plyr::ddply(df, "gp", plyr::summarise, mean = mean(y), sd = sd(y))
#'
#' # Declare the data frame and common aesthetics.
#' # The summary data frame ds is used to plot
#' # larger red points in a second geom_point() layer.
#' # If the data = argument is not specified, it uses the
#' # declared data frame from ggplot(); ditto for the aesthetics.
#' ggplot(df, aes(x = gp, y = y)) +
#'    geom_point() +
#'    geom_point(data = ds, aes(y = mean),
#'               colour = 'red', size = 3)
#' # Same plot as above, declaring only the data frame in ggplot().
#' # Note how the x and y aesthetics must now be declared in
#' # each geom_point() layer.
#' ggplot(df) +
#'    geom_point(aes(x = gp, y = y)) +
#'    geom_point(data = ds, aes(x = gp, y = mean),
#'                  colour = 'red', size = 3)
#' # Set up a skeleton ggplot object and add layers:
#' ggplot() +
#'   geom_point(data = df, aes(x = gp, y = y)) +
#'   geom_point(data = ds, aes(x = gp, y = mean),
#'                         colour = 'red', size = 3) +
#'   geom_errorbar(data = ds, aes(x = gp, y = mean,
#'                     ymin = mean - sd, ymax = mean + sd),
#'                     colour = 'red', width = 0.4)
ggplot <- function(data = NULL, mapping = aes(), ...,
                   environment = parent.frame()) {
  UseMethod("ggplot")
}

#' @export
#' @rdname ggplot
#' @usage NULL
ggplot.default <- function(data = NULL, mapping = aes(), ...,
                           environment = parent.frame()) {
  ggplot.data.frame(fortify(data, ...), mapping, environment = environment)
}

#' @export
#' @rdname ggplot
#' @usage NULL
ggplot.data.frame <- function(data, mapping = aes(), ...,
                              environment = parent.frame()) {
  if (!missing(mapping) && !inherits(mapping, "uneval")) {
    stop("Mapping should be created with `aes() or `aes_()`.", call. = FALSE)
  }

  p <- structure(list(
    data = data,
    layers = list(),
    scales = a_scales_list(),
    mapping = mapping,
    theme = list(),
    coordinates = coord_cartesian(),
    facet = facet_null(),
    plot_env = environment
  ), class = c("gganimint", "gganimintplot"))

  p$labels <- make_labels(mapping)

  set_last_plot(p)
  p
}

a_plot_clone <- function(plot) {
  p <- plot
  p$scales <- plot$scales$clone()

  p
}

#' Reports whether x is a ggplot object
#' @param x An object to test
#' @keywords internal
#' @export
is.ggplot <- function(x) inherits(x, "gganimintplot")

#' Draw plot on current graphics device.
#'
#' @param x plot to display
#' @param newpage draw new (empty) page first?
#' @param vp viewport to draw plot in
#' @param ... other arguments not used by this method
#' @keywords hplot
#' @return Invisibly returns the result of \code{\link{ggplot_build}}, which
#'   is a list with components that contain the plot itself, the data,
#'   information about the scales, panels etc.
#' @export
#' @method print gganimintplot
print.gganimintplot <- function(x, newpage = is.null(vp), vp = NULL, ...) {
  set_last_plot(x)
  if (newpage) grid.newpage()

  # Record dependency on 'animint2' on the display list
  # (AFTER grid.newpage())
  grDevices::recordGraphics(
    requireNamespace("animint2", quietly = TRUE),
    list(),
    getNamespace("animint2")
  )

  data <- ggplot_build(x)

  gtable <- ggplot_gtable(data)
  if (is.null(vp)) {
    grid.draw(gtable)
  } else {
    if (is.character(vp)) seekViewport(vp) else pushViewport(vp)
    grid.draw(gtable)
    upViewport()
  }

  invisible(data)
}
#' @rdname print.gganimintplot
#' @method plot gganimintplot
#' @export
plot.gganimintplot <- print.gganimintplot

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animint2 documentation built on March 18, 2022, 7:29 p.m.