Files
shiny/R/render-plot.R
2015-04-16 23:40:07 -05:00

387 lines
13 KiB
R

#' Plot Output
#'
#' Renders a reactive plot that is suitable for assigning to an \code{output}
#' slot.
#'
#' The corresponding HTML output tag should be \code{div} or \code{img} and have
#' the CSS class name \code{shiny-plot-output}.
#'
#' @seealso For the corresponding client-side output function, and example
#' usage, see \code{\link{plotOutput}}. For more details on how the plots are
#' generated, and how to control the output, see \code{\link{plotPNG}}.
#'
#' @param expr An expression that generates a plot.
#' @param width,height The width/height of the rendered plot, in pixels; or
#' \code{'auto'} to use the \code{offsetWidth}/\code{offsetHeight} of the HTML
#' element that is bound to this plot. You can also pass in a function that
#' returns the width/height in pixels or \code{'auto'}; in the body of the
#' function you may reference reactive values and functions. When rendering an
#' inline plot, you must provide numeric values (in pixels) to both
#' \code{width} and \code{height}.
#' @param res Resolution of resulting plot, in pixels per inch. This value is
#' passed to \code{\link{png}}. Note that this affects the resolution of PNG
#' rendering in R; it won't change the actual ppi of the browser.
#' @param ... Arguments to be passed through to \code{\link[grDevices]{png}}.
#' These can be used to set the width, height, background color, etc.
#' @param env The environment in which to evaluate \code{expr}.
#' @param quoted Is \code{expr} a quoted expression (with \code{quote()})? This
#' is useful if you want to save an expression in a variable.
#' @param func A function that generates a plot (deprecated; use \code{expr}
#' instead).
#'
#' @export
renderPlot <- function(expr, width='auto', height='auto', res=72, ...,
env=parent.frame(), quoted=FALSE, func=NULL) {
if (!is.null(func)) {
shinyDeprecated(msg="renderPlot: argument 'func' is deprecated. Please use 'expr' instead.")
} else {
installExprFunction(expr, "func", env, quoted)
}
args <- list(...)
if (is.function(width))
widthWrapper <- reactive({ width() })
else
widthWrapper <- NULL
if (is.function(height))
heightWrapper <- reactive({ height() })
else
heightWrapper <- NULL
# If renderPlot isn't going to adapt to the height of the div, then the
# div needs to adapt to the height of renderPlot. By default, plotOutput
# sets the height to 400px, so to make it adapt we need to override it
# with NULL.
outputFunc <- plotOutput
if (!identical(height, 'auto')) formals(outputFunc)['height'] <- list(NULL)
return(markRenderFunction(outputFunc, function(shinysession, name, ...) {
if (!is.null(widthWrapper))
width <- widthWrapper()
if (!is.null(heightWrapper))
height <- heightWrapper()
# Note that these are reactive calls. A change to the width and height
# will inherently cause a reactive plot to redraw (unless width and
# height were explicitly specified).
prefix <- 'output_'
if (width == 'auto')
width <- shinysession$clientData[[paste(prefix, name, '_width', sep='')]];
if (height == 'auto')
height <- shinysession$clientData[[paste(prefix, name, '_height', sep='')]];
if (is.null(width) || is.null(height) || width <= 0 || height <= 0)
return(NULL)
# Resolution multiplier
pixelratio <- shinysession$clientData$pixelratio
if (is.null(pixelratio))
pixelratio <- 1
coordmap <- NULL
plotFunc <- function() {
# Actually perform the plotting
result <- withVisible(func())
coordmap <<- NULL
if (result$visible) {
# Use capture.output to squelch printing to the actual console; we
# are only interested in plot output
# Special case for ggplot objects - need to capture coordmap
if (inherits(result$value, "ggplot")) {
capture.output(coordmap <<- getGgplotCoordmap(result$value, pixelratio))
} else {
capture.output(print(result$value))
}
}
if (is.null(coordmap)) {
coordmap <<- getPrevPlotCoordmap(width, height)
}
}
outfile <- do.call(plotPNG, c(plotFunc, width=width*pixelratio,
height=height*pixelratio, res=res*pixelratio, args))
on.exit(unlink(outfile))
# Return a list of attributes for the img
return(list(
src=shinysession$fileUrl(name, outfile, contentType='image/png'),
width=width, height=height, coordmap=coordmap
))
}))
}
# Get a coordmap for the previous plot made with base graphics.
# Requires width and height of output image, in pixels.
# Must be called before the graphics device is closed.
getPrevPlotCoordmap <- function(width, height) {
usrCoords <- par('usr')
usrBounds <- usrCoords
if (par('xlog')) {
usrBounds[c(1,2)] <- 10 ^ usrBounds[c(1,2)]
}
if (par('ylog')) {
usrBounds[c(3,4)] <- 10 ^ usrBounds[c(3,4)]
}
# Wrapped in double list because other types of plots can have multiple panels.
list(list(
# Bounds of the plot area, in data space
domain = list(
left = usrCoords[1],
right = usrCoords[2],
bottom = usrCoords[3],
top = usrCoords[4]
),
# The bounds of the plot area, in DOM pixels
range = list(
left = grconvertX(usrBounds[1], 'user', 'nfc') * width - 1,
right = grconvertX(usrBounds[2], 'user', 'nfc') * width - 1,
bottom = (1-grconvertY(usrBounds[3], 'user', 'nfc')) * height - 1,
top = (1-grconvertY(usrBounds[4], 'user', 'nfc')) * height - 1
),
log = list(
x = if (par('xlog')) 10 else NULL,
y = if (par('ylog')) 10 else NULL
))
)
}
# Print a ggplot object and return a coordmap for it.
getGgplotCoordmap <- function(p, pixelratio) {
if (!inherits(p, "ggplot"))
return(NULL)
# A modified version of print.ggplot which returns the built ggplot object
# as well as the gtable grob.
print_ggplot <- function(x) {
grid::grid.newpage()
build <- ggplot2::ggplot_build(x)
gtable <- ggplot2::ggplot_gtable(build)
grid::grid.draw(gtable)
list(
build = build,
gtable = gtable
)
}
# Given a built ggplot object and corresponding gtable, return x and y domains
# (data space coords) and ranges (pixel coords).
find_panel_info <- function(b) {
layout <- b$panel$layout
# Convert factor to numbers
layout$PANEL <- as.integer(as.character(layout$PANEL))
# Names of facets
facet <- b$plot$facet
facet_vars <- NULL
if (inherits(facet, "grid")) {
facet_vars <- vapply(c(facet$cols, facet$rows), as.character, character(1))
} else if (inherits(facet, "wrap")) {
facet_vars <- vapply(b$plot$facet$facets, as.character, character(1))
}
# Iterate over each row in the layout data frame
lapply(seq_len(nrow(layout)), function(i) {
# Slice out one row
l <- layout[i, ]
scale_x <- l$SCALE_X
scale_y <- l$SCALE_Y
vars <- lapply(facet_vars, function(var) {
list(name = var, value = l[[var]])
})
list(
panel = l$PANEL,
row = l$ROW,
col = l$COL,
vars = vars,
scale_x = scale_x,
scale_y = scale_x,
log = check_log_scales(b, scale_x, scale_y),
domain = find_panel_domain(b, l$PANEL, scale_x, scale_y)
)
})
}
# Given a single range object (representing the data domain) from a built
# ggplot object, return the domain.
find_panel_domain <- function(b, panel_num, scalex_num = 1, scaley_num = 1) {
range <- b$panel$ranges[[panel_num]]
res <- list(
left = range$x.range[1],
right = range$x.range[2],
bottom = range$y.range[1],
top = range$y.range[2]
)
# Check for reversed scales
xscale <- b$panel$x_scales[[scalex_num]]
yscale <- b$panel$y_scales[[scaley_num]]
if (!is.null(xscale$trans) && xscale$trans$name == "reverse") {
res$left <- -res$left
res$right <- -res$right
}
if (!is.null(yscale$trans) && yscale$trans$name == "reverse") {
res$top <- -res$top
res$bottom <- -res$bottom
}
res
}
# Given built ggplot object, return object with the log base for x and y if
# there are log scales or coord transforms.
check_log_scales <- function(b, scalex_num = 1, scaley_num = 1) {
# Given a vector of transformation names like c("log-10", "identity"),
# return the first log base, like 10. If none are present, return NULL.
extract_log_base <- function(names) {
names <- names[grepl("^log-", names)]
if (length(names) == 0)
return(NULL)
names <- names[1]
as.numeric(sub("^log-", "", names))
}
# Look for log scales and log coord transforms. People shouldn't use both.
x_names <- character(0)
y_names <- character(0)
# Continuous scales have a trans; discrete ones don't
if (!is.null(b$panel$x_scales[[scalex_num]]$trans))
x_names <- b$panel$x_scales[[scalex_num]]$trans$name
if (!is.null(b$panel$y_scales[[scaley_num]]$trans))
y_names <- b$panel$y_scales[[scaley_num]]$trans$name
coords <- b$plot$coordinates
if (!is.null(coords$trans)) {
if (!is.null(coords$trans$x))
x_names <- c(x_names, coords$trans$x$name)
if (!is.null(coords$trans$y))
y_names <- c(y_names, coords$trans$y$name)
}
# Keep only scale/trans names that start with "log-"
x_names <- x_names[grepl("^log-", x_names)]
y_names <- y_names[grepl("^log-", y_names)]
# Extract the log base from the trans name -- a string like "log-10".
list(
x = extract_log_base(x_names),
y = extract_log_base(y_names)
)
}
# Given a gtable object, return the x and y ranges (in pixel dimensions)
find_panel_ranges <- function(g, pixelratio) {
# Given a vector of unit objects, return logical vector indicating which ones
# are "null" units. These units use the remaining available width/height --
# that is, the space not occupied by elements that have an absolute size.
is_null_unit <- function(x) {
vapply(x, FUN.VALUE = logical(1), function(u) {
isTRUE(attr(u, "unit", exact = TRUE) == "null")
})
}
# Convert a unit (or vector of units) to a numeric vector of pixel sizes
h_px <- function(x) as.numeric(grid::convertHeight(x, "native"))
w_px <- function(x) as.numeric(grid::convertWidth(x, "native"))
# Given a vector of relative sizes (in grid units), and a function for
# converting grid units to numeric pixels, return a numeric vector of
# pixel sizes.
find_px_sizes <- function(rel_sizes, unit_to_px) {
# Total pixels (in height or width)
total_px <- unit_to_px(grid::unit(1, "npc"))
# Calculate size of all panel(s) together. Panels (and only panels) have
# null size.
null_idx <- is_null_unit(rel_sizes)
# All the absolute heights. At this point, null heights are 0. We need to
# calculate them separately and add them in later.
px_sizes <- unit_to_px(rel_sizes)
# Total size for panels is image size minus absolute (non-panel) elements
panel_px_total <- total_px - sum(px_sizes)
# Divide up the total panel size up into the panels (scaled by size)
panel_sizes_rel <- as.numeric(rel_sizes[null_idx])
panel_sizes_rel <- panel_sizes_rel / sum(panel_sizes_rel)
px_sizes[null_idx] <- panel_px_total * panel_sizes_rel
abs(px_sizes)
}
px_heights <- find_px_sizes(g$heights, h_px)
px_widths <- find_px_sizes(g$widths, w_px)
# Convert to absolute pixel positions
x_pos <- cumsum(px_widths)
y_pos <- cumsum(px_heights)
# Match up the pixel dimensions to panels
layout <- g$layout
# For panels:
# * For facet_wrap, they'll be named "panel-1", "panel-2", etc.
# * For no facet or facet_grid, they'll just be named "panel". For
# facet_grid, we need to re-order the layout table. Assume that panel
# numbers go from left to right, then next row.
# Assign a number to each panel, corresponding to PANEl in the built ggplot
# object.
layout <- layout[grepl("^panel", layout$name), ]
layout <- layout[order(layout$t, layout$l), ]
layout$panel <- seq_len(nrow(layout))
# When using a HiDPI client on a Linux server, the pixel
# dimensions are doubled, so we have to divide the dimensions by
# `pixelratio`. When a HiDPI client is used on a Mac server (with
# the quartz device), the pixel dimensions _aren't_ doubled, even though
# the image has double size. In the latter case we don't have to scale the
# numbers down.
pix_ratio <- 1
if (!grepl("^quartz", names(dev.cur()))) {
pix_ratio <- pixelratio
}
# Return list of lists, where each inner list has left, right, top, bottom
# values for a panel
lapply(seq_len(nrow(layout)), function(i) {
p <- layout[i, , drop = FALSE]
list(
left = x_pos[p$l - 1] / pix_ratio,
right = x_pos[p$r] / pix_ratio,
bottom = y_pos[p$b] / pix_ratio,
top = y_pos[p$t - 1] / pix_ratio
)
})
}
res <- print_ggplot(p)
# Get info from built ggplot object
info <- find_panel_info(res$build)
# Get ranges from gtable - it's possible for this to return more elements than
# info, because it calculates positions even for panels that aren't present.
# This can happen with facet_wrap.
ranges <- find_panel_ranges(res$gtable, pixelratio)
for (i in seq_along(info)) {
info[[i]]$range <- ranges[[i]]
}
info
}