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#' Save plot as a static image
#'
#' Static image exporting via [the kaleido python
#' package](https://github.com/plotly/Kaleido/). `kaleido()` imports
#' kaleido into a \pkg{reticulate}d Python session and returns a `$transform()`
#' method for converting R plots into static images. `save_image()` provides a convenience wrapper around `kaleido()$transform()`.
#'
#' @section Installation:
#'
#' `kaleido()` requires [the kaleido python
#' package](https://github.com/plotly/Kaleido/) to be usable via the \pkg{reticulate} package. Here is a recommended way to do the installation:
#'
#' ```
#' install.packages('reticulate')
#' reticulate::install_miniconda()
#' reticulate::conda_install('r-reticulate', 'python-kaleido')
#' reticulate::conda_install('r-reticulate', 'plotly', channel = 'plotly')
#' reticulate::use_miniconda('r-reticulate')
#' ```
#'
#' @param ... not currently used.
#' @param p a plot object.
#' @param file a file path with a suitable file extension (png, jpg, jpeg,
#' webp, svg, or pdf).
#' @param width,height The width/height of the exported image in layout
#' pixels. If `scale` is 1, this will also be the width/height of the exported
#' image in physical pixels.
#' @param scale The scale factor to use when exporting
#' the figure. A scale factor larger than 1.0 will increase the image
#' resolution with respect to the figure's layout pixel dimensions. Whereas as
#' scale factor of less than 1.0 will decrease the image resolution.
#' @export
#' @return For `save_image()`, the generated `file`. For `kaleido()`, an environment that contains:
#' * `transform()`: a function to convert plots objects into static images. This function has the same signature (i.e., arguments) as `save_image()`
#' * `shutdown()`: a function for shutting down any currently running subprocesses
#' that were launched via `transform()`
#' * `scope`: a reference to the underlying `kaleido.scopes.plotly.PlotlyScope`
#' python object. Modify this object to customize the underlying Chromium
#' subprocess and/or configure other details such as URL to plotly.js, MathJax, etc.
#' @examplesIf interactive() || !identical(.Platform$OS.type, "windows")
#'
#' \dontrun{
#' # Save a single image
#' p <- plot_ly(x = 1:10)
#' tmp <- tempfile(fileext = ".png")
#' save_image(p, tmp)
#' file.show(tmp)
#'
#' # Efficiently save multiple images
#' scope <- kaleido()
#' for (i in 1:5) {
#' scope$transform(p, tmp)
#' }
#' # Remove and garbage collect to remove
#' # R/Python objects and shutdown subprocesses
#' rm(scope); gc()
#' }
#'
save_image <- function(p, file, ..., width = NULL, height = NULL, scale = NULL) {
kaleido()$transform(
p, file, ..., width = width, height = height, scale = scale
)
}
#' @rdname save_image
#' @export
kaleido <- function(...) {
if (!rlang::is_installed("reticulate")) {
stop("`kaleido()` requires the reticulate package.")
}
if (!reticulate::py_available(initialize = TRUE)) {
stop("`kaleido()` requires `reticulate::py_available()` to be `TRUE`. Do you need to install python?")
}
py <- reticulate::py
scope_name <- paste0("scope_", new_id())
py[[scope_name]] <- reticulate::import("kaleido")$scopes$plotly$PlotlyScope(
plotlyjs = plotlyMainBundlePath()
)
scope <- py[[scope_name]]
mapbox <- Sys.getenv("MAPBOX_TOKEN", NA)
if (!is.na(mapbox)) {
scope$mapbox_access_token <- mapbox
}
res <- list2env(list(
scope = scope,
# https://github.com/plotly/Kaleido/blob/6a46ecae/repos/kaleido/py/kaleido/scopes/plotly.py#L78-L106
transform = function(p, file = "figure.png", ..., width = NULL, height = NULL, scale = NULL) {
# Perform JSON conversion exactly how the R package would do it
# (this is essentially plotly_json(), without the additional unneeded info)
# and attach as an attribute on the python scope object
scope[["_last_plot"]] <- to_JSON(
plotly_build(p)$x[c("data", "layout", "config")]
)
# On the python side, _last_plot is a string, so use json.loads() to
# convert to dict(). This should be fine since json is a dependency of the
# BaseScope() https://github.com/plotly/Kaleido/blob/586be5/repos/kaleido/py/kaleido/scopes/base.py#L2
transform_cmd <- sprintf(
"%s.transform(sys.modules['json'].loads(%s._last_plot), format='%s', width=%s, height=%s, scale=%s)",
scope_name, scope_name, tools::file_ext(file),
reticulate::r_to_py(width), reticulate::r_to_py(height),
reticulate::r_to_py(scale)
)
# Write the base64 encoded string that transform() returns to disk
# https://github.com/plotly/Kaleido/blame/master/README.md#L52
reticulate::py_run_string(
sprintf("import sys; open('%s', 'wb').write(%s)", file, transform_cmd)
)
invisible(file)
},
# Shutdown the kaleido subprocesses
# https://github.com/plotly/Kaleido/blob/586be5c/repos/kaleido/py/kaleido/scopes/base.py#L71-L72
shutdown = function() {
reticulate::py_run_string(paste0(scope_name, ".__del__()"))
}
))
# Shutdown subprocesses and delete python scope when
# this object is garbage collected by R
reg.finalizer(res, onexit = TRUE, function(x) {
x$shutdown()
reticulate::py_run_string(paste("del", scope_name))
})
class(res) <- "kaleidoScope"
res
}
#' Print method for kaleido
#'
#' S3 method for [kaleido()].
#'
#' @param x a [kaleido()] object.
#' @param ... currently unused.
#' @export
#' @importFrom utils capture.output
#' @keywords internal
print.kaleidoScope <- function(x, ...) {
args <- formals(x$transform)
cat("$transform: function(", paste(names(args), collapse = ", "), ")\n", sep = "")
cat("$shutdown: function()\n")
cat("$scope: ", utils::capture.output(x$scope))
}
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