diff --git a/.gitignore b/.gitignore
index 9db8f3c3..a9c22539 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1,2 +1,5 @@
*.ipynb_checkpoints
.Rproj.user
+.RData
+.Rhistory
+*.pdf
diff --git a/DESCRIPTION b/DESCRIPTION
index 668a1af7..a289cf8a 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -21,3 +21,8 @@ Imports:
jsonlite (>= 0.9.6),
uuid,
digest
+Collate:
+ 'options.R'
+ 'execution.r'
+ 'help.r'
+ 'kernel.r'
diff --git a/Demo.ipynb b/Demo.ipynb
index 2a296228..8ff720d4 100644
--- a/Demo.ipynb
+++ b/Demo.ipynb
@@ -15,7 +15,7 @@
},
"outputs": [],
"source": [
- "a=8"
+ "a <- 8"
]
},
{
@@ -26,7 +26,7 @@
},
"outputs": [],
"source": [
- "b=4:59"
+ "b <- 4:59"
]
},
{
@@ -57,7 +57,7 @@
}
],
"source": [
- "a+b"
+ "a + b"
]
},
{
@@ -83,7 +83,7 @@
}
],
"source": [
- "print(\"Hello world! Love, R in IPython.\")"
+ "print('Hello world! Love, R in IPython.')"
]
},
{
@@ -102,10 +102,10 @@
"outputs": [
{
"ename": "ERROR",
- "evalue": "Error in eval(expr, envir, enclos): object 'h' not found\n",
+ "evalue": "Error in eval(expr, envir, enclos): Objekt 'h' nicht gefunden\n",
"output_type": "error",
"traceback": [
- "Error in eval(expr, envir, enclos): object 'h' not found\n"
+ "Error in eval(expr, envir, enclos): Objekt 'h' nicht gefunden\n"
]
}
],
@@ -129,8 +129,210 @@
"outputs": [
{
"data": {
+ "application/pdf": [
+ "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"
+ ],
"image/png": [
- 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"
+ ],
+ "image/svg+xml": [
+ "\n",
+ "\n"
]
},
"metadata": {},
diff --git a/Display.ipynb b/Display.ipynb
index 810be5d8..8cec4f24 100644
--- a/Display.ipynb
+++ b/Display.ipynb
@@ -36,7 +36,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
- "Plotting in R is now displayed automatically, but if you want to display a PNG from another source, this is how to do it:"
+ "Plotting in R is displayed automatically, but if you want to display a PNG from another source, this is how to do it:"
]
},
{
@@ -60,7 +60,7 @@
{
"data": {
"image/png": [
- 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6F22qR/QrrrM478VL+0/ca2/cwNTj4GHfmuH032meyRJHYHEEFkdgcQQWR2BxBBZHYHEEFkdgcQQWR2BxBBZHYHEEFkdgcQQWR2BxBBZHYHE9M3Bx7dc+cvNirmzTEwMffwnXyY9cvZgr2/TEwMdfwmUmzfbyYq5s0xMD/++3izdtNx5ezJVtenDgEx+5ejFXtiGwyxdzZRsCu3wxV7bpwYFPfA929WKubNODAyeuoj28mCvb9MzAPQiBxRFYHIHFEVgcgcURWByBxRFYHIHFEVgcgcURWByBxRFYHIHFEVgcgcURWNx/AYHGoyPN6vK2AAAAAElFTkSuQmCC"
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"
]
},
"metadata": {},
@@ -71,7 +71,78 @@
"png('Rplot.png')\n",
"plot(1:10, 1:10)\n",
"dev.off()\n",
- "display_png(filename='Rplot.png')"
+ "display_png(file = 'Rplot.png')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The following will result in the preferred image format being chosen by the frontend:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": [
+ "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"
+ ],
+ "image/svg+xml": [
+ ""
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 50,
+ "width": 50
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "display_images(\n",
+ " svg = '',\n",
+ " png = list(file = 'Rplot.png', width = 50, height = 50))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "The best format is chosen according to the frontend’s setting. Configuring this is coming soon."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": [
+ "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"
+ ]
+ },
+ "metadata": {
+ "image/png": {
+ "height": 50,
+ "width": 50
+ }
+ },
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "display_images(png = list(file = 'Rplot.png', width = 50, height = 50))"
]
}
],
diff --git a/IRkernel.Rproj b/IRkernel.Rproj
new file mode 100644
index 00000000..828602dd
--- /dev/null
+++ b/IRkernel.Rproj
@@ -0,0 +1,18 @@
+Version: 1.0
+
+RestoreWorkspace: Default
+SaveWorkspace: Default
+AlwaysSaveHistory: Default
+
+EnableCodeIndexing: Yes
+UseSpacesForTab: Yes
+NumSpacesForTab: 4
+Encoding: UTF-8
+
+RnwWeave: Sweave
+LaTeX: pdfLaTeX
+
+BuildType: Package
+PackageUseDevtools: Yes
+PackageInstallArgs: --no-multiarch --with-keep.source
+PackageRoxygenize: rd,collate,namespace
diff --git a/NAMESPACE b/NAMESPACE
index d592584e..f2c0a24f 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -7,9 +7,12 @@ export(set_plot_options)
import(digest)
import(evaluate)
import(methods)
+import(repr)
import(rzmq)
import(uuid)
importFrom(IRdisplay,display)
+importFrom(IRdisplay,display_alternatives)
importFrom(IRdisplay,display_png)
+importFrom(base64enc,base64encode)
importFrom(jsonlite,fromJSON)
importFrom(jsonlite,toJSON)
diff --git a/R/execution.r b/R/execution.r
index 3160ef28..85a323a1 100644
--- a/R/execution.r
+++ b/R/execution.r
@@ -1,28 +1,7 @@
-displayenv = environment(display)
-
-plot_options=new.env() # environment for storing plot-options
-
-#'Set options for plotting
-#'
-#'IRkernel displays plots in the notebook with calls to png().
-#'This function allows to set the variables that will be passed on to
-#'png(), for example width or height, see help(png).
-#' @param ... options that will be passed to png()
-#' @export
-set_plot_options <- function(...){
- options <- list(...)
- for(opt in names(options)){
- assign( opt, options[[opt]], plot_options )
- }
-}
+#' @include options.R
+NULL
-#'Get options for plotting
-#'
-#'Use set_plot_options() for modifying.
-#' @export
-get_plot_options <- function(){
- return(as.list(plot_options))
-}
+displayenv = environment(display)
lappend <- function(lst, obj) {
# I hope this isn't the best way to do this.
@@ -43,6 +22,11 @@ plot_builds_upon <- function(prev, current) {
return((lcurrent >= lprev) && (identical(current[[1]][1:lprev], prev[[1]][1:lprev])))
}
+# needed to easily encode reprs as json.
+setOldClass('repr')
+asJSON <- jsonlite:::asJSON
+setMethod('asJSON', 'repr', function(x, ...) jsonlite:::asJSON(structure(x, class = NULL, repr.format = NULL), ...))
+
Executor = setRefClass("Executor",
fields=c("execution_count", "payload", "err", "interrupted", "kernel",
"last_recorded_plot"),
@@ -83,12 +67,12 @@ execute = function(request) {
payload <<- lappend(payload, list(source='page', text=paste(text, collapse="\n")))
})
- send_plot = function(plotobj) {
- tf = tempfile(fileext='.png')
- do.call(png, c(list(filename=tf), get_plot_options()))
- replayPlot(plotobj)
- dev.off()
- display_png(file=tf)
+ send_plot <- function(plotobj) {
+ params <- list()
+ for (mime in getOption('jupyter.plot_mimetypes')) {
+ params[[mime]] <- mime2repr[[mime]](plotobj)
+ }
+ display(params)
}
err <<- list()
diff --git a/R/help.r b/R/help.r
index 4af07d5e..a96a4a14 100644
--- a/R/help.r
+++ b/R/help.r
@@ -1,17 +1,33 @@
-#'An R kernel for IPython.
+#' An R kernel for IPython.
+#'
+#' IPython's modern interfaces, including the IPython Notebook, speak a JSON+ZMQ
+#' protocol to a 'kernel' which is responsible for executing code. This protocol
+#' is language agnostic, so other languages can take advantage of IPython's rich
+#' UI by implementing a kernel. This package is a kernel for the R language.
+#'
+#' @section Options:
+#'
+#' The following can be set/read via \code{options(opt.name = ...)} / \code{getOption('opt.name')}
+#'
+#' \describe{
+#' \item{\code{jupyter.plot_mimetypes}}{
+#' The plot formats emitted to the frontend when a plot is displayed.
+#' (default: image/png, application/pdf, and image/svg+xml)
+#' }
+#' }
#'
-#'IPython's modern interfaces, including the IPython Notebook, speak a JSON+ZMQ
-#'protocol to a 'kernel' which is responsible for executing code. This protocol
-#'is language agnostic, so other languages can take advantage of IPython's rich
-#'UI by implementing a kernel. This package is a kernel for the R language.
#' @export main
+#'
+#' @import repr
#' @import methods
#' @import rzmq
#' @import uuid
#' @import digest
#' @import evaluate
#' @importFrom jsonlite fromJSON toJSON
-#' @importFrom IRdisplay display display_png
+#' @importFrom base64enc base64encode
+#' @importFrom IRdisplay display display_png display_alternatives
+#'
#' @docType package
#' @name IRkernel
#' @aliases IRkernel IRkernel-package
diff --git a/R/options.R b/R/options.R
new file mode 100644
index 00000000..4a658e10
--- /dev/null
+++ b/R/options.R
@@ -0,0 +1,28 @@
+#' @export
+set_plot_options <- function(...) {
+ .Deprecated('options', msg = 'use the `repr.plot.*` options from the repr package instead')
+ opts <- list(...)
+ names(opts) <- paste0('repr.plot.', names(opts))
+ do.call(options, opts)
+}
+
+#' @export
+get_plot_options <- function() {
+ .Deprecated('getOption', msg = 'use the `repr.plot.*` options from the repr package instead')
+ all.opts <- options()
+ plot.opt.idx <- grep('^repr.plot', names(all.opts))
+ plot.opts <- all.opts[plot.opt.idx]
+ names(plot.opts) <- gsub('^repr\\.plot\\.', '', names(plot.opts))
+ return(as.list(plot.opts))
+}
+
+# all plot mime types. default value for the jupyter.plot_mimetypes option
+plot_mimetypes <- c(
+ 'image/png',
+ 'application/pdf',
+ 'image/svg+xml')
+
+.onLoad = function(libname = NULL, pkgname = NULL) {
+ if (is.null(getOption('jupyter.plot_mimetypes')))
+ options(jupyter.plot_mimetypes = plot_mimetypes)
+}
\ No newline at end of file
diff --git a/README.md b/README.md
index 10a8a797..9c318a7e 100644
--- a/README.md
+++ b/README.md
@@ -55,8 +55,9 @@ you'll lose all your variables if it crashes.
install.packages('RCurl')
library(devtools)
install_github('armstrtw/rzmq')
- install_github("IRkernel/IRdisplay")
- install_github("IRkernel/IRkernel")
+ install_github('IRkernel/repr')
+ install_github('IRkernel/IRdisplay')
+ install_github('IRkernel/IRkernel')
# Only if you have IPython 3 or above installed:
IRkernel::installspec()
diff --git a/man/IRkernel.Rd b/man/IRkernel.Rd
index c9e60526..58939d62 100644
--- a/man/IRkernel.Rd
+++ b/man/IRkernel.Rd
@@ -11,4 +11,16 @@ protocol to a 'kernel' which is responsible for executing code. This protocol
is language agnostic, so other languages can take advantage of IPython's rich
UI by implementing a kernel. This package is a kernel for the R language.
}
+\section{Options}{
+
+
+The following can be set/read via \code{options(opt.name = ...)} / \code{getOption('opt.name')}
+
+\describe{
+ \item{\code{jupyter.plot_mimetypes}}{
+ The plot formats emitted to the frontend when a plot is displayed.
+ (default: image/png, application/pdf, and image/svg+xml)
+ }
+}
+}
diff --git a/man/get_plot_options.Rd b/man/get_plot_options.Rd
deleted file mode 100644
index a4203780..00000000
--- a/man/get_plot_options.Rd
+++ /dev/null
@@ -1,12 +0,0 @@
-% Generated by roxygen2 (4.1.0): do not edit by hand
-% Please edit documentation in R/execution.r
-\name{get_plot_options}
-\alias{get_plot_options}
-\title{Get options for plotting}
-\usage{
-get_plot_options()
-}
-\description{
-Use set_plot_options() for modifying.
-}
-
diff --git a/man/installspec.Rd b/man/installspec.Rd
index 5265d88b..57d061d4 100644
--- a/man/installspec.Rd
+++ b/man/installspec.Rd
@@ -4,7 +4,7 @@
\alias{installspec}
\title{Install the kernelspec to tell IPython (>= 3) about IRkernel}
\usage{
-installspec(user = F)
+installspec(user = T)
}
\arguments{
\item{user}{Install into user directory ~/.ipython or globally?}
diff --git a/man/set_plot_options.Rd b/man/set_plot_options.Rd
deleted file mode 100644
index 86ce08a0..00000000
--- a/man/set_plot_options.Rd
+++ /dev/null
@@ -1,17 +0,0 @@
-% Generated by roxygen2 (4.1.0): do not edit by hand
-% Please edit documentation in R/execution.r
-\name{set_plot_options}
-\alias{set_plot_options}
-\title{Set options for plotting}
-\usage{
-set_plot_options(...)
-}
-\arguments{
-\item{...}{options that will be passed to png()}
-}
-\description{
-IRkernel displays plots in the notebook with calls to png().
-This function allows to set the variables that will be passed on to
-png(), for example width or height, see help(png).
-}
-