| Title: | Seamless Integration Between R and 'Julia' |
|---|---|
| Description: | Provides an R interface to 'Julia', which is a high-level, high-performance dynamic programming language for numerical computing, see <https://julialang.org/> for more information. It provides a high-level interface as well as a low-level interface. Using the high level interface, you could call any 'Julia' function just like any R function with automatic type conversion. Using the low level interface, you could deal with C-level SEXP directly while enjoying the convenience of using a high-level programming language like 'Julia'. |
| Authors: | Changcheng Li [aut, cre], Randy Lai [ctb], Dmitri Grominski [ctb], Nagi Teramo [ctb] |
| Maintainer: | Changcheng Li <[email protected]> |
| License: | MIT + file LICENSE |
| Version: | 0.17.5 |
| Built: | 2024-11-26 06:27:13 UTC |
| Source: | CRAN |
The experimental language piper for julia language.
obj %>J% func_callobj %>J% func_call
obj |
the object to pass to the piper. |
func_call |
the impartial julia function call. |
if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) 2 %>J% sqrt 3 %>J% log(2) }if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) 2 %>J% sqrt 3 %>J% log(2) }
autowrap tells 'JuliaCall' to use automatic wrapper for julia type.
autowrap(type, fields = NULL, methods = c())autowrap(type, fields = NULL, methods = c())
type |
the julia type to wrap. |
fields |
names of fields to be included in the wrapper. If the value is NULL, then every julia fields will be included in the wrapper. |
methods |
names of methods to be overloaded for the wrapper. |
julia_do.call is the do.call for julia.
And julia_call calls julia functions.
For usage of these functions, see documentation of arguments and examples.
julia_do.call( func_name, arg_list, need_return = c("R", "Julia", "None"), show_value = FALSE ) julia_call( func_name, ..., need_return = c("R", "Julia", "None"), show_value = FALSE )julia_do.call( func_name, arg_list, need_return = c("R", "Julia", "None"), show_value = FALSE ) julia_call( func_name, ..., need_return = c("R", "Julia", "None"), show_value = FALSE )
func_name |
the name of julia function you want to call. If you add "." after 'func_name', the julia function call will be broadcasted. |
arg_list |
the list of the arguments you want to pass to the julia function. |
need_return |
whether you want julia to return value as an R object, a wrapper for julia object or no return. The value of need_return could be TRUE (equal to option "R") or FALSE (equal to option "None"), or one of the options "R", "Julia" and "None". |
show_value |
whether to invoke the julia display system or not. |
... |
the arguments you want to pass to the julia function. |
Note that named arguments will be discarded if the call uses dot notation, for example, "sqrt.".
if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) julia_do.call("sqrt", list(2)) julia_call("sqrt", 2) julia_call("sqrt.", 1:10) }if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) julia_do.call("sqrt", list(2)) julia_call("sqrt", 2) julia_call("sqrt.", 1:10) }
Julia language engine in R Markdown
eng_juliacall(options)eng_juliacall(options)
options |
a list of chunk options |
knitr::knit_engines$set(julia = JuliaCall::eng_juliacall)knitr::knit_engines$set(julia = JuliaCall::eng_juliacall)
Install Julia.
install_julia(version = "latest", prefix = julia_default_install_dir())install_julia(version = "latest", prefix = julia_default_install_dir())
version |
The version of Julia to install (e.g. |
prefix |
the directory where Julia will be installed.
If not set, a default location will be determined by |
julia_assign assigns a value to a name in julia with automatic type conversion.
julia_assign(x, value)julia_assign(x, value)
x |
a variable name, given as a character string. |
value |
a value to be assigned to x, note that R value will be converted to corresponding julia value automatically. |
if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) julia_assign("x", 2) julia_assign("rsqrt", sqrt) }if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) julia_assign("x", 2) julia_assign("rsqrt", sqrt) }
julia_command evaluates string commands in julia
without returning the result back to R.
However, it may evoke julia display system,
see the documentation of the argument 'show_value' for more details.
If you need to get the evaluation result in R, you can use
julia_eval.
julia_command(cmd, show_value = !endsWith(trimws(cmd, "right"), ";"))julia_command(cmd, show_value = !endsWith(trimws(cmd, "right"), ";"))
cmd |
the command string you want to evaluate in julia. |
show_value |
whether to display julia returning value or not, the default value is 'FALSE' if the 'cmd' ends with semicolon and 'TRUE' otherwise. |
if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) julia_command("a = sqrt(2);") }if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) julia_command("a = sqrt(2);") }
Open julia console.
julia_console()julia_console()
if (identical(interactive(), TRUE)) { ## julia_setup is quite time consuming julia_console() }if (identical(interactive(), TRUE)) { ## julia_setup is quite time consuming julia_console() }
julia_eval evaluates string commands in julia and
returns the result to R.
The returning julia object will be automatically converted
to an R object or a JuliaObject wrapper,
see the documentation of the argument 'need_return' for more details.
'julia_eval' will not invoke julia display system.
If you don't need the returning result in R or
you want to invoke the julia display system, you can
use julia_command.
julia_eval(cmd, need_return = c("R", "Julia"))julia_eval(cmd, need_return = c("R", "Julia"))
cmd |
the command string you want to evaluate in julia. |
need_return |
whether you want julia to return value as an R object or a wrapper for julia object. |
the R object automatically converted from julia object.
if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) julia_eval("sqrt(2)") }if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) julia_eval("sqrt(2)") }
julia_exists returns whether a julia object with the given name exists or not.
julia_exists(name)julia_exists(name)
name |
the name of julia object you want to check. |
if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) julia_exists("sqrt") }if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) julia_exists("sqrt") }
julia_help outputs the documentation of a julia function.
julia_help(fname)julia_help(fname)
fname |
the name of julia function you want to get help with. |
if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) julia_help("sqrt") }if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) julia_help("sqrt") }
julia_markdown_setup does the initial setup for JuliaCall in RMarkdown document and RStudio notebooks.
The function should be invoked automatically most of the case.
It can also be called explicitly in RMarkdown documents or notebooks.
julia_markdown_setup(..., notebook = TRUE)julia_markdown_setup(..., notebook = TRUE)
... |
The same arguments accepted by 'julia_setup'. |
notebook |
whether it is in RStudio notebook environment or not. |
julia_notebook_setup is deprecated,
use julia_markdown_setup(notebook=TRUE) instead.
julia_notebook_setup(...)julia_notebook_setup(...)
... |
The same arguments accepted by 'julia_setup'. |
Using julia packages.
julia_install_package(pkg_name_or_url) julia_installed_package(pkg_name) julia_install_package_if_needed(pkg_name) julia_update_package(...) julia_library(pkg_name)julia_install_package(pkg_name_or_url) julia_installed_package(pkg_name) julia_install_package_if_needed(pkg_name) julia_update_package(...) julia_library(pkg_name)
pkg_name_or_url |
the julia package name or url. |
pkg_name |
the julia package name. |
... |
you can provide none or one or multiple julia package names here. |
julia_installed_package will return the version number of the julia package, "nothing" if the package is not installed.
if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) julia_install_package("DataFrames") julia_installed_package("DataFrames") julia_install_package_if_needed("DataFrames") julia_update_package("DataFrames") julia_library("DataFrames") }if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) julia_install_package("DataFrames") julia_installed_package("DataFrames") julia_install_package_if_needed("DataFrames") julia_update_package("DataFrames") julia_library("DataFrames") }
Wrap julia functions and packages the easy way.
julia_function(func_name, pkg_name = "Main", env = new.env(emptyenv())) julia_pkg_import(pkg_name, func_list, env = new.env(parent = emptyenv())) julia_pkg_hook(env, hook)julia_function(func_name, pkg_name = "Main", env = new.env(emptyenv())) julia_pkg_import(pkg_name, func_list, env = new.env(parent = emptyenv())) julia_pkg_hook(env, hook)
func_name |
the julia function name to be wrapped. |
pkg_name |
the julia package name to be wrapped. |
env |
the environment where the functions and packages are wrapped. |
func_list |
the list of julia function names to be wrapped. |
hook |
the function to be executed before the execution of wrapped functions. |
if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## do initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) julia_install_package_if_needed("Optim") opt <- julia_pkg_import("Optim", func_list = c("optimize", "BFGS")) rosenbrock <- function(x) (1.0 - x[1])^2 + 100.0 * (x[2] - x[1]^2)^2 result <- opt$optimize(rosenbrock, rep(0,2), opt$BFGS()) result }if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## do initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) julia_install_package_if_needed("Optim") opt <- julia_pkg_import("Optim", func_list = c("optimize", "BFGS")) rosenbrock <- function(x) (1.0 - x[1])^2 + 100.0 * (x[2] - x[1]^2)^2 result <- opt$optimize(rosenbrock, rep(0,2), opt$BFGS()) result }
julia_setup does the initial setup for the JuliaCall package.
It setups automatic type conversion, Julia display systems, etc,
and is necessary for every new R session to use the package.
If not carried out manually, it will be invoked automatically before other julia_xxx functions.
julia_setup( JULIA_HOME = NULL, verbose = TRUE, installJulia = FALSE, install = TRUE, force = FALSE, useRCall = TRUE, rebuild = FALSE, sysimage_path = NULL )julia_setup( JULIA_HOME = NULL, verbose = TRUE, installJulia = FALSE, install = TRUE, force = FALSE, useRCall = TRUE, rebuild = FALSE, sysimage_path = NULL )
JULIA_HOME |
the file folder which contains julia binary, if not set, JuliaCall will look at the global option JULIA_HOME, if the global option is not set, JuliaCall will then look at the environmental variable JULIA_HOME, if still not found, JuliaCall will try to use the julia in path. |
verbose |
whether to print out detailed information
about |
installJulia |
whether to install julia automatically when julia is not found, whose default value is FALSE. |
install |
whether to execute installation script for dependent julia packages, whose default value is TRUE; but can be set to FALSE to save startup time when no installation of dependent julia packages is needed. |
force |
whether to force julia_setup to execute again. |
useRCall |
whether or not you want to use RCall.jl in julia, which is an amazing package to access R in julia. |
rebuild |
whether to rebuild RCall.jl, whose default value is FALSE to save startup time. If a new version of R is used, then this parameter needs to be set to TRUE. |
sysimage_path |
path to the precompiled custom sys image. Path can be either an absolute path or relative to the current directory. |
The julia interface, which is an environment with the necessary methods like command, source and things like that to communicate with julia.
if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming julia <- julia_setup(installJulia = TRUE) }if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming julia <- julia_setup(installJulia = TRUE) }
julia_source sources a julia source file.
julia_source(file_name)julia_source(file_name)
file_name |
the name of julia source file. |
JuliaCall provides you with functions to call Julia functions and to use Julia packages as easy as possible.
if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## The examples are quite time consuming ## Do initiation for JuliaCall and automatic installation if necessary julia <- julia_setup(installJulia = TRUE) ## Different ways for calculating `sqrt(2)` # julia$command("a = sqrt(2)"); julia$eval("a") julia_command("a = sqrt(2)"); julia_eval("a") # julia$eval("sqrt(2)") julia_eval("sqrt(2)") # julia$call("sqrt", 2) julia_call("sqrt", 2) # julia$eval("sqrt")(2) julia_eval("sqrt")(2) ## You can use `julia_exists` as `exists` in R to test ## whether a function or name exists in Julia or not # julia$exists("sqrt") julia_exists("sqrt") ## You can use `julia$help` to get help for Julia functions # julia$help("sqrt") julia_help("sqrt") ## You can install and use Julia packages through JuliaCall # julia$install_package("Optim") julia_install_package("Optim") # julia$install_package_if_needed("Optim") julia_install_package_if_needed("Optim") # julia$installed_package("Optim") julia_installed_package("Optim") # julia$library("Optim") julia_library("Optim") }if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## The examples are quite time consuming ## Do initiation for JuliaCall and automatic installation if necessary julia <- julia_setup(installJulia = TRUE) ## Different ways for calculating `sqrt(2)` # julia$command("a = sqrt(2)"); julia$eval("a") julia_command("a = sqrt(2)"); julia_eval("a") # julia$eval("sqrt(2)") julia_eval("sqrt(2)") # julia$call("sqrt", 2) julia_call("sqrt", 2) # julia$eval("sqrt")(2) julia_eval("sqrt")(2) ## You can use `julia_exists` as `exists` in R to test ## whether a function or name exists in Julia or not # julia$exists("sqrt") julia_exists("sqrt") ## You can use `julia$help` to get help for Julia functions # julia$help("sqrt") julia_help("sqrt") ## You can install and use Julia packages through JuliaCall # julia$install_package("Optim") julia_install_package("Optim") # julia$install_package_if_needed("Optim") julia_install_package_if_needed("Optim") # julia$installed_package("Optim") julia_installed_package("Optim") # julia$library("Optim") julia_library("Optim") }
JuliaObject converts an R object to julia object
and returns a reference of the corresponding julia object.
JuliaObject(x)JuliaObject(x)
x |
the R object you want to convert to julia object. |
an environment of class JuliaObject, which contains an id corresponding to the actual julia object.
if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) a <- JuliaObject(1) }if (identical(Sys.getenv("AUTO_JULIA_INSTALL"), "true")) { ## julia_setup is quite time consuming ## doing initialization and automatic installation of Julia if necessary julia_setup(installJulia = TRUE) a <- JuliaObject(1) }
Get the field names, get or set certain fields of an JuliaObject.
fields(object) ## S3 method for class 'JuliaObject' fields(object) field(object, name) ## S3 method for class 'JuliaObject' field(object, name) field(object, name) <- value ## S3 replacement method for class 'JuliaObject' field(object, name) <- valuefields(object) ## S3 method for class 'JuliaObject' fields(object) field(object, name) ## S3 method for class 'JuliaObject' field(object, name) field(object, name) <- value ## S3 replacement method for class 'JuliaObject' field(object, name) <- value
object |
the JuliaObject. |
name |
a character string specifying the fields to be accessed or set. |
value |
the new value of the field of the JuliaObject. |
plotsViewer lets you view julia plots in R.
plotsViewer()plotsViewer()