How to link R and Julia code
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Julia is a powerful, high-level, dynamic programming language. It is also a general-purpose language used to write applications. It has many features like being open-source, simple, efficient, and fast. But one feature that makes it stand out is interoperability.
What is interoperability?
Interoperability can be described as the capacity of two or more languages to interact with each other for effective data transmission in any system. One of Julia’s features is its ability to communicate and call language into itself while writing the Julia syntax.
How can we link R and Julia code?
To inter-operate with the R language, the RCall package is used. This package is built by RCall package, we can harness the strengths of both languages, enhancing the flexibility and capabilities of the data analysis or scientific computing workflows.
Code example
Let's look at the following example:
using RCall
@rlibrary stats
N = 10
x = 1:10
mean = 10
sd = 5
a = R"rnorm($N, mean=$mean, sd=$sd)"
y = dlnorm(x, meanlog=mean, sdlog=sd)
println("List of random numbers")
for i = 1:length(a)
println("$i \t $(a[i])")
end
println("\nLog normal probability density function")
println(y)Explanation
Line 1: The
RCalllibrary is imported in the Julia file.Line 2: The
Rlibrarystatsis imported in Julia using the@rlibrarymacro.Lines 4–7: Different variables are defined in Julia which will be used for random number generation and a log-normal probability density function.
Line 9: An
Rscript is used to generate random numbers withNvalues, a mean ofmean, and a standard distribution ofsd.Line 10: The R function
stats.dlnorm()is used to generate a log-normal probability density function with the independent variable arrayx, a log mean ofmean, and a log standard distribution ofsd.Lines 12–18: The resulting arrays are printed.
Note: If you want to learn about how to link Julia code in R using
XRJuliapackage, visit this Educative Answer.
