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Accessing the Common Language Runtime (.NET or Mono) from the R statistical software, in-process.
Keywords: interfacing R and .NET; R and Mono; R to .NET; CLR hosting; embedding Mono
- R 3.0 or above. May work with earlier version
- .NET 4.0 or above
- MS Visual C++ 2012 runtime
- RTools (if Windows)
- R 3.0.x
- Building with the Microsoft toolchain: MS .NET SDK, 4.0 or above, with C++ and C# compilers, msbuild. Visual Studio 2012 (Desktop Express Edition or developer and above) provides the toolchain.
- Building with the Mono toolchain: Mono 3.0.6 to 3.12.1
Please follow the Installing R packages in the Documentation. A Quick start page documents the first steps to get the library loaded in R.
…is available from https://rclr.codeplex.com.
- Fixed memory leaks when passing R vectors to .NET
- Major improvement to the handling and reporting of CLR exceptions on MS.NET
- The download page also has a tarball of the sources
- Support for Mono included in the windows binaries. Date-time handling is the main lagging feature.
The R Project for Statistical Computing has seen an outstanding adoption in many scientific fields and is a tool of choice for many. Some things are still better done in other languages (C, Fortran, Java, .NET, etc.). There are ways to link R in-process with most languages, however the interoperability with .NET is lagging. R.NET offers one way to access R from a Common Language Runtime implementation (CLR). The project rClr offers the access to a CLR from R in a manner natural to R users.
To give a feel for the capabilities, below is an extract from the tutorials. A hydrology model written in C# and its time series outputs are visualized in R.
rClr aims to be for .NET CLR implementations (.NET framework and Mono) what rJava is for Java.