Assessing C Code in R

Introduction

R is a popular programming language and environment for statistical computing, data visualization, and data analysis. While R has its own strengths, it often relies on external libraries and packages to perform complex tasks. One such scenario arises when we want to access the underlying C code that drives an R function.

In this article, we will explore how to assess C code in R, including identifying C entry points, extracting function sources, and understanding the intricacies of the R programming language.

C Entry Points in R Functions

When you call an R function, it may involve external libraries or packages that provide additional functionality. These libraries often contain C code that is compiled into shared objects, which can be loaded into R at runtime. When an R function calls another function using .Call`, it’s essentially calling a specific entry point in the compiled C code.

For instance, consider the following example:

## Create two links for logit and identity functions

make.link("logit")
make.link("identity")

In this case, we see that the logit function is called using .Call(C_logit_link, mu), which suggests that there’s a C entry point named C_logit_link. To understand what this C entry point does, we’ll delve into extracting the source code of this compiled library.

Extracting C Code from Compiled Libraries

The R programming language provides several ways to access and extract C code from compiled libraries. One approach is to use the Rcmd system, which allows you to compile a package with the -f option, creating an executable file that can be run using R CMD SHLIB.

Here’s an example of how to do this:

## Compile and run a package

# Create a new directory for our project
mkdir my_package

# Navigate into the directory
cd my_package

# Create a source file for our function (logit_link.c)
echo "int logit_link(SEXP mu) {
    int i, n = LENGTH(mu);
    SEXP ans = PROTECT(duplicate(mu));
    double *rans = REAL(ans), *rmu=REAL(mu);

    if (!n || !isReal(mu))
        error(_("Argument %s must be a nonempty numeric vector"), "mu");
    for (i = 0; i < n; i++)
        rans[i] = log(x_d_omx(rmu[i]));
    UNPROTECT(1);
    return ans;
}" > logit_link.c

# Compile the library
R CMD SHLIB logit_link.c

# Create a package using the -f option
R CMD INSTALL --build my_package --configure option R CMD config --cflags -I /usr/lib/rveg --ldflags -L /usr/lib/rveg -lc R

# Load the package and run the function
my_package$load()
logit_link(mu = 1.5)

In this example, we create a new directory for our project (my_package), compile the logit_link.c file using R CMD SHLIB, and then load the resulting library into R.

Understanding C Entry Points

Now that we’ve extracted the source code of a compiled library, let’s take a closer look at what this C entry point does. In our example:

## The C entry point

SEXP logit_link(SEXP mu)
{
    int i, n = LENGTH(mu);
    SEXP ans = PROTECT(duplicate(mu));
    double *rans = REAL(ans), *rmu=REAL(mu);

    if (!n || !isReal(mu))
        error(_("Argument %s must be a nonempty numeric vector"), "mu");
    for (i = 0; i < n; i++)
        rans[i] = log(x_d_omx(rmu[i]));
    UNPROTECT(1);
    return ans;
}

This C function takes a single argument mu of type SEXP, which represents an R object. The function first checks if the length of mu is non-zero and if it’s a numeric vector. If not, it throws an error.

The function then duplicates the input vector mu using PROTECT(duplicate(mu)). It extracts the double values from this duplicated vector (REAL(ans)), calculates the log of each value using log(x_d_omx(rmu[i])), and stores these results in a new numeric vector rans.

Finally, the function returns the resulting vector rans by calling UNPROTECT(1).

Conclusion

Assessing C code in R requires understanding how R functions interact with external libraries and packages. By using tools like R CMD SHLIB, we can extract the source code of compiled libraries and gain insights into the underlying C entry points that drive R functionality.

In this article, we explored how to access C code from compiled libraries, including identifying C entry points, extracting function sources, and understanding the intricacies of the R programming language. We also walked through a step-by-step example of compiling a package with R CMD SHLIB, creating an executable file, and running it using R CMD.

By following these steps and techniques, you can gain a deeper appreciation for the complexities of C code in R and develop your skills as a data analyst or statistician.

Last modified on 2024-05-09