Optimizing Performance-Critical Operations in R with C++ and Rcpp

Here is a concise and readable explanation of the changes made:

R Code

The original R code has been replaced with a more efficient version using vectorized operations. The following lines have been changed:

stands[, baseD := max(D, na.rm = TRUE), by = "A"] 
[,
  D := baseD * 0.1234 ^ (B - 1)
][, baseD := NULL]

becomes

stands$baseD <- stands$D * (stands$B - 1) * 0.1234
stands$D <- stands$baseD
stands$baseD <- NA

Rcpp Code

The Rcpp code has been rewritten to use C++ for performance-critical operations. The following lines have been changed:

a[i] = (A[i]*123 + b[i-1]) * (1-lookup_a);
b2[i] = b[i] * 123;

becomes

double a[i] = (A[i]*123 + b[i-1]) * (1-lookup_a);
a[i] *= 0.1234;
b[i] = (B[i]*123 + b[i-1]) * (1-lookup_b);
b2[i] = b[i] * 123;

Loop Optimization

The loop has been optimized by using C++’s for loop and array indexing, which is faster than R’s for loop. The following lines have been changed:

for (int i = 1; i < n; i++) {
    // ...
}

becomes

for (int i = 0; i < n-1; i++) {
    a[i] = (A[i]*123 + b[i]) * (1-lookup_a);
    a2[i] = a[i] * 123;
    b[i+1] = (B[i+1]*123 + b[i]) * (1-lookup_b);
}

Data Structures

The DataFrame data structure has been replaced with C++’s std::vector to improve performance. The following lines have been changed:

DataFrame out = DataFrame::create(
    _["A"] = A,
    _["B"] = B,
    _["C"] = C,
    _["D"] = D,
    _["E"] = E,
    _["a"] = a,
    _["a2"] = a2,
    _["b"] = b,
    _["b2"] = b2,
    _["c"] = c,
    _["c2"] = c,
    _["d"] = d,
    _["e"] = e
);

becomes

std::vector<double> a = std::vector<double>(A.size());
std::vector<double> b = std::vector<double>(B.size());
// ...
DataFrame out;
out.push_back({"A", A});
out.push_back({"B", B});
out.push_back({"C", C});
out.push_back({"D", D});
out.push_back({"E", E});
out.push_back({"a", a});
out.push_back({"a2", a2});
out.push_back({"b", b});
out.push_back({"b2", b2});
out.push_back({"c", c});
out.push_back({"c2", c});
out.push_back({"d", d});
out.push_back({"e", e});

Note that this is just one possible way to optimize the R code using C++ and Rcpp. The actual implementation may vary depending on the specific requirements of your project.

Last modified on 2025-05-01