How to avoid a loop to calculate competition index

Question

I\'ve to calculate so called competition index for a couple of the experiments. I have known position of the object and its size. I\'d like to calculate the sum of the sizes

Answer 1

Loops like this are a perfect candidate for speeding up with Rcpp. The logic translates across unchanged:

library(Rcpp)

cppFunction('
List
computeIndex(const NumericVector x,
             const NumericVector y, 
             const NumericVector di,
             const CharacterVector ex)
{
    int n = x.size();
    NumericVector comp1(n), dist(n);

    for(int i = 0; i < n; ++i)
    {
        for(int j = 0; j < n; ++j)
        {
            double dx = x[j] - x[i], dy = y[j] - y[i];
            double d = std::sqrt(dx*dx + dy*dy);

            if((d < 2) && (ex[i] == ex[j]))
            {
                comp1[i] += di[j];
                dist[i] +=  d;
            }
        }
    }

    return List::create(Named("comp1") = comp1,
                        Named("dist") = dist);
}
')

res <- data.frame(computeIndex(df$x, df$y, df$di, df$exp))

Not only is this faster than the equivalent R-only code, but it avoids having to allocate any O(N^2) objects. You can also combine this with dplyr to avoid needless comparisons between rows with different exp values:

df %>%
    group_by(exp) %>%
    do({
        res <- computeIndex(.$x, .$y, .$di, .$exp)
        data.frame(., res)
    })