# Intro

Have you ever wanted to see if you can write the part of the `table()` function’s frequency summation for one vector in C++?! Well, that’s exactly what I did by accident. As some of the best results come from pure accidents, I felt it only right to add a post describing how to obtain such a result.

# The Plan

First of all, we need to find the unique values for the vector of numbers. To do this, we opt to store the number being counted as a `key` within a `std::map` and increment the `value` each time we observe that number.

Next, we need to export the data from the `std::map` to a `std::vector<std::pair<double,int> >` so that we can sort by the number of occurrences.

With a sorted vector in hand by `std::pair<double,int>`, we need to then write a list structure to export into R. This is the case for because Rcpp does not support `std::set<T>`.

# The Implementation

``````#include <Rcpp.h>

// Save on the typing...
typedef std::pair<double, int>  ptype;

// A comparison function to rank values in descending order
bool compare_values(const ptype &p1, const ptype &p2)
{
return p1.second > p2.second;
}

// Get the top number of observations
// [[Rcpp::export]]
Rcpp::List table_cpp(const Rcpp::NumericVector & v, bool sort_data = false)
{

// Create a map
std::map<double, int> Elt;

Elt.clear();

// Fill the map with occurrences per number.
for (int i = 0; i != v.size(); ++i) {
Elt[ v[i] ] += 1;
}

// Get how many unique elements exist...
unsigned int n_obs = Elt.size();

// Switch map to a vector so that we can sort by value
std::vector< ptype > sorted_Elt(Elt.begin(), Elt.end());

if(sort_data){
// Perform the sort with a custom sort function.
std::sort(sorted_Elt.begin(), sorted_Elt.end(), compare_values);
}
// Else, return.

// Stop here if you do not need to import into R.
// Why? There is no ability to export a set w/ a pair into R. *cries*

// Recast for R using Rcpp::*Vectors to avoid another copy)
Rcpp::NumericVector result_keys(n_obs);
Rcpp::IntegerVector result_vals(n_obs);

unsigned int count = 0;

// Need to use iterators to access objects
for( std::vector< ptype >::iterator it = sorted_Elt.begin(); it != sorted_Elt.end(); ++it )
{
// Move them into split vectors
result_keys(count) = it->first;
result_vals(count) = it->second;

count++;
}

return Rcpp::List::create(Rcpp::Named("lengths") = result_vals,
Rcpp::Named("values") = result_keys);
}
``````

# Short Test

Let’s verify that it works by running over some data:

``````# Set seed for reproducibility
set.seed(223)
(a = sample(seq(0, 1, by = .2), 10, replace = T))
``````
``````##   0.0 0.0 0.2 1.0 0.4 1.0 0.8 0.6 0.2 0.2
``````

Generates:

``````      0.8 0.2 0.0 0.6 0.4 1.0 0.6 0.2 0.8 0.8
``````

And now we seek to obtain the occurrence information:

``````# Call our function
table_cpp(a)
``````
``````## \$lengths
##  2 3 1 1 1 2
##
## \$values
##  0.0 0.2 0.4 0.6 0.8 1.0
``````

Gives us:

``````\$lengths
 3 2 2 1 1 1

\$values
 0.8 0.2 0.6 0.0 0.4 1.0
``````

Let’s check by looking at `table()`’s output very quickly.

``````table(a)
0 0.2 0.4 0.6 0.8   1
1   2   1   2   3   1
``````

And now, we go to the winchester to grab a pint and wait for this to …