column vector with row means -- with std::accumulate?
accumulate, c++, mean, stl, vector
Solution
std::transform(data.begin(), data.end(), rowmeans.begin(),
[](std::vector<double> const& d) {
return std::accumulate(d.begin(), d.end(), 0.0) / d.size();
});
Although, my personal style would involve a named lambda or function, because I would find that more self-documenting:
auto Mean = [](std::vector<double> const& d) { return std::accumulate(d.begin(), d.end(), 0.0) / d.size(); };
std::transform(data.begin(), data.end(), rowmeans.begin(), Mean);
Problem
In an effort to be as lazy as possible I read in a matrix as ``` vector< vector<double> > data ( rows, vector<double> ( columns ) ); ``` and try to use as many STL goodies as I can. One thing I need to do next is to compute the row means. In C-style programming that would be ``` vector<double> rowmeans( data.size() ); for ( int i=0; i<data.size(); i++ ) for ( int j=0; j<data[i].size(); j++ ) rowmeans[i] += data[i][j]/data[i].size(); ``` In In C++, how to compute the mean of a vector of integers using a vector view and gsl_stats_mean? it is explained that for a vector of numbers you can compute a vector mean in one line without calling the size() operator at every step: ``` double mean = std::accumulate(stl_v.begin(), stl_v.end(), 0.0) / stl_v.size(); ``` Is it possible to use these iterators over a vector of vectors? An intermediate form is ``` vector<double> rowmeans( rows ); for ( int i=0; i<data.size(); i++ ) rowmeans[i] = std::accumulate(data[i].begin(), data[i].end(), 0.0) / data[i].size(); ``` already 1 line gone! but using STL functions is it possible to get rid of the [i] index as well? (on the top level it's just a matter of collecting the row means).