You are an expert in writing code in many different languages. Your goal is to perform code completion for the following code, keeping in mind the rest of the code and the file meta data.
    Metadata details:
    filename: feComputeEvidence.m
    path of file: ./repos/encode/life/compute
    
    the code of the file until where you have to start completion: function se = feComputeEvidence(rmse1,rmse2)
% Computes a series of distance metrics between two RMSE distribtions.
%
% Compute summary statistics on to characterize the lesion,:
% We compute:
% - The strength of evidence, namely the effect size of the lesion
% - The Kullback-Leibler Divergence
% - Jeffrey's Divergence
% - The Earth Mover's distance
%
% Copyright (2016), Franco Pestilli, Indiana University, frakkopesto@gmail.com.

% Prepare the distribution of errors and the histograms describing the
% erros.
se.nolesion.rmse.all  = rmse1;
se.lesion.rmse.all    = rmse2;
se.nolesion.rmse.mean = mean(se.nolesion.rmse.all);
se.lesion.rmse.mean   = mean(se.lesion.rmse.all);

% Histograms
se.xrange(1) = min([se.lesion.rmse.all se.nolesion.rmse.all]);
se.xrange(2) = max([se.lesion.rmse.all se.nolesion.rmse.all]);
se.nbins     = 60;
se.bins      = linspace(se.xrange(1),se.xrange(2),se.nbins);
[se.lesion.hist,   se.lesion.xhist]   = hist(se.lesion.rmse.all,  se.bins);
[se.nolesion.hist, se.nolesion.xhist] = hist(se.nolesion.rmse.all,se.bins);
se.lesion.hist     = se.lesion.hist ./   sum(se.lesion.hist);
se.nolesion.hist   = se.nolesion.hist ./ sum(se.nolesion.hist);

% Kullback-Leibler Divergence
se.kl.name = sprintf('Kullbackâ€“Leibler divergence: http://en.wikipedia.org/wiki/Kullback-Leibler_divergence');
tmp = se.nolesion.hist .* log2( (se.nolesion.hist) ./ (se.lesion.hist + eps) );
se.kl.mean = nansum(tmp);clear tmp
se.kl.std  = nan;

% Jeffrey's divergence
se.j.name = sprintf('Jeffrey''s divergence: http://en.wikipedia.org/wiki/Divergence_(statistics)');
tmp = se.nolesion.hist .* log2( (se.nolesion.hist) ./ ((se.lesion.hist + se.lesion.hist + eps)./2)  ) + ...
      se.lesion.hist .* log2( (se.lesion.hist) ./ ((se.lesion.hist + se.lesion.hist + eps)./2) );
se.j.mean = nansum(tmp); clear tmp

    
function se = feComputeEvidence(rmse1,rmse2)
% Computes a series of distance metrics between two RMSE distribtions.
%
% Compute summary statistics on to characterize the lesion,:
% We compute:
% - The strength of evidence, namely the effect size of the lesion
% - The Kullback-Leibler Divergence
% - Jeffrey's Divergence
% - The Earth Mover's distance
%
% Copyright (2016), Franco Pestilli, Indiana University, frakkopesto@gmail.com.

% Prepare the distribution of errors and the histograms describing the
% erros.
se.nolesion.rmse.all  = rmse1;
se.lesion.rmse.all    = rmse2;
se.nolesion.rmse.mean = mean(se.nolesion.rmse.all);
se.lesion.rmse.mean   = mean(se.lesion.rmse.all);

% Histograms
se.xrange(1) = min([se.lesion.rmse.all se.nolesion.rmse.all]);
se.xrange(2) = max([se.lesion.rmse.all se.nolesion.rmse.all]);
se.nbins     = 60;
se.bins      = linspace(se.xrange(1),se.xrange(2),se.nbins);
[se.lesion.hist,   se.lesion.xhist]   = hist(se.lesion.rmse.all,  se.bins);
[se.nolesion.hist, se.nolesion.xhist] = hist(se.nolesion.rmse.all,se.bins);
se.lesion.hist     = se.lesion.hist ./   sum(se.lesion.hist);
se.nolesion.hist   = se.nolesion.hist ./ sum(se.nolesion.hist);

% Kullback-Leibler Divergence
se.kl.name = sprintf('Kullbackâ€“Leibler divergence: http://en.wikipedia.org/wiki/Kullback-Leibler_divergence');
tmp = se.nolesion.hist .* log2( (se.nolesion.hist) ./ (se.lesion.hist + eps) );
se.kl.mean = nansum(tmp);clear tmp
se.kl.std  = nan;

% Jeffrey's divergence
se.j.name = sprintf('Jeffrey''s divergence: http://en.wikipedia.org/wiki/Divergence_(statistics)');
tmp = se.nolesion.hist .* log2( (se.nolesion.hist) ./ ((se.lesion.hist + se.lesion.hist + eps)./2)  ) + ...
      se.lesion.hist .* log2( (se.lesion.hist) ./ ((se.lesion.hist + se.lesion.hist + eps)./2) );
se.j.mean = nansum(tmp); clear tmp
se.j.std   = nan;

% Earth Mover's Distance:
% Note: This can be very slow and my require large amounts of memory for more than 1000 voxels
% fprintf('[%s] Computing the Earth Mover''s distance... \n',mfilename)
se.em.name = sprintf('Earth Mover''s distance: http://en.wikipedia.org/wiki/Earth_mover''s_distance');

try % Using Rubinov c-code fastest
    pairwiseDist = zeros(size(se.lesion.xhist,2));
    for i=1:size(se.nolesion.xhist,2)
        for j=1:size(se.lesion.xhist,2)
            pairwiseDist(i,j) = abs(se.lesion.xhist(i)-se.nolesion.xhist(j));
        end