function [simValuesSame, simValuesDiff] = ...
    example(featuresPred, featuresExp, nSame, nDiff, nData, alpha, beta, gamma)
% An example using the matlab functions I wrote.
% reads feature arrays from the data base and calculates similarity values
% using simple counting.
% Inputs:
% 1. feature arrays from predicted data
% 2. feature arrays from experiment data
% 3. number of arrays where predicted and experiment proteins are from the
%    same superfamily
% 4. number of arrays where predicted and experiment proteins are from 
%    different superfamilies

% Outputs:
% 1. array of similarity values for arrays from same super family
% 2. array of similarity values for arrays from different super families

% Usage
% ***Step1: Code to get data from the database***
%% desiredColumns = {'correct_superfamily', 'zscore', ...
%% 'experiment_sequence_length', 'prediction_sequence_length', ...
%% 'experiment_contact_order', 'prediction_contact_order', ...
%% 'experiment_percent_alpha', 'prediction_percent_alpha', ...
%% 'experiment_percent_beta', 'prediction_percent_beta'};
%% location = 'newer_csv_data';
%% dataMat = readSeparatedDataColumns(location, desiredColumns);
%% [sameSfPred, sameSfExp, diffSfPred, diffSfExp, featNames] = ...
%%     predExpFeatureMatrices(dataMat, desiredColumns);
%% clear dataMat;

% Remove duplicates
%% sameSf = [sameSfExp sameSfPred];
%% sameSf = unique(sameSf, 'rows');
%% sameSfExp = sameSf(:, 1:5);
%% sameSfPred = sameSf(:, 6:10);
%% diffSf = [diffSfExp diffSfPred];
%% diffSf = unique(diffSf, 'rows');
%% diffSfExp = diffSf(:, 1:5);
%% diffSfPred = diffSf(:, 6:10);
%% predFeatMat = [sameSfPred; diffSfPred];
%% nSame = size(sameSfPred, 1);
%% nDiff = size(diffSfPred, 1);
%% nData = size(predFeatMat, 1);
%% expFeatMat = [sameSfExp; diffSfExp];

% ***Step2: Call example 
%% [simValuesSame, simValuesDiff] = example(predFeatMat, expFeatMat,
%% nSame, nDiff, nData, alpha, beta, gamma);

for i= 1:nSame
    [AintersectB, AnotB, BnotA] = featurescomp(featuresPred(i),...
        featuresExp(i));
    simValuesSame(i) = simCounting(AintersectB, AnotB, BnotA, alpha, beta, gamma);
    j= nSame+i;
    if(j<=nData)
        [AintersectB, AnotB, BnotA] = featurescomp(featuresPred(j),...
            featuresExp(j));
        simValuesDiff(i) = simCounting(AintersectB, AnotB, BnotA, alpha, beta, gamma);
    end
end
j
%for k= j:nData
%       [AintersectB, AnotB, BnotA] = featurescomp(featuresPred(k),...
%            featuresExp(k));
%       simValuesDiff(i) = simCounting(AintersectB, AnotB, BnotA, alpha, beta, gamma);
%      i=i+1;
%end
%i
%nData