function [simDsf, simSsf, features1 features2] = example2(numFeaturePairs, typeDistribution, inputsDistrib, typeSim, simInputs)
% Create feature arrays from 2 different classes, and calculate pairwise
% similarities.
% Inputs:
% 1. numFeaturePairs: number of feature arrays from each class
% 2. typeDistribution: the distribution used to generate the feature
%   matrices ("mean", "mutEx", "exp", "zipf")
% 3. inputsDistrib: array of inputs to the distribution
% 4. typeSim: type of similarity metric ("lin", "counting", "re")
% 5. simInputs: inputs needed by the similarity metric

switch(typeDistribution)
    case 'mean'
        mean1 = inputsDistrib(1);
        mean2 = inputsDistrib(2);
        p1 = inputsDistrib(3);
        p2 = inputsDistrib(4);
        for i=1:numFeaturePairs
            [features1(i,:) features2(i,:)] = simMean(mean1, mean2, p1, p2);
        end
    case 'mutEx'
        dim = inputsDistrib(1);
        p = inputsDistrib(2);
        for i=1:numFeaturePairs
            [features1(i,:) features2(i,:) classOne classTwo] = simMutuallyExclusive(dim, p);
        end
    case 'exp'
        dim = inputsDistrib(1);
        gamma = inputsDistrib(2);
        lambda = inputsDistrib(3);       
        for i=1:numFeaturePairs
            [features1(i,:),features2(i,:)] = simExp(dim, gamma, lambda);
        end
    case 'zipf'
        dim = inputsDistrib(1);
        s = inputsDistrib(2);
        for i=1:numFeaturePairs
            [f1 f2] = simZipf(dim, s);
            features1(i,:) = f1;
            features2(i,:) = f2;
        end
    otherwise
        disp('Invalid distribution')
        return
end

switch(typeSim)
    case 'lin'
        for i=1:numFeaturePairs
            [AintersectB AnotB BnotA] = featurescomp(features1(i,:), features2(i,:));
            probAintersectB = calcTrueProbIntersect(AintersectB, typeDistribution, 0, ...
                inputsDistrib);
            [probAnotB] = calcTrueProbExclusive('A', AnotB, typeDistribution, 0, inputsDistrib);
            [probBnotA] = calcTrueProbExclusive('B', BnotA, typeDistribution, 0, inputsDistrib);            
            disp('probAintersectB');
            disp(probAintersectB);
            disp('probAnotB');
            disp(probAnotB);
            disp('probBnotA');
            disp(probBnotA);
            [simDsf(i)] = simLin(probAintersectB, probAnotB, probBnotA);
            simSsf(i)=0;
        end
    case 'counting'
        for i=1:numFeaturePairs
            [AintersectB AnotB BnotA] = featurescomp(features1(i,:), features2(i,:));
            disp('AintersectB');
            disp(AintersectB);
            disp('AnotB');
            disp(AnotB);
            disp('BnotA');
            disp(BnotA);
            alpha = simInputs(1);
            beta = simInputs(2);
            gamma = simInputs(3);            
            [simDsf(i)] = simCounting(AintersectB, AnotB, BnotA, alpha, beta, gamma);     
            disp('sim');
            disp(simDsf(i));
        end
        if(numFeaturePairs >=2)
            for i=1:numFeaturePairs-1
                [AintersectB AnotB BnotA] = featurescomp(features1(i,:), features1(i+1,:));
                alpha = simInputs(1);
                beta = simInputs(2);
                gamma = simInputs(3);            
                [simSsf(i)] = simCounting(AintersectB, AnotB, BnotA, alpha, beta, gamma);     
            end
        else
            simSsf = -1;
        end           
    case 're'
        probMatrix = calcReProbs(features1, features2);        
        for i=1:numFeatures
            [AintersectB AnotB BnotA] = featurescomp(features1(i,:), features2(i,:));            
            [sim(i)] = simRe(probMatrix, AintersectB, AnotB, BnotA)
        end
    otherwise
        disp('Invalid similarity metric');
end