Use a variable outside the function in matlab

Question

I've written the following function:

% This function plots the contours of likelihood values on the scatter plot of a 2 dimensional data.

    function [xgrid,ygrid,Z,xy_matrix] = biVariateContourPlotsGMMCopula(givenData,gmmObject,~,numMeshPoints,x_dim,y_dim)

%INPUT: givenData (MxN, M=number of points, N=Dimension)
%     : plo = binary variable (1 plot contour plot, 0 do not plot)
%OUTPUT: xgrid,ygrid,Z ( Z contains the likelihood values of the points defined by xgrid and ygrid)

%load general_info;

    d = 2;
    if nargin < 5
        x_dim = 1;
        y_dim = 2;
    end
    
    if x_dim == y_dim
        hist(givenData(:,x_dim),10);
        return;
    end
    
    numMeshPoints = min(numMeshPoints,256);
    
    givenData = givenData(:,[x_dim y_dim]);
    alpha = gmmObject.alpha;
    mu = gmmObject.mu(:,[x_dim y_dim]);
    sigma = gmmObject.sigma([x_dim y_dim],[x_dim y_dim],:) + 0.005*repmat(eye(d),[1 1 numel(alpha)]);

    gmmObject = gmdistribution(mu,sigma,alpha);

    bin_num = 256;
    for j = 1:2
       l_limit = min(gmmObject.mu(:,j))-3*(max(gmmObject.Sigma(j,j,:))^0.5);
       u_limit = max(gmmObject.mu(:,j))+3*(max(gmmObject.Sigma(j,j,:))^0.5);
       xmesh_inverse_space{j} = (l_limit:(u_limit-l_limit)/(bin_num-1):u_limit);
    end


%if isempty(xmesh)||isempty(pdensity)||isempty(cdensity)
% Following for loop does the non-parameteric estimation of marginal % densities if not provided
    
    for i = 1:d
        currentVar = givenData(:,i);
        [~,pdensity{i},xmesh{i}]=kde(currentVar,numMeshPoints);
        pdensity{i}(pdensity{i}<0) = 0;
        cdensity{i} = cumsum(pdensity{i});
        cdensity{i} = (cdensity{i}-min(cdensity{i}))/(max(cdensity{i})-min(cdensity{i})); % scaling the cdensity value to be between [0 1]
    end

    [xgrid,ygrid] = meshgrid(xmesh{1}(2:end-1),xmesh{2}(2:end-1));
    
    for k = 1:d
        marginalLogLikelihood_grid{k} = log(pdensity{k}(2:end-1)+eps);
        marginalCDFValues_grid{k} = cdensity{k}(2:end-1);
    end
    [marg1,marg2] = meshgrid(marginalLogLikelihood_grid{1},marginalLogLikelihood_grid{2});

    [xg,yg] = meshgrid(marginalCDFValues_grid{1},marginalCDFValues_grid{2});
    inputMatrix = [reshape(xg,numel(xg),1) reshape(yg,numel(yg),1)];
    clear xg yg;

    copulaLogLikelihoodVals = gmmCopulaPDF(inputMatrix,gmmObject,xmesh_inverse_space);
    Z = reshape(copulaLogLikelihoodVals,size(marg1,1),size(marg1,2));
    Z = Z+marg1+marg2;
    
    Z = exp(Z);

% Getting the likelihood value from the log-likelihood

    plot(givenData(:,1),givenData(:,2),'b.','MarkerSize',5);hold
    [~,h] = contour(xgrid,ygrid,Z,[4e-6,4e-6]);

% Extract the (x, y) coordinates of the contour and concatenate them along the first dimension

    xy_matrix = [];
    for i = 1:length(h)
        xy = get(h(i), 'XData');
        x = xy(1, :);
        y = xy(2, :);
        xy_matrix = [xy_matrix, [x; y]];
    end

% Print the concatenated matrix

    disp(xy_matrix);

%title_string = ['GMCM fit (Log-Likelihood = ',num2str(logLikelihoodVal), ')'];
%title(title_string,'FontSize',12,'FontWeight','demi');

    axis tight

however xy_matrix is not shown on the workspace. How do I return the variable xy_matrix so that I can use it in another function?

Function call is inside a for loop as in below:

for i = 1:d
    for j = 1:d
        subplot(d,d,count); count = count+1;    
        [xgrid,ygrid,Z,xy_matrix] = biVariateContourPlotsGMMCopula(power_curve_reference_build_T2,gmcObject_bestfit,0,256,i,j);        
    end
end

So, when I'm including xy_matrix as a params in the function call, it generates the following error:

Have I missed anything here?

Answer 1

When you're calling the function with i==j==1 as parameters x_dim and y_dim, the function ends in the following if:

if x_dim == y_dim
    hist(givenData(:,x_dim),10);
    return;
end

The return values aren't defined at that point. If you define them in the beginning of the function, you won't get the error message.

function [xgrid,ygrid,Z,xy_matrix] = biVariateContourPlotsGMMCopula(givenData,gmmObject,~,numMeshPoints,x_dim,y_dim)
%INPUT: givenData (MxN, M=number of points, N=Dimension)
%     : plo = binary variable (1 plot contour plot, 0 do not plot)
%OUTPUT: xgrid,ygrid,Z ( Z contains the likelihood values of the points defined by xgrid and ygrid)
%load general_info;
xgrid=0;
ygrid=0;
Z=0;
xy_matrix=0;

d = 2;
if nargin < 5
    x_dim = 1;
    y_dim = 2;
end

Below is a suggestion of some changes of your function call. The return values are saved in cells so that you don't overwrite them in the next iteration. The function is also not called when i==j==x_dim==y_dim.

xgrids={};
ygrids={};
Zs={};
xy_matrices={};
for i = 1:d
    for j = 1:d
        if i~=j 
            subplot(d,d,count); count = count+1;    
            [xgrids{i,j},ygrids{i,j},Zs{i,j},xy_matrices{i,j}] = biVariateContourPlotsGMMCopula(power_curve_reference_build_T2,gmcObject_bestfit,0,256,i,j);      
        end  
    end
end