Silhouette function gives me an error: element number 2 undefined in return list - function

Question

I am trying to check the performance of k-means with the silhouette function but I am getting an error.
I am calling the function like this [out1,out2] = silhouette(normalized, idx); or [out1,out2] = silhouette(normalized, idx, 'cosine');
The definition of the function is function [si, h] = silhouette(X, clust, metric)
I expect to take a number between -1,+1 but instead of that I am getting error: element number 2 undefined in return list.
My code for the silhouette function:
function [si, h] = silhouette(X, clust, metric)
% Nan Zhou
% Code Matlab 'silhouette' into Octave function
% Sichuan University, Macquarie University
% zhnanx#gmail.com
% input parameters
% X, n-by-p data matrix
% - Rows of X correspond to points, columns correspond to coordinates.
% clust, clusters defined for X; n-by-1 vector
% metric, e.g. Euclidean, sqEuclidean, cosine
% return values
% si, silhouettte values, n-by-1 vector
% h, figure handle, waiting to be solved in the future
% algorithm reference
% - Peter J. Rousseeuw (1987)
% - Silhouettes: a Graphical Aid to the Interpretation and Validation of Cluster Analysis
% - doi:10.1016/0377-0427(87)90125-7
% check size
if (size(X, 1) != size(clust, 1))
error("First dimension of X <%d> doesn't match that of clust <%d>",...
size(X, 1), size(clust, 1));
endif
% check metric
if (! exist('metric', 'var'))
metric = 'sqEuclidean';
endif
%%%% function set
function [dist] = EuclideanDist(x, y)
dist = sqrt((x - y) * (x - y)');
endfunction
function [dist] = sqEuclideanDist(x, y)
dist = (x - y) * (x - y)';
endfunction
function [dist] = cosineDist(x, y)
cosineValue = dot(x,y)/(norm(x,2)*norm(y,2));
dist = 1 - cosineValue;
endfunction
%%% end function set
% calculating
si = zeros(size(X, 1), 1);
%h
%calculate values of si one by one
for iii = 1:length(si)
%%% distance of iii to all others
iii2all = zeros(size(X, 1), 1);
for jjj = 1:size(X, 1)
switch (metric)
case 'Euclidean'
iii2all(jjj) = EuclideanDist(X(iii, :), X(jjj, :));
case 'sqEuclidean'
iii2all(jjj) = sqEuclideanDist(X(iii, :), X(jjj, :));
case 'cosine'
iii2all(jjj) = cosineDist(X(iii, :), X(jjj, :));
otherwise
error('Invalid metric.');
endswitch
endfor
%%% end distance to all
%%% allocate values to clusters
clusterIDs = unique(clust); % eg [1; 2; 3; 4]
groupedValues = {};
for jjj = 1:length(clusterIDs)
groupedValues{clusterIDs(jjj)} = [iii2all(clust == clusterIDs(jjj))];
endfor
%%% end allocation
%%% calculate a(i)
% dist of object iii to all other objects in the same cluster
a_iii = groupedValues{clust(iii)};
% average distance of iii to all other objects in the same cluster
a_i = sum(a_iii) / (size(a_iii, 1) - 1);
%disp(a_i);pause;
%%% end a(i)
%%% calculate b(i)
clusterIDs_new = clusterIDs;
% remove the cluster iii in
clusterIDs_new(find(clusterIDs_new == clust(iii))) = [];
% average distance of iii to all objects of another cluster
a_iii_2others = zeros(length(clusterIDs_new), 1);
for jjj = 1:length(clusterIDs_new)
values_another = groupedValues{clusterIDs_new(jjj)};
a_iii_2others(jjj) = mean(values_another);
endfor
b_i = min(a_iii_2others);
%disp(b_i);disp('---');pause;
%%% end b(i)
%%% calculate s(i)
si(iii) = (b_i - a_i) / max([a_i; b_i]);
%%% end s(i)
endfor
end