MATLAB: Example from patternnet docs fails in Neural Network Toolbox Version 10.0 (R2017a)

neural networkspatternnet

I'd remove this post now if I could. Tracking down the function name conflict has been difficult. The code attached to this answer https://www.mathworks.com/matlabcentral/answers/100197-is-there-any-way-to-list-all-shadowed-files-in-the-matlab-path-in-matlab-7-8-2009a#answer_109545 got me started.
Original problem: Trying to run the example from
 help paternnet
but get:
Index exceeds matrix dimensions.
Error in initnw>initialize_layer (line 168)
       range(inputStart(j):inputStop(j),:) = temp2((inputStart(j):inputStop(j))-inputStart(j)+1,:);
Complete code (revised):
% NNTest from help patternnet
clear all
clc
dbstop if error
[x,t] = iris_dataset;
net = patternnet(10);
net = train(net,x,t);
Complete output:
Index exceeds matrix dimensions.
Error in initnw>initialize_layer (line 168)
     range(inputStart(j):inputStop(j),:) = temp2((inputStart(j):inputStop(j))-inputStart(j)+1,:);
Error in initnw (line 93)
  out1 = initialize_layer(in1,in2);
Error in initlay>initialize_network (line 147)
    net = feval(initFcn,net,i);
Error in initlay (line 89)
  out1 = initialize_network(in1);
Error in network/init (line 32)
net = feval(initFcn,net);
Error in network/configure (line 243)
net = init(net);
Error in nntraining.config (line 116)
net = configure(network(net),X,T);
Error in nntraining.setup>setupPerWorker (line 68)
[net,X,Xi,Ai,T,EW,Q,TS,err] = nntraining.config(net,X,Xi,Ai,T,EW,configNetEnable);
Error in nntraining.setup (line 43)
[net,data,tr,err] = setupPerWorker(net,trainFcn,X,Xi,Ai,T,EW,enableConfigure);
Error in network/train (line 335)
[net,data,tr,err] = nntraining.setup(net,net.trainFcn,X,Xi,Ai,T,EW,enableConfigure,isComposite);
Error in NNTest (line 7)
net = train(net,x,t); 
Version information:
 MATLAB Version: 9.2.0.556344 (R2017a)
 Neural Network Toolbox   Version 10.0    (R2017a)
OS info:
 Mac OS X 10.11.6 (15G1611)

Best Answer

 clear all
clc
  %stoperr
  %Undefined function or variable 'stoperr'.
%   [x,t] = iris_dataset;
%      net = patternnet(10);
%      net = train(net,x,t);
%      view(net)
%      y = net(x);
%      perf = perform(net,t,y) %0.0302
%      classes = vec2ind(y);
 %    end
 %  Error: Illegal use of reserved keyword "end".
 close all, clear all, clc
 [ x,t ] = iris_dataset;
 [ I N ] = size(x)% [ 4 150 ]
 [ O N ] = size(t)% [ 3 150]
 truclass = vec2ind(t); % 1 to 3
 MSEref  = mse(t-mean(t,2)) % 0.2222
 rng(0), Ntrials = 10
 for h = 1:10   % No. of hidden nodes
    net = patternnet(h);
    for n = 1:Ntrials
        net = configure(net,x,t);
       [net tr y e ] = train(net,x,t);
       % y = net(x); e = t-y;
       NMSE(h,n)   = mse(e)/MSEref;   
       predclass   = vec2ind(y);
       PCTERR(h,n) = 100*mean(predclass~=truclass);
    end
 end
 PCTERR = PCTERR 
 %  Columns 1 through 5
% 


%     2.6667    2.0000    2.0000    3.3333    2.6667
%     2.0000    1.3333    2.6667    2.0000    2.0000
%     2.0000    2.0000    4.0000    0.6667    2.6667
%     1.3333    4.0000    4.0000    1.3333    1.3333
%     2.0000    3.3333    3.3333    2.6667    1.3333
%     3.3333    2.0000    2.6667    1.3333    2.0000
%     2.6667    4.6667    3.3333    4.0000    3.3333
%     1.3333    1.3333    2.6667    2.0000    4.6667
%     2.6667    0.6667    2.6667    1.3333    1.3333
%     2.0000    1.3333    1.3333    1.3333    4.0000
% 
%   Columns 6 through 10
% 
%     3.3333    2.6667    2.0000    2.6667    2.0000
%     1.3333   68.6667    1.3333    2.6667    6.0000
%     1.3333    2.6667    2.6667    1.3333    1.3333
%     1.3333    3.3333    3.3333    4.0000    2.6667
%     3.3333    2.0000    1.3333    2.0000    1.3333
%     1.3333    1.3333    1.3333    2.6667    1.3333
%     2.0000    2.6667    2.6667    2.6667    1.3333
%     2.0000    1.3333    1.3333    2.0000    1.3333
%     3.3333    4.0000    3.3333    2.0000    2.0000
%     1.3333    1.3333    2.0000    2.6667    1.3333
Hope this helps,
Thank you for formally accepting my answer
Greg
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