%% elman -------
numinputs = 64;
%net = newelm(repmat([0 1],numinputs,1),[70 50 2],{'tansig','tansig','tansig','satlins'});
net = newelm(repmat([0 1],numinputs,1),[70 50 3],{'tansig','tansig','tansig','satlins'});
net.trainParam.show = 1;


%% build t matrix (from single desired output vector)
[h w] = size(p);
t = repmat(t,1,900);
t = repmat({t},h,w);


%% assemble input
np = [];
nt = [];

%load ani
%np = [np p]; nt = [nt t];

%load ambient
%np = [np p]; nt = [nt t];

load trance
np = [np p]; nt = [nt t];

load house
np = [np p]; nt = [nt t];

load jungle
np = [np p]; nt = [nt t];

p = []; t = [];


%% mix up input
[h w] = size(np);
perm = randperm(w);
np = np(:,perm);
nt = nt(:,perm);


%% train
net = train(net,np,nt);


% train loop (do 10 epochs on 50 input sequences at a time, since i only have 512mb ram)
chunk = 40;
net.trainParam.epochs = 10;
s = 101;
for n = 1:100
  load n
  [h w] = size(np);
  if w < chunk + s
    s = 1;
  end

  np = np(s:s+chunk-1);
  nt = nt(s:s+chunk-1);
  s = s + chunk;

  net = train(net,np,nt);
  save nett net

%  net.trainParam.lr = net.trainParamlr / 1.1
end


% [ ani house . . . ]



plotsom(net.layers{1}.positions)






%% check accuracy!   (based on max of output)

yes = 0;
left = 0;
right = 0;
leftt = 0;
rightt = 0;
[h w] = size(np);
for n = 1:w
   s = np{n};
   sr = sim(net,s);
   r = mean(sr');                % only pay attention to secnd half of sequence output!
   [ r(1) r(2) nt{n}(1) nt{n}(2) ]
 
   % just get totals...
   if nt{n}(1)
     leftt = leftt + 1;
   end
   if nt{n}(2)
     rightt = rightt + 1;
   end

   % correctly classified?
   if and(r(1) > r(2), nt{n}(1))
     yes = yes + 1;
     left = left + 1;
   end
   if and(r(1) < r(2), nt{n}(2))
     yes = yes + 1;
     right = right + 1;
   end
end
[ yes w ]
[ left leftt ]
[ right rightt ]






%% train set
% for whole sequence
   508   595  total   85.3%
   212   298  ani     71.1
   296   297  house   99.6
% second half of sequence
   499   595 total    83.9
   202   298  ani     67.8 
   297   297  house  100

%% test set
% cure
ans =

    34    68

EDU>> [ left leftt ]

ans =

    10    29

EDU>> [ right rightt ]

ans =

    24    39


% nando

    64   123

EDU>> [ left leftt ]

ans =

     8    60

EDU>> [ right rightt ]

ans =

    56    63

EDU>>                                         





brc 800 483 2000 
circuit id = 10QGDB000674GTCA