% MLTC2NARX multilayer time-course to narx network
%    [narx] = mltc2narx(net,d)
%     net : multilayer time-course network
%       d : delay lines
%    narx : narx network
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

function [narx] = mltc2narx(net,d)

% Get input range for real inputs
R = net.inputs{1}.range;
n = size(R,1)-length(d);
Pr = R(1:n,:);

% Get layer dimensions for all but first two
h = zeros(1,net.numLayers-2);
for i = 1:length(h)
   h(i) = net.layers{i+2}.dimensions;
end

% Get transfer functions for all but first two
TF = cell(1,net.numLayers-2);
for i = 1:length(TF)
   TF{i} = net.layers{i+2}.transferFcn;
end

% Create narx network
narx = newnarx(Pr,0,d,h,TF);
nl = narx.numLayers;
narx.biasConnect = zeros(nl,1);

% Disconnect all layers
narx.layerConnect = zeros(size(narx.layerConnect));

% Set input weights
narx.IW{1} = net.LW{3,2};

% Connect feedforward layers and assign weights
for i = 2:size(narx.layerConnect,1)
   narx.layerConnect(i,i-1) = 1;
   narx.LW{i,i-1} = net.LW{i+2,i+1};
end

% Set biases
for i = 1:nl
   if net.biasConnect(i+2)
      narx.b{i} = net.b{i+2};
   end
end

% Connect delay layers and assign weights
for i = 1:nl
   if net.layerConnect(i+2,1)
      narx.layerConnect(i,nl) = 1;
      narx.layerWeights{i,nl}.delays = d;
      narx.LW{i,nl} = net.LW{i+2,1};
   end
end