void EssexWriter::write(NeuralNetwork &nn,ostream &os)
{
// Process layers
nn.setIndices();
nn.findLayers();
const int numNeurons=nn.getNumNeurons();
Array1D<int> layers(numNeurons);
computeLayers(nn,layers);
int outputLayer=0;
for(int i=0 ; i<numNeurons ; ++i)
if(layers[i]>outputLayer) outputLayer=layers[i];
// Generate output
os<<"(network\n";
for(int i=0 ; i<numNeurons ; ++i) {
Neuron &neuron=nn[i];
const int layer=layers[i];
bool isInput=layer==0, isOutput=layer==outputLayer;
os<<" (neuron "<<i<<" (layer "<<layers[i]<<")";
if(isInput) { os<<")"<<endl; continue; }
os<<" (transfer sigmoid)";
if(isOutput) os<<" (output)";
os<<" (value "<<neuron.getActivationValue()<<")";
const int inDeg=neuron.getInDegree();
if(inDeg>0) os<<endl;
for(int j=0 ; j<inDeg ; ++j) {
Synapse &synapse=neuron.getInput(j);
const int from=synapse.getFrom();
const float weight=synapse.getWeight();
os<<" (input (from "<<from<<") (weight "<<weight<<"))";
if(j+1<inDeg) os<<endl;
}
os<<")";
if(i+1<numNeurons) os<<endl;
}
os<<")\n"<<endl;
}
