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extnolfi.cc

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void NolfiNet::indexInputs () {
    for (int i=0; i<cells.size; i++)
        if (cells[i].mFinalType==CT_OUTPUT)
            cells[i].mFinalID = int (cells[i].mCoord.y+0.5);
}

void NolfiNet::indexHiddens (int hiddens) {
    // Index the hidden units according to their X-position. This is
    // one easy way to solve the problem
    int ind=0;
    for (int i=0; i<hiddens; i++) {
        // Find the unindexed hidden cell with the smallest X coordinate
        double minX = 666.0;
        int minNeuron = -1;
        
        for (int j=0; j<cells.size; j++)
            if (cells[j].mFinalType==CT_HIDDEN && cells[j].mCoord.x<=minX &&
                cells[j].mFinalID==EMPTYID) {
                minX = cells[j].mCoord.x;
                minNeuron = j;
            }
        
        ASSERT (minNeuron!=-1);
        
        // Set the index of the smallest found unindexed cell
        cells[minNeuron].mFinalID = mInputs+ind;
        ind++;
    }
}

void NolfiNet::indexOutputs (int hiddens) {
    int totalUnits = mInputs+hiddens+mOutputs;
    for (int i=0; i<cells.size; i++)
        if (cells[i].mFinalType==CT_OUTPUT) {
            cells[i].mFinalID = mInputs+hiddens;//int ((mSize/mOutputs)/cells[i].mCoord.y);
            
            ASSERT (cells[i].mFinalID>=totalUnits-mOutputs);
            ASSERT (cells[i].mFinalID<totalUnits);
        }
}

void NolfiNet::removeDuplicates (int& rOutputs) {
    // Remove input and output cells with duplicate indices
    for (int i=0; i<cells.size; i++)
        for (int j=i+1; j<cells.size; j++)
            if (cells[i].mFinalID!=EMPTYID && cells[i].mFinalID == cells[j].mFinalID) {
                cells[j].mFinalID = EMPTYID;
                // We want to calculate the number of output units exactly
                if (cells[i].mFinalType==CT_OUTPUT)
                    rOutputs--;
            }
}

int NolfiNet::connect (FreeNetwork& network) {
    int connections=0;
    for (int i=0; i<cells.size; i++) {
        // (sout << cells[i]).print("\n");

        // Only the cells that have been given a neuron index
        if (cells[i].mFinalID!=EMPTYID) {
            FreeNeuron& neuron = network[cells[i].mFinalID];

            // Set the neuron attributes
            neuron.setBias (cells[i].mBias);
            neuron.moveTo (cells[i].mCoord);
            
            // Generate the branch tip points
            PackArray<Coord2D> tips;
            cells[i].developAxon (tips, mSize);
                    
            // Now find other cells that lie near these points
            for (int j=0; j<cells.size; j++)
                if (cells[j].mFinalID > cells[i].mFinalID && cells[j].mFinalType>CT_INPUT)
                    for (int k=0; k<tips.size; k++) {
                        double d = cells[j].mCoord.sqdist (tips[k]);
                        if (d < 25.0) {
                            // TRACE4 ("%d->%d: d(%d)=%f", i, j, k, d);
                            if (!neuron.connectedTo (cells[j].mFinalID)) {
                                // Found a new target, add it to the network
                                network.connect (cells[i].mFinalID, cells[j].mFinalID);
                                connections++;
                                break;  // Break from the k loop
                            }
                        }
                    }

            // Set the initial connection weights to the encoded weight
            for (int j=0; j<neuron.conns(); j++)
                neuron[j].setWeight (cells[i].mWeight);
        }
    }

    return connections;
}

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