/// <summary>
/// Constructs a AcyclicNeuralNet with the provided neural net definition parameters.
/// </summary>
/// <param name="digraph">Network structure definition</param>
/// <param name="weightArr">Connection weights array.</param>
/// <param name="activationFn">Node activation function.</param>
public NeuralNetAcyclic(
DirectedGraphAcyclic digraph,
double[] weightArr,
VecFnSegment <double> activationFn)
{
// Store refs to network structure data.
_srcIdArr = digraph.ConnectionIdArrays._sourceIdArr;
_tgtIdArr = digraph.ConnectionIdArrays._targetIdArr;
_weightArr = weightArr;
_layerInfoArr = digraph.LayerArray;
// Store network activation function.
_activationFn = activationFn;
// Store input/output node counts.
_inputCount = digraph.InputCount;
_outputCount = digraph.OutputCount;
// Create working array for node activation signals.
_activationArr = new double[digraph.TotalNodeCount];
// Wrap a sub-range of the _activationArr that holds the activation values for the input nodes.
this.InputVector = new VectorSegment <double>(_activationArr, 0, _inputCount);
// Wrap the output nodes. Nodes have been sorted by depth within the network therefore the output
// nodes can no longer be guaranteed to be in a contiguous segment at a fixed location. As such their
// positions are indicated by outputNodeIdxArr, and so we package up this array with the node signal
// array to abstract away the indirection described by outputNodeIdxArr.
this.OutputVector = new MappingVector <double>(_activationArr, digraph.OutputNodeIdxArr);
}
/// <summary>
/// Constructs a AcyclicNeuralNet with the provided neural net definition parameters.
/// </summary>
/// <param name="digraph">Network structure definition</param>
/// <param name="activationFn">Node activation function.</param>
/// <param name="boundedOutput">Indicates that the output values at the output nodes should be bounded to the interval [0,1]</param>
public AcyclicNeuralNet(
WeightedAcyclicDirectedGraph <double> digraph,
VecFnSegment <double> activationFn,
bool boundedOutput)
: this(digraph, digraph.WeightArray, activationFn, boundedOutput)
{
}
/// <summary>
/// Constructs a AcyclicNeuralNet with the provided neural net definition parameters.
/// </summary>
/// <param name="digraph">Network structure definition</param>
/// <param name="activationFn">Node activation function.</param>
public NeuralNetAcyclic(
WeightedDirectedGraphAcyclic <double> digraph,
VecFnSegment <double> activationFn)
: this(digraph, digraph.WeightArray, activationFn)
{
}
