public DecisionNet(DInput[] p_inputs, DOutput[] p_outputs, Matrix <float> p_weights)
{
if (!MatrixCalc.isSize(p_weights, p_inputs.Length, p_outputs.Length))
{
Debug.LogError("Constructing DecisionNet with wrong sized matrix");
}
m_inputs = p_inputs;
m_outputs = p_outputs;
m_weights = MatrixCalc.shallowClone(p_weights);
}
private void performOutputs(Matrix <float> p_output_values)
{
if (!MatrixCalc.isSize(p_output_values, 1, m_outputs.Length))
{
Debug.LogError("Trying to perform outputs in Decision net with malformed output_values matrix");
}
for (int i = 0; i < m_outputs.Length; i++)
{
m_outputs[i](p_output_values[0, i]);
}
}
public DecisionNetDNA(int p_id, DInputFactory <T>[] p_inputs, DOutputFactory <T>[] p_outputs, Matrix <float> p_weights, Range <float> p_mutation_multiplier)
{
if (!MatrixCalc.isSize(p_weights, p_inputs.Length, p_outputs.Length))
{
Debug.LogError("DecisionNetDNA requires Matrix input size inputs by outputs");
}
m_id = p_id;
m_inputs = ArrayCalc.shallowClone(p_inputs);
m_outputs = ArrayCalc.shallowClone(p_outputs);
m_weights = MatrixCalc.shallowClone(MatrixCalc.columnNormalize(p_weights));
m_mutation_multiplier = p_mutation_multiplier;
}