public void TestNetworkSumOutputPort()
{
var multipliers = new Dictionary <int, IReceptiveField>();
multipliers[0] = new MulReceptiveField(0.0, 1.0);
multipliers[1] = new MulReceptiveField(1.0, 1.0);
multipliers[2] = new MulReceptiveField(2.0, 1.0);
multipliers[3] = new MulReceptiveField(3.0, 1.0);
multipliers[4] = new MulReceptiveField(4.0, 1.0);
multipliers[5] = new MulReceptiveField(5.0, 1.0);
multipliers[6] = new MulReceptiveField(6.0, 1.0);
multipliers[7] = new MulReceptiveField(7.0, 1.0);
multipliers[8] = new MulReceptiveField(8.0, 1.0);
multipliers[9] = new MulReceptiveField(9.0, 1.0);
// 0, 1, 2, 3, 4, 5, 6, 7, 8, 9
// 0, 1, 0, 1, 0, 1, 0, 1, 0, 1
var arr = Enumerable.Range(0, 10)
.Select(i => (double)(i % 2) * 30.0)
.ToArray();
Assert.AreEqual(arr.Length, multipliers.Count);
var port = new NetworkSumOutputPort(arr, multipliers);
var sum = port.Get();
Assert.AreEqual(25.0, sum);
}
public void TestNetworkSumOutputPort()
{
var multipliers = new Dictionary<int, IReceptiveField>();
multipliers[0] = new MulReceptiveField(0.0, 1.0);
multipliers[1] = new MulReceptiveField(1.0, 1.0);
multipliers[2] = new MulReceptiveField(2.0, 1.0);
multipliers[3] = new MulReceptiveField(3.0, 1.0);
multipliers[4] = new MulReceptiveField(4.0, 1.0);
multipliers[5] = new MulReceptiveField(5.0, 1.0);
multipliers[6] = new MulReceptiveField(6.0, 1.0);
multipliers[7] = new MulReceptiveField(7.0, 1.0);
multipliers[8] = new MulReceptiveField(8.0, 1.0);
multipliers[9] = new MulReceptiveField(9.0, 1.0);
// 0, 1, 2, 3, 4, 5, 6, 7, 8, 9
// 0, 1, 0, 1, 0, 1, 0, 1, 0, 1
var arr = Enumerable.Range(0, 10)
.Select(i => (double)(i % 2) * 30.0)
.ToArray();
Assert.AreEqual(arr.Length, multipliers.Count);
var port = new NetworkSumOutputPort(arr, multipliers);
var sum = port.Get();
Assert.AreEqual(25.0, sum);
}
public NetworkPorts(Neural.Network network,
IDictionary <int, IReceptiveField> upperNeurons,
IDictionary <int, IReceptiveField> lowerNeurons,
IDictionary <int, IReceptiveField> positionNeurons,
IDictionary <int, IReceptiveField> speedNeurons
)
{
this.network = network;
this.input = new double[network.NeuronCount];
this.output = new double[network.NeuronCount];
UpperTheta = new NetworkInputPort(input, upperNeurons);
LowerTheta = new NetworkInputPort(input, lowerNeurons);
Position = new NetworkInputPort(input, positionNeurons);
Speed = new NetworkSumOutputPort(output, speedNeurons);
}
public NetworkPorts(Neural.Network network,
IDictionary<int, IReceptiveField> upperNeurons,
IDictionary<int, IReceptiveField> lowerNeurons,
IDictionary<int, IReceptiveField> positionNeurons,
IDictionary<int, IReceptiveField> speedNeurons
)
{
this.network = network;
this.input = new double[network.NeuronCount];
this.output = new double[network.NeuronCount];
UpperTheta = new NetworkInputPort(input, upperNeurons);
LowerTheta = new NetworkInputPort(input, lowerNeurons);
Position = new NetworkInputPort(input, positionNeurons);
Speed = new NetworkSumOutputPort(output, speedNeurons);
}
