public Tree(Vector Pos, VectorI ChunkPos, float StartEnergy = 5)
{
Col = Color.SaddleBrown;
LeafColor = Color.ForestGreen;
BranchColor = Color.SaddleBrown;
this.Pos = Pos;
this.ChunkPos = ChunkPos;
Timer = Form1.Rand.Next(MaxTimer);
Energy = StartEnergy;
//Inputs: TreeAge,TreeEnergy,IsBranch,Layer,ChildBranches,ChildLeaves,LocalEnergy(if branch sum of all children),LocalAge,HasFlower,FruitRatio
//Outputs: SpawnLeaf(if below -1, drop instead),LeafAngle1,LeafAngle2,LeafAngle3,SpawnBranch,BranchAngle1,BranchAngle2,ThickerBranch,LongerBranch,SpawnSeed,SpawnFlower,FruitRate
int InputCount = 10;
int OutputCount = 12;
NeuralNetwork = new FeedForwardNetwork(InputCount, OutputCount, 8, 1, NeuralNetwork.OutputType.Linear);
Inputs = new float[InputCount];
FeedForwardNetwork N = NeuralNetwork as FeedForwardNetwork;
/*for (int i = 0; i < N.WeightMatrix[0].Length; i++)
* {
* N.WeightMatrix[0][i][0] = 0;
* }
* for (int i = 0; i < N.WeightMatrix[1].Length; i++)
* {
* N.WeightMatrix[1][i][9] = 0;
* }*/
/*N.WeightMatrix[N.ToIndex(0,3,0)] = 0.1f;
* N.WeightMatrix[N.ToIndex(0, 1, 0)] = 2;
* N.WeightMatrix[N.ToIndex(0, 10, 0)] = -2;
* N.WeightMatrix[N.ToIndex(1, 0, 9)] = 1;
*
* //N.WeightMatrix[0][0][0] = 1;
* N.WeightMatrix[N.ToIndex(0, 5, 1)] = -1;
* N.WeightMatrix[N.ToIndex(0, 3, 1)] = -0.5f;
* N.WeightMatrix[N.ToIndex(0, 10, 1)] = -0.3f;
* N.WeightMatrix[N.ToIndex(0, 1, 1)] = 1;
* N.WeightMatrix[N.ToIndex(1, 1, 0)] = 1;
* N.WeightMatrix[N.ToIndex(1, 1, 4)] = 1;
*
* N.WeightMatrix[N.ToIndex(0, 6, 2)] = 2;
* N.WeightMatrix[N.ToIndex(1, 8, 1)] = 0.5f;
* N.WeightMatrix[N.ToIndex(1, 2, 2)] = 2f;
*
* //N.WeightMatrix[1][8][9] = -1f;
*
* N.Mutate(MutationRate);*/
N.GenerateRandom(-2, 2);
Root = new Branch(this, null, 3, 0, 0);
AddLeaf(Root, new Leaf(Root, 40, Form1.Rand.Next(0, 360), 0));
Branches.Add(Root);
UpdateArea();
}
public FeedForwardNetwork(FeedForwardNetwork OldNetwork)
{
InputCount = OldNetwork.InputCount;
OutputCount = OldNetwork.OutputCount;
NeuronCount = OldNetwork.NeuronCount;
Layers = OldNetwork.Layers;
outputType = new OutputType[OldNetwork.outputType.Length];
OldNetwork.outputType.CopyTo(outputType, 0);
Neurons = new float[Layers][];
WeightMatrix = new float[OldNetwork.WeightMatrix.Length];
for (int i = 0; i < Neurons.Length; i++)
{
Neurons[i] = new float[OldNetwork.Neurons[i].Length];
}
for (int i = 0; i < WeightMatrix.Length; i++)
{
WeightMatrix[i] = OldNetwork.WeightMatrix[i];
}
}