public static CSNeuroNet FromByteArray(byte[] array)
{
int i = 0;
int inputsc = BitConverter.ToInt32(array, i); i += 4;
int outputsc = BitConverter.ToInt32(array, i); i += 4;
CSNeuroNet result = new CSNeuroNet(inputsc, outputsc);
int nodesC = BitConverter.ToInt32(array, i); i += 4;
for (int k = 0; k < nodesC; ++k)
{
Node n = new Node(BitConverter.ToInt32(array, i)); i += 4;
n.Value = BitConverter.ToDouble(array, i); i += 8;
result.AddNode(n);
}
int connectionsCount = BitConverter.ToInt32(array, i); i += 4;
for (int k = 0; k < connectionsCount; ++k)
{
int id = BitConverter.ToInt32(array, i); i += 4;
int from = BitConverter.ToInt32(array, i); i += 4;
int to = BitConverter.ToInt32(array, i); i += 4;
double weight = BitConverter.ToDouble(array, i); i += 8;
Connection c = new Connection(id, from, to, weight);
result.AddConnection(c);
}
return(result);
}
public byte[] ToByteArray()
{
CSNeuroNet copy = new CSNeuroNet(this);
//copy.Optimize();
List <byte> result = new List <byte>();
result.AddRange(BitConverter.GetBytes(copy.Inputs));
result.AddRange(BitConverter.GetBytes(copy.Outputs));
result.AddRange(BitConverter.GetBytes(copy.Nodes.Count - Inputs - Outputs));
foreach (Node n in copy.Nodes)
{
if (n.ID > Inputs + Outputs - 1)
{
result.AddRange(BitConverter.GetBytes(n.ID));
result.AddRange(BitConverter.GetBytes(n.Value));
}
}
result.AddRange(BitConverter.GetBytes(copy.Connections.Count));
foreach (Connection c in copy.Connections)
{
result.AddRange(BitConverter.GetBytes(c.ID));
result.AddRange(BitConverter.GetBytes(c.From));
result.AddRange(BitConverter.GetBytes(c.To));
result.AddRange(BitConverter.GetBytes(c.Weight));
}
return(result.ToArray());
}
// Use this for initialization
public void Start(int passes)
{
BestFromPasses = new Dictionary <int, Tuple <double, CSNeuroNet> >();
ET.Init();
for (int i = 0; i < passes; ++i)
{
bool wasP = false;
Console.WriteLine("Starting pass {0}", i);
ET.PassGeneration();
ET.LastResult.Sort((x, y) =>
{
if (x.a > y.a)
{
return(1);
}
else if (x.a < y.a)
{
return(-1);
}
else
{
return(0);
}
});
var max = ET.LastResult[ET.LastResult.Count - 1];
BestFromPasses.Add(i, new Tuple <double, CSNeuroNet>(max.a, max.b));
Console.WriteLine("Minimum is: {0:F5}, Maximum: {1:F5}, medium: {2:F5}", ET.LastResult.Min(x => x.a), max.a, ET.LastResult.ConvertAll(x => x.a).Average(x => x));
Console.WriteLine("Best net: {0}", max.b);
Console.WriteLine("Pass {0} have been passed", i);
if (pause)
{
Console.WriteLine("Pausing...");
wasP = true;
}
while (pause)
{
Thread.Sleep(100);
}
if (wasP)
{
Console.WriteLine("Continueing");
}
}
neuro = ET[ET.Individuals - 1];
while (true)
{
}
}
public CSNeuroNet(CSNeuroNet copy)
{
Copies = copy.Copies;
Nodes = new List <Node>();
outputs = new List <Node>();
inputs = new List <Node>();
Inputs = copy.Inputs;
Outputs = copy.Outputs;
copy.Nodes.ForEach(x =>
{
Node n = new Node(x);
Nodes.Add(n);
if (x.ID < Inputs)
{
inputs.Add(n);
}
else if (x.ID < Inputs + Outputs)
{
outputs.Add(n);
}
});
Connections = new List <Connection>();
copy.Connections.ForEach(x =>
{
Connection c = new Connection(x);
Connections.Add(c);
});
}
public double Test(CSNeuroNet nn)
{
Vector2 pos = new Vector2(0.0, 10.0);
Vector2 vel = new Vector2((double)((0.5) * 5), 0.0);
Vector2 player = new Vector2(0.0, 0.0);
Vector2 grav = new Vector2(0.0, -30.0);
Vector2 controller = new Vector2(10.0, 0.0);
double time = 0.04;
nn.Flush();
double overall = 0.0;
int hj = 0;
int max = 75;
while (hj++ < max)
{
Random r = new Random(hj + 4723);
Random rad = new Random(hj + 1234);
Func <double, double, double> randF = (x, y) =>
{
return((double)(rad.NextDouble() * ((double)y - x) + x));
};
double fr = randF(-2, 2);
double fr2 = randF(-2, 2);
controller = new Vector2(17.0, 0.0);
pos = new Vector2(randF(-5, 5), randF(3, 20));
int diff = hj / 4;
int maxDiff = max / 4;
double diffC = (diff / (double)maxDiff);
vel = new Vector2(randF(-5, 5) + randF(-1, 1) * diffC * controller.x, randF(-1, 1) + randF(-4, 0) * diffC);
player = new Vector2(0.0, 0.0);
grav = new Vector2(0.0, -35.0);
double curTim = 0;
while (true)
{
var res = nn.Calculate(new double[] { player.x, player.y, pos.x, pos.y, vel.x, vel.y, time, controller.x, grav.y, -10.0, 10.0, -0.5, 0.5 });
if (res[0] > 0.6)
{
player -= controller * time;
}
if (res[1] > 0.6)
{
player += controller * time;
}
if (player.x > 10.0)
{
player.x = 10.0;
}
else if (player.x < -10.0)
{
player.x = -10.0;
}
vel = vel + grav * time;
pos += vel * time;
if (pos.x > 10.0)
{
pos.x = 10.0;
vel.x = -vel.x;
}
else if (pos.x < -10.0)
{
pos.x = -10.0;
vel.x = -vel.x;
}
if (pos.y < 0.0)
{
if ((pos.x < player.x + 0.5) && (pos.x > player.x - 0.5))
{
pos.y = 0.0;
vel.y = -vel.y;
vel.x = vel.x + (pos.x - player.x) + (double)((r.NextDouble() - 0.5) * 2);
}
else
{
break;
}
}
curTim += time;
if ((pos.x < player.x + 0.5) && (pos.x > player.x - 0.5))
{
curTim += time * 2;
}
if (curTim > 40.0)
{
break;
}
}
overall += curTim * diffC;
}
if (overall > record)
{
record = overall;
Console.WriteLine("New record! {0:F5} by net: {1}", record, nn);
}
return(overall);
}
