public TileMap(string path, int size)
{
this.size = size;
tileMap = new List2D <char>();
using (StreamReader sr = new StreamReader(path))
{
while (!sr.EndOfStream)
{
string line = sr.ReadLine();
List <char> lineList = new List <char>();
for (int i = 0; i < line.Length; i++)
{
lineList.Add(line[i]);
if (line[i] == 'P')//indicate that the player start here
{
playerPosition = new Vector2(i * Size, tileMap.Count * Size);
}
if (line[i] == '@')
{
npcPosition.Add(new Vector2(i * Size, tileMap.Count * Size));
}
}
tileMap.Add(lineList);
}
}
}
//Constructor for single sprite
public Sprite(string path)
{
graph = new List2D <char>();
using (StreamReader sr = new StreamReader(path))
{
while (!sr.EndOfStream)
{
string line = sr.ReadLine();
List <char> lineList = new List <char>();
for (int i = 0; i < line.Length; i++)
{
lineList.Add(line[i]);
}
Console.WriteLine(line);
graph.Add(lineList);
}
}
size.Y = graph.Count * 2;
size.X = graph[0].Count * 2;
}
public Megachunk LoadMegachunk(int x, int y)
{
Megachunk mc = null;
mc = new Megachunk(x, y, graphicsDevice, generator, () => {
megachunks.Remove(x, y);
});
megachunks.Add(x, y, mc);
return(mc);
}
//create a sprite with a tab in text
//Constructor for animation
public Sprite(string text, Vector2 position)
{
graph = new List2D <char>();
using (StringReader sr = new StringReader(text))
{
string line;
while ((line = sr.ReadLine()) != null)
{
List <char> lineList = new List <char>();
for (int i = 0; i < line.Length; i++)
{
lineList.Add(line[i]);
}
Console.WriteLine(line);
graph.Add(lineList);
}
}
size.Y = graph.Count * 2;
size.X = graph[0].Count * 2;
}
public void UpdateLoadedArea(int x, int y, int width, int height, WorldLoader worldLoader)
{
Rect newrect = new Rect(x - 3, y - 3, width + 6, height + 6);
if (newrect.Equals(lastRect))
{
return;
}
Rect newDrawRect = new Rect(x, y, width, height);
ChunksLoaded.ForEachWrapper((cw) => {
int j = cw.x;
int i = cw.y;
if (!newrect.Contains(j, i))
{
Chunk chunk = ChunksLoaded.Get(j, i);
if (chunk == null)
{
return;
}
UnloadChunk(chunk);
}
});
ChunksVisible.ForEachWrapper((cw) => {
int j = cw.x;
int i = cw.y;
if (!newDrawRect.Contains(j, i))
{
ChunksVisible.Remove(j, i);
}
});
for (int i = newrect.Y; i < newrect.Y + newrect.Height; i++)
{
for (int j = newrect.X; j < newrect.X + newrect.Width; j++)
{
if (!ChunksLoaded.Includes(j, i))
{
Chunk chunk = worldLoader.LoadChunk(j, i);
if (chunk == null)
{
continue;
}
chunk.Load();
ChunksLoaded.Add(j, i, chunk);
}
if (newDrawRect.Contains(j, i))
{
Chunk chunk = ChunksLoaded.Get(j, i);
if (chunk == null)
{
continue;
}
ChunksVisible.Add(j, i, chunk);
}
}
}
lastRect = newrect;
lastDrawRect = newDrawRect;
}
private void Initialize(InputData input, OutputData output)
{
inputLength = input.data[0].Count;
outputLength = output.data[0].Count;
Debug.Log("input size = " + inputLength + ", output size = " + outputLength);
sizes = new List <int>();
sizes.Add(inputLength);
if (hiddenLayers == null)
{
sizes.Add((int)Math.Max(3, Math.Floor((double)(inputLength / 2))));
}
else
{
foreach (int size in hiddenLayers)
{
sizes.Add(size);
}
}
sizes.Add(outputLength);
outputLayer = sizes.Count - 1; // index du niveau de sortie
biases = new List2D <double>(); // weights for bias nodes
weights = new List3D <double>();
outputs = new List2D <double>();
// state for training
deltas = new List2D <double>();
changes = new List3D <double>();
errors = new List2D <double>();
// On remplit chaque niveau du réseau
for (int layer = 0; layer <= outputLayer; ++layer)
{
int size = (int)sizes[layer]; // numéro du niveau
deltas.Add(Zeros(size)); // On remplit les deltas du niveau avec des zéros
errors.Add(Zeros(size)); // On remplit les erreurs du niveau avec des zéros
outputs.Add(Zeros(size)); // On remplit la sortie du niveau avec des zéros
if (layer == 0)
{
biases.Add(new List <double>());
weights.Add(new List2D <double>());
changes.Add(new List2D <double>());
}
if (layer > 0)
{
biases.Add(Randos(size)); // les biais sont initialisés de façon random
weights.Add(new List2D <double>()); // les poids sont vides
changes.Add(new List2D <double>()); // les modifs sont vides
for (int node = 0; node < size; ++node) // pour chaque neurone du niveau
{
int prevSize = (int)sizes[layer - 1];
weights[layer].Add(Randos(prevSize)); // le poids du neurone est random
changes[layer].Add(Zeros(prevSize)); // les modifs valent 0
}
}
}
SetActivation();
}
