Adaptive <GameStateWithInputs, GameInput> GetTestAdaptive(string hostname, int peerId, int bufferSize)
{
var game = new GameManager()
{
testInput = Vector3.right
};
var inputClock = new TestClock(framesPerSecond: 60, autostart: false, endOfFrame: true, startFrame: 0, name: string.Format("H{0} inputclock", hostname))
{
ExecutionOrder = 2
};
var network = new Network <GameStateWithInputs, GameInput> (inputClock, transport: new TestTransport(hostname), peerId: peerId);
var adaptive = new Adaptive <GameStateWithInputs, GameInput> (game, simulationDelay: bufferSize, inputClock: inputClock, simulationClock: new TestClock(framesPerSecond: 60, autostart: false, name: string.Format("H{0} simclock", hostname))
{
ExecutionOrder = 0
}, bufferClock: new TestClock(framesPerSecond: 60)
{
ExecutionOrder = 1
}, network: network);
adaptive.Simulation.InputHandler = delegate(GameStateWithInputs mutableState, System.Collections.Generic.KeyValuePair <int, GameInput>[] inputs, int frameIndex) {
foreach (var kv in inputs)
{
var input = kv.Value;
mutableState.Move(input.direction);
}
};
return(adaptive);
}
// Use this for initialization
void Start()
{
#if SERVER
Adaptive = new Adaptive <GameState, GameInput> (gameManager: this, maxPeerDelay: 2, simulationDelay: 1, port: 12500);
Adaptive.Simulation.InputHandler = HandleSimulationInputHandler;
Adaptive.Host(GetStartState());
#else
Adaptive = new Adaptive <GameState, GameInput> (gameManager: this, maxPeerDelay: 2, simulationDelay: 1, port: 12501);
Adaptive.Simulation.InputHandler = HandleSimulationInputHandler;
Adaptive.Connect("127.0.0.1", 12500);
#endif
}
/// <summary>
/// This is the method that actually does the work.
/// </summary>
/// <param name="DA">The DA object is used to retrieve from inputs and store in outputs.</param>
protected override void SolveInstance(IGH_DataAccess DA)
{
IGH_Goo goo = null;
Image image = new Image();
if (!DA.GetData(0, ref goo))
{
return;
}
if (!goo.TryGetImage(ref image))
{
return;
}
int mode = 0;
DA.GetData(1, ref mode);
int numValA = 1;
DA.GetData(2, ref numValA);
int numValB = 1;
DA.GetData(3, ref numValB);
Filter filter = new Filter();
int[] indices = new int[] { 2, 3 };
switch ((FilterModes)mode)
{
case FilterModes.Adaptive:
ClearParameters(indices);
filter = new Adaptive();
image.Filters.Add(new Adaptive());
break;
case FilterModes.Conservative:
ClearParameters(indices);
filter = new Conservative();
image.Filters.Add(new Conservative());
break;
case FilterModes.Median:
ClearParameters(indices);
filter = new Median();
image.Filters.Add(new Median());
break;
case FilterModes.Gaussian:
SetParameter(2, "D", "Divisor", "Division factor");
SetParameter(3, "T", "Threshold", "Threshold weighted sum");
filter = new Gaussian(numValA, numValB);
image.Filters.Add(new Gaussian(numValA, numValB));
break;
case FilterModes.HighBoost:
SetParameter(2, "D", "Divisor", "Division factor");
SetParameter(3, "T", "Threshold", "Threshold weighted sum");
filter = new HighBoost(numValA, numValB);
image.Filters.Add(new HighBoost(numValA, numValB));
break;
case FilterModes.Mean:
SetParameter(2, "D", "Divisor", "Division factor");
SetParameter(3, "T", "Threshold", "Threshold weighted sum");
filter = new Mean(numValA, numValB);
image.Filters.Add(new Mean(numValA, numValB));
break;
case FilterModes.Simple:
SetParameter(2, "D", "Divisor", "Division factor");
SetParameter(3, "T", "Threshold", "Threshold weighted sum");
filter = new Simple(numValA, numValB);
image.Filters.Add(new Simple(numValA, numValB));
break;
}
message = ((FilterModes)mode).ToString();
UpdateMessage();
DA.SetData(0, image);
DA.SetData(1, filter);
}
