public static double SimpleLinearVal(WaveData low_betaWD, WaveData high_betaWD)
{
return((low_betaWD.NormalizedValue() + high_betaWD.NormalizedValue()) / 2.0);
}
static void Application_Idle(object sender, EventArgs e)
{
Stopwatch stopWatch = new Stopwatch();
double currentAcceleration = 0;
double currentPosition = 0;
double maxAcceleration = 1;
bool haveWon = false;
while (true)
{
if (engine.EngineGetNumUser() > 0)
{
engine.IEE_FFTSetWindowingType(0, EdkDll.IEE_WindowingTypes.IEE_HAMMING);
}
engine.ProcessEvents(100);
WaveData alphaWD = new WaveData("alpha");
WaveData low_betaWD = new WaveData("low_beta");
WaveData high_betaWD = new WaveData("high_beta");
WaveData gammaWD = new WaveData("gamma");
WaveData thetaWD = new WaveData("theta");
double[] alpha = new double[1];
double[] low_beta = new double[1];
double[] high_beta = new double[1];
double[] gamma = new double[1];
double[] theta = new double[1];
EdkDll.IEE_DataChannel_t[] channelList = new EdkDll.IEE_DataChannel_t[5] {
EdkDll.IEE_DataChannel_t.IED_AF3, EdkDll.IEE_DataChannel_t.IED_AF4, EdkDll.IEE_DataChannel_t.IED_T7,
EdkDll.IEE_DataChannel_t.IED_T8, EdkDll.IEE_DataChannel_t.IED_O1
};
for (int i = 0; i < 5; i++)
{
engine.IEE_GetAverageBandPowers(0, channelList[i], theta, alpha, low_beta, high_beta, gamma);
//Console.Write(theta[0] + ",");
//Console.Write(alpha[0] + ",");
//Console.Write(low_beta[0] + ",");
//Console.Write(high_beta[0] + ",");
//Console.WriteLine(gamma[0] + ",");
//Console.WriteLine("");
alphaWD.AddVal(alpha[0]);
low_betaWD.AddVal(low_beta[0]);
high_betaWD.AddVal(high_beta[0]);
gammaWD.AddVal(gamma[0]);
thetaWD.AddVal(theta[0]);
}
if (!stopWatch.IsRunning)
{
stopWatch.Start();
Console.WriteLine("Starting stopwatch.");
}
else
{
stopWatch.Stop();
long timeDeltaTicks = stopWatch.ElapsedTicks;
double accChange = AccelerationChange(alphaWD, low_betaWD, high_betaWD, thetaWD, gammaWD);
//Console.WriteLine("Acceleration change: " + accChange);
currentAcceleration = BindToMaxValue(currentAcceleration + accChange, maxAcceleration);
//double newPosition = currentPosition + 0.5 * currentAcceleration * timeDeltaTicks * timeDeltaTicks;
double newPosition = currentPosition + 0.5 * currentAcceleration; // Time is unitary
Console.WriteLine("CurrAcc: {0}, TimeDelta: {1}, NewPos: {2}",
currentAcceleration, timeDeltaTicks, newPosition);
displayInputHandler.ApplyNewScaledValueForMeasure(Math.Log(Math.Abs(newPosition), 100));
if (newPosition > 1)
{
haveWon = true;
// END PROGRAM
}
else if (newPosition < 0)
{
currentPosition = 0;
currentAcceleration = 0;
}
else
{
currentPosition = newPosition;
}
//double currentPosition = SimpleLinearVal(low_betaWD, high_betaWD);
Console.WriteLine(currentPosition);
if (!Double.IsNaN(currentPosition))
{
//Console.WriteLine("New position (formerly Awesome value):" + currentPosition);
displayInputHandler.ApplyNewScaledValueForBall(currentPosition);
}
stopWatch.Reset();
stopWatch.Start();
}
Application.DoEvents();
if (haveWon)
{
ThreadPool.QueueUserWorkItem(
delegate(object param)
{
WMPLib.WindowsMediaPlayer player = new WMPLib.WindowsMediaPlayer();
try
{
player.URL = "resources\\bell.mp3";
}
catch (Exception)
{
// Nada
}
player.controls.play();
});
Console.WriteLine("VICTORY!");
Thread.Sleep(3000);
exitGame();
}
Thread.Sleep(30);
}
}
// Assumption: brain waves are equally likely to be of any power. Goal: keep return value of this function statistically between -1 and 1.
// Method: tinker with
public static double AccelerationChange(WaveData alphaWD, WaveData low_betaWD, WaveData high_betaWD, WaveData thetaWD, WaveData gammaWD)
{
Console.WriteLine("Waves: A: {0}, LB: {1}, HB: {2}, T: {3}, G: {4}", alphaWD.DecibelValue(), low_betaWD.DecibelValue(), high_betaWD.DecibelValue(), thetaWD.DecibelValue(), gammaWD.DecibelValue());
double sum = 0;
double scalingFactor = 1;
double gravity = 0;
double[] waveValues = new double[] { low_betaWD.DecibelValue(), high_betaWD.DecibelValue(), alphaWD.DecibelValue(), thetaWD.DecibelValue(), gammaWD.DecibelValue() };
//// SUMS
//double weightedSum = 1.0 * low_betaWD.NormalizedValue() + 1.0 * high_betaWD.NormalizedValue() + 0.5 * alphaWD.NormalizedValue() - 1.5 * thetaWD.NormalizedValue() - 0.5 * gammaWD.NormalizedValue();
double mixedWeightedSum = 1.0 * low_betaWD.DecibelValue() + 1.0 * high_betaWD.DecibelValue() + 0.5 * alphaWD.DecibelValue() - 1.5 * thetaWD.DecibelValue() - 0.5 * gammaWD.DecibelValue();
double positiveWeightedSum = 1.0 * low_betaWD.DecibelValue() + 1.0 * high_betaWD.DecibelValue() + 0.5 * alphaWD.DecibelValue() + 0.5 * thetaWD.DecibelValue() + 0.5 * gammaWD.DecibelValue();
double simpleSum = waveValues.Sum();
//// Scaling-used values
double span = waveValues.Max() - waveValues.Min();
double average = waveValues.Average();
//// Different scaling showcases, intended to be more consistent across the magnitude space
// Span-inversely-proportional scaling
//scalingFactor = 1 / span;
// Magnitude-inversely-proportional scaling
//scalingFactor = 1 / average;
// Magnitude-complement-proportional scaling
//scalingFactor = 1 - average;
//// Packaged scalings
// Best Relaxation Tailoring
sum = simpleSum;
scalingFactor = 1 - average;
gravity = 1.2;
return(sum * scalingFactor - gravity); // Alternatively, gravity could be subtracted from sum directly
}
