private List <RilData> ExtrapolateFutureData(List <RilData> pastData)
{
const int nbSlices = 1000;
//get growth Coefficient
SpawnCoeff spawnCoeffs = CalculateSpawnCoefficient(pastData, 0.3f, nbSlices);
GrowthCoeff growthCoeffs = CalculateGrowthCoefficient(pastData, 0.3f, nbSlices);
return(PredictFutureData(pastData, spawnCoeffs, growthCoeffs));
}
private static List <RilData> PredictFutureData(List <RilData> pastData,
SpawnCoeff spawnCoeffs,
GrowthCoeff growthCoeffs)
{
if (spawnCoeffs.Values.Length != growthCoeffs.Values.Length)
{
throw new Exception("Coefficient arrays are not the same length");
}
List <RilData> newData = new List <RilData>(pastData);
Random rnd = new Random();
for (int i = 0; i < spawnCoeffs.Values.Length; i++)
{
int nbOfDataToCreate = (int)Math.Ceiling(spawnCoeffs.Values[i]);
float timespanBetweenTwoSpawn = spawnCoeffs.NormalizedTimespanOfSlice / nbOfDataToCreate;
float batSize = growthCoeffs.Values[i] / nbOfDataToCreate;
float lastT = 1f; // we start the time at the end of the normalized timeline
for (int dataToCreateIndex = 0; dataToCreateIndex < nbOfDataToCreate; dataToCreateIndex++)
{
float futureT = lastT + timespanBetweenTwoSpawn;
//noise function for Nb log
RilData pastDatatoGetPosFrom = pastData[rnd.Next(0, pastData.Count - 1)];
float[] futurePos = new[] { pastDatatoGetPosFrom.X, pastDatatoGetPosFrom.Y };
futurePos[0] += (rnd.Next(0, 50) - 25);
futurePos[1] += (rnd.Next(0, 50) - 25);
RilData rilData = new RilData("future", futurePos[0], futurePos[1], futureT)
{
//TODO : Add Noise here for organic results
NOMBRE_LOG = batSize
};
newData.Add(rilData);
}
}
//Reassign new T with max being extrapolation
float newMaxT = newData.Max(data => data.T);
foreach (RilData rilData in pastData)
{
rilData.SetT(rilData.T / newMaxT);
}
return(newData);
}
