// Incorporates a new simulation result into the simulation data set and calculate a new semi deployment multiplier. If the data set has a poor correlation, then it might just leave the mutiplier. If the correlation becomes positive then it will clear the dataset and start again.
public void AddResult(ReentrySimulation.Result newResult)
{
// if this result is the same as the old result, then it is not new!
if (newResult.multiplierHasError)
{
if (lastErrorResult != null)
{
if (newResult.id == lastErrorResult.id) { return; }
}
lastErrorResult = newResult;
}
else
{
if (lastResult != null)
{
if (newResult.id == lastResult.id) { return; }
}
lastResult = newResult;
}
// What was the overshoot for this new result?
double overshoot = newResult.GetOvershoot(this.autoPilot.core.target.targetLatitude, this.autoPilot.core.target.targetLongitude);
//Debug.Log("overshoot: " + overshoot.ToString("F2") + " multiplier: " + newResult.parachuteMultiplier.ToString("F4") + " hasError:" + newResult.multiplierHasError);
// Add the new result to the linear regression
regression.Add(overshoot, newResult.parachuteMultiplier);
// What is the correlation coefficent of the data. If it is weak a correlation then we will dismiss the dataset and use it to change the current multiplier
correlation = regression.CorrelationCoefficent;
if (correlation > -0.2) // TODO this is the best value to test for non-correlation?
{
// If the correlation is less that 0 then we will give up controlling the parachutes and throw away the dataset. Also check that we have got several bits of data, just in case we get two datapoints that are badly correlated.
if (correlation > 0 && this.regression.dataSetSize > 5)
{
ClearData();
// Debug.Log("Giving up control of the parachutes as the data does not correlate: " + correlation);
}
else
{
// Debug.Log("Ignoring the simulation dataset because the correlation is not significant enough: " + correlation);
}
}
else
{
// How much data is there? If just one datapoint then we need to slightly vary the multplier to avoid doing exactly the same multiplier again and getting a divide by zero!. If there is just two then we will not update the multiplier as we can't conclude much from two points of data!
int dataSetSize = regression.dataSetSize;
if (dataSetSize == 1)
{
this.currentMultiplier *= 0.99999;
}
else if (dataSetSize == 2)
{
// Doing nothing
}
else
{
// Use the linear regression to give us a new prediciton for when to open the parachutes
try
{
this.currentMultiplier = regression.yIntercept;
}
catch (Exception)
{
// If there is not enough data then we expect an exception. However we need to vary the multiplier everso slightly so that we get different data in order to start generating data. This should never happen as we have already checked the size of the dataset.
this.currentMultiplier *= 0.99999;
}
}
// Impose sensible limits on the multiplier
if (this.currentMultiplier < 1 || double.IsNaN(currentMultiplier)) { this.currentMultiplier = 1; }
if (this.currentMultiplier > this.maxMultiplier) { this.currentMultiplier = this.maxMultiplier; }
}
return;
}
