/// <summary>
/// Gets the data of a variable from an episode using the parameters of the target track
/// </summary>
/// <param name="episode">The episode</param>
/// <param name="trackParameters">The track parameters</param>
/// <param name="variableIndex">Index of the variable</param>
/// <returns>A Series objetct with the requested data or null if something fails</returns>
public static Series GetVariableData(Log.Episode episode, Report trackParameters, int variableIndex)
{
if (episode.steps[episode.steps.Count - 1].episodeSimTime < trackParameters.MinEpisodeLength)
{
return(null);
}
Series data = new Series();
foreach (Log.Step step in episode.steps)
{
if (step.episodeSimTime >= trackParameters.TimeOffset)
{
data.AddValue(step.episodeSimTime
, ProcessFunc.Get(trackParameters.ProcessFunc, step.data[variableIndex]));
}
}
if (data.Values.Count == 0)
{
return(null);
}
data.CalculateStats(trackParameters);
if (trackParameters.Resample)
{
data.Resample(trackParameters.NumSamples);
}
return(data);
}
/// <summary>
/// Gets the average value of a variable in an episode using the track parameters
/// </summary>
/// <param name="episode">The episode</param>
/// <param name="variableIndex">Index of the variable</param>
/// <param name="trackParameters">The track parameters</param>
/// <returns>The averaged value</returns>
public static double GetEpisodeAverage(Log.Episode episode, int variableIndex, Report trackParameters)
{
double avg = 0.0;
int count = 0;
if (episode.steps.Count == 0)
{
return(0.0);
}
foreach (Log.Step step in episode.steps)
{
if (step.episodeSimTime >= trackParameters.TimeOffset)
{
avg += ProcessFunc.Get(trackParameters.ProcessFunc, step.data[variableIndex]);
count++;
}
}
return(avg / count);
}
public void CalculateStats(Report trackParameters)
{
//calculate avg, min and max
double sum = 0.0;
Stats.min = double.MaxValue;
Stats.max = double.MinValue;
//curve "beauty"
double prevY = Values[0].Y;
double prevX = Values[0].X;
double ascBeauty = 0.0;
double dscBeauty = 0.0;
double sumSlopes = 0.0;
double slope;
foreach (XYValue val in Values)
{
if (val.Y > Stats.max)
{
Stats.max = val.Y;
}
if (val.Y < Stats.min)
{
Stats.min = val.Y;
}
if (val.X - prevX != 0.0)
{
slope = (ProcessFunc.Get(trackParameters.ProcessFunc, val.Y)
- prevY) / (val.X - prevX);
if (slope > 0.0)
{
ascBeauty += slope;
dscBeauty -= slope * 10.0;
}
else if (slope < 0.0)
{
ascBeauty += slope * 10.0;
dscBeauty -= slope;
}
sumSlopes += slope;
}
prevY = val.Y;
prevX = val.X;
sum += ProcessFunc.Get(trackParameters.ProcessFunc, val.Y);
}
double avgSlope = sumSlopes / Values.Count;
Stats.ascBeauty = ascBeauty / Values.Count;
Stats.dscBeauty = dscBeauty / Values.Count;
Stats.avg = sum / Values.Count;
//calculate std. deviation
double diff;
sum = 0.0;
foreach (XYValue val in Values)
{
diff = val.Y - Stats.avg;
sum += diff * diff;
}
Stats.stdDev = Math.Sqrt(sum / Values.Count);
}
