ParticipationAndSummary Summarize(Participation participation)
{
ParticipationAndSummary result = new ParticipationAndSummary();
result.Participation = participation;
ParticipationsSummary summary = new ParticipationsSummary();
Correlator correlator = new Correlator();
double x = this.GetWeight(participation.Duration);
double weight = x / 2;
correlator.Add(0, 0, weight);
correlator.Add(x, x, weight);
summary.Trend = correlator;
Distribution logActiveTime = Distribution.MakeDistribution(Math.Log(participation.Duration.TotalSeconds), 0, 1);
summary.LogActiveTime = logActiveTime;
summary.Start = participation.StartDate;
summary.End = participation.EndDate;
summary.CumulativeIntensity = participation.Duration;
result.Summary = summary;
return(result);
}
public ParticipationAndSummary Combine(ParticipationAndSummary a, ParticipationAndSummary b)
{
if (a == null || a.Summary.CumulativeIntensity.TotalSeconds <= 0)
{
return(b);
}
if (b == null || b.Summary.CumulativeIntensity.TotalSeconds <= 0)
{
return(a);
}
ParticipationsSummary earlier = a.Summary;
ParticipationsSummary later = b.Summary;
if (earlier.Start.CompareTo(later.Start) > 0)
{
ParticipationsSummary temp = earlier;
earlier = later;
later = temp;
}
ParticipationsSummary summary = new ParticipationsSummary();
summary.CumulativeIntensity = earlier.CumulativeIntensity.Add(later.CumulativeIntensity);
summary.Start = earlier.Start;
summary.End = later.End;
summary.LogActiveTime = earlier.LogActiveTime.Plus(later.LogActiveTime);
// time between prev end and next start
TimeSpan idleDuration = later.Start.Subtract(earlier.End);
double idleX1 = this.GetWeight(earlier.End.Subtract(earlier.Start));
double idleX2 = this.GetWeight(later.Start.Subtract(earlier.Start));
double earlierSum = this.GetWeight(earlier.CumulativeIntensity);
Correlator laterShifted = later.Trend.CopyAndShiftRightAndUp(idleX2, earlierSum);
Correlator correlator = earlier.Trend.Plus(laterShifted);
if (idleDuration.TotalSeconds > 0)
{
double idleY = earlierSum;
double weight = this.GetWeight(idleDuration);
correlator.Add(idleX1, idleY, weight);
correlator.Add(idleX2, idleY, weight);
}
summary.Trend = correlator;
ParticipationAndSummary result = new ParticipationAndSummary();
result.Summary = summary;
if (summary.Trend.Correlation < 0)
{
System.Diagnostics.Debug.WriteLine("illegal correlation found: " + summary.Trend.Correlation + " for Activity " + this.Owner.Name);
}
// not bothering to assign a Participation because nothing will need it
return(result);
}
public ProgressionValue GetValueViaCorrelation(DateTime when, bool strictlyEarlier)
{
double resultNumber = 0.5;
DateTime startDate;
// The UI for logging data improved at this date. Any earlier data isn't used for computing correlation
DateTime changeDate = new DateTime(2015, 9, 20);
if (when.CompareTo(changeDate) > 0)
{
startDate = changeDate;
}
else
{
startDate = DateTime.MinValue;
}
ParticipationAndSummary info = this.searchHelper.CombineBetweenKeys(startDate, true, when, !strictlyEarlier);
if (info != null)
{
ParticipationsSummary summary = info.Summary;
Correlator correlator = summary.Trend;
double x = this.GetWeight(when.Subtract(summary.Start));
double predictedY = correlator.GetYForX(x);
double actualY = this.GetWeight(summary.CumulativeIntensity);
double deltaY = actualY - predictedY;
// Ideally we'd just return deltaY, but we have to transform it into a predefined range so the interpolator can use it
// Although it would be possible to divide by the total time elapsed, that would cause any deviation to decrease over time
// So instead we just warp the space from (-infinity, infinity) into (0, 1)
bool positive = true;
if (deltaY < 0)
{
deltaY *= -1;
positive = false;
}
// rescale such that a 32 hour deviation reaches halfway to the end of the space
resultNumber = deltaY / this.GetWeight(TimeSpan.FromHours(32));
// rescale such that nothing escapes the end of the space
resultNumber = 1.0 - 1.0 / (1.0 + Math.Log(1 + resultNumber));
if (positive)
{
resultNumber = (resultNumber + 1.0) / 2.0;
}
else
{
resultNumber = (1 - resultNumber) / 2.0;
}
}
return(new ProgressionValue(when, Distribution.MakeDistribution(resultNumber, 0, 0)));
}
public ParticipationsSummary SummarizeParticipationsBetween(DateTime startDate, DateTime endDate)
{
ParticipationAndSummary result = this.searchHelper.CombineBetweenKeys(startDate, true, endDate, false);
if (result == null)
{
ParticipationsSummary summary = new ParticipationsSummary();
summary.Start = startDate;
summary.End = endDate;
summary.CumulativeIntensity = new TimeSpan();
summary.LogActiveTime = Distribution.Zero;
summary.Trend = new Correlator();
return(summary);
}
return(result.Summary);
}
