public TemporalSummary CalcSMapMinMaxMean(SMapSensorReading reading)
{
TemporalSummary temporalSummary = new TemporalSummary
{
MinValue = double.MaxValue,
MaxValue = double.MinValue,
MeanValue = 0
};
if (reading.Readings.Count > 1)
{
DateTime fromTime = dateConverter.ConvertDate((long)reading.Readings[0][0]);
DateTime toTime = dateConverter.ConvertDate((long)reading.Readings[reading.Readings.Count - 1][0]);
TimeSpan timeSpan = toTime - fromTime;
for (int i = 0; i < reading.Readings.Count - 1; i++)
{
List<double> readings = new List<double>();
readings.AddRange(reading.Readings[i]);
double readingsValue = readings[1];
if (temporalSummary.MinValue > readingsValue)
{
temporalSummary.MinValue = readingsValue;
}
if (temporalSummary.MaxValue < readingsValue)
{
temporalSummary.MaxValue = readingsValue;
}
DateTime time = dateConverter.ConvertDate((long)readings[0]);
TimeSpan? timeDif = dateConverter.ConvertDate((long)reading.Readings[i + 1][0]) - time;
temporalSummary.MeanValue += readingsValue * (timeDif.Value.TotalSeconds / timeSpan.TotalSeconds);
}
}
else if (reading.Readings.Count == 1)
{
double readingsValue = reading.Readings[0][0];
temporalSummary.MinValue = readingsValue;
temporalSummary.MaxValue = readingsValue;
temporalSummary.MeanValue = readingsValue;
}
else
{
temporalSummary.MaxValue = 0;
temporalSummary.MinValue = 0;
}
return temporalSummary;
}
private void CalcSMapMinMaxMeanCase(SMapSensorReading reading, DateTime timeFrom, DateTime timeTo,
TemporalSummary temporalSummary)
{
TimeSpan timeSpan = timeTo - timeFrom;
double state = reading.Readings[0][1];
DateTime time = dateConverter.ConvertDate((long)reading.Readings[0][0]);
temporalSummary.MaxValue = 1;
temporalSummary.MinValue = 0;
TimeSpan timeFromStart = time - timeFrom;
TimeSpan timeToEnd = timeTo - time;
if (state.Equals(0.0))
{
temporalSummary.MeanValue = 1 * (timeFromStart.TotalSeconds / timeSpan.TotalSeconds);
}
temporalSummary.MeanValue += state * (timeToEnd.TotalSeconds / timeSpan.TotalSeconds);
}
public TemporalSummary CalcSMapMinMaxMean(SMapSensorReading reading, DateTime timeFrom, DateTime timeTo)
{
TemporalSummary temporalSummary = new TemporalSummary
{
MinValue = double.MaxValue,
MaxValue = double.MinValue,
MeanValue = 0
};
if (reading.Readings.Count > 1)
{
temporalSummary.MaxValue = 1;
temporalSummary.MinValue = 0;
TimeSpan timeSpan = timeTo - timeFrom;
for (int i = 0; i < reading.Readings.Count - 1; i++)
{
DateTime timeCurrent = dateConverter.ConvertDate((long)reading.Readings[i][0]);
double state = reading.Readings[i][1];
if (i + 1 > reading.Readings.Count)
{
TimeSpan timeBeetween = timeTo - timeCurrent;
temporalSummary.MeanValue += state * (timeBeetween.TotalSeconds / timeSpan.TotalSeconds);
}
else if (i != 0)
{
DateTime timeNext = dateConverter.ConvertDate((long)reading.Readings[i + 1][0]);
TimeSpan timeBeetween = timeNext - timeCurrent;
temporalSummary.MeanValue += state * (timeBeetween.TotalSeconds / timeSpan.TotalSeconds);
}
else //i = 0
{
DateTime timeNext = dateConverter.ConvertDate((long)reading.Readings[i + 1][0]);
//if state = 0, then all values before was 1
if (state.Equals(0.0))
{
TimeSpan timeFromStart = timeCurrent - timeFrom;
temporalSummary.MeanValue += 1 * (timeFromStart.TotalSeconds / timeSpan.TotalSeconds);
}
else
{
TimeSpan timeBeetween = timeNext - timeCurrent;
temporalSummary.MeanValue += state * (timeBeetween.TotalSeconds / timeSpan.TotalSeconds);
}
}
}
}
else if (reading.Readings.Count == 1)
{
CalcSMapMinMaxMeanCase(reading, timeFrom, timeTo, temporalSummary);
}
else
{
temporalSummary.MaxValue = 0;
temporalSummary.MinValue = 0;
}
return temporalSummary;
}
