private AccordResult CalculateLinearRegression(List <BalancePointPair> allBalancePointPairs, WthNormalParams normalParamsKey)
{
var allBalancePointGroups = allBalancePointPairs.GroupBy(s => new { s.CoolingBalancePoint, s.HeatingBalancePoint });
List <AccordResult> accordResults = new List <AccordResult>();
foreach (var group in allBalancePointGroups)
{
try
{
List <BalancePointPair> IdenticalBalancePointPairsFromAllReadings = group.ToList();
BalancePointPair _pointPair = IdenticalBalancePointPairsFromAllReadings.First();
int readingsCount = IdenticalBalancePointPairsFromAllReadings.Count;
double[] fullYData = new double[readingsCount];
double[] fullYDataDailyAvg = new double[readingsCount];
double[][] hcddMatrix = new double[readingsCount][];
double[][] hcddMatrixNonDaily = new double[readingsCount][];
foreach (BalancePointPair balancePointPair in IdenticalBalancePointPairsFromAllReadings)
{
fullYData[IdenticalBalancePointPairsFromAllReadings.IndexOf(balancePointPair)] = (balancePointPair.ActualUsage);
fullYDataDailyAvg[IdenticalBalancePointPairsFromAllReadings.IndexOf(balancePointPair)]
= (balancePointPair.ActualUsage / balancePointPair.DaysInReading);
hcddMatrix[IdenticalBalancePointPairsFromAllReadings.IndexOf(balancePointPair)] = new double[]
{
(balancePointPair.HeatingDegreeDays / balancePointPair.DaysInReading),
(balancePointPair.CoolingDegreeDays / balancePointPair.DaysInReading)
};
}
if (!(fullYData.Sum() > 0))
{
return(new AccordResult());
}
double[] avgHddsForEachReadingInYear = new double[readingsCount];
double[] avgCddsForEachReadingInYear = new double[readingsCount];
for (int i = 0; i < readingsCount; i++)
{
avgHddsForEachReadingInYear[i] = hcddMatrix[i][0];
avgCddsForEachReadingInYear[i] = hcddMatrix[i][1];
}
double[] modelParams = new double[3];
modelParams[0] = 0;
modelParams[1] = 0;
modelParams[2] = 0;
if (_pointPair.HeatingBalancePoint == 0 && _pointPair.CoolingBalancePoint == 0)
{
double[] onesVector = new double[readingsCount];
for (int i = 0; i < readingsCount; i++)
{
onesVector[i] = 1;
}
modelParams[0] = Fit.LineThroughOrigin(onesVector, fullYDataDailyAvg);
OrdinaryLeastSquares ols = new OrdinaryLeastSquares()
{
UseIntercept = false
};
double r2 = MathNet.Numerics.GoodnessOfFit.CoefficientOfDetermination(
onesVector.Select(x => x * modelParams[0]), fullYDataDailyAvg);
AccordResult accordResult = new AccordResult()
{
IsSimpleSingleRegression = true,
HeatingBP = _pointPair.HeatingBalancePoint,
CoolingBP = _pointPair.CoolingBalancePoint,
Intercept = modelParams[0],
R2Accord = r2,
//R2Accord = 0
};
accordResults.Add(accordResult);
}
else if (_pointPair.CoolingBalancePoint != 0 && _pointPair.HeatingBalancePoint != 0)
{
try
{
MultipleLinearRegressionAnalysis mlra = new MultipleLinearRegressionAnalysis(intercept: true);
mlra.Learn(hcddMatrix, fullYDataDailyAvg);
var regressionAccord = mlra.Regression;
double[] predictedAccord = regressionAccord.Transform(hcddMatrix);
double r2Accord = new RSquaredLoss(numberOfInputs: 2, expected: fullYDataDailyAvg)
{
Adjust = false
}.Loss(predictedAccord);
double r2Coeff = regressionAccord.CoefficientOfDetermination(hcddMatrix, fullYDataDailyAvg, adjust: false);
bool FTestFailed = !mlra.FTest.Significant;
AccordResult accordResult = new AccordResult()
{
IsMultipleLinearRegression = true,
HeatingBP = _pointPair.HeatingBalancePoint,
CoolingBP = _pointPair.CoolingBalancePoint,
Intercept = regressionAccord.Intercept,
B2 = regressionAccord.Weights[0],
B4 = regressionAccord.Weights[1],
R2Accord = r2Accord,
FTestFailed = FTestFailed
};
//int degreesOfFreedom = normalParamsKey.MoCt - 3;
double degreesOfFreedomAsDouble = mlra.Regression.GetDegreesOfFreedom(readingsCount);
int degreesOfFreedom = Convert.ToInt32(degreesOfFreedomAsDouble);
//if (degreesOfFreedom != 9)
//{
// Log.Warning($"Multivariable regression. DOF expected to be 9. is: {degreesOfFreedom}");
//}
//if (degreesOfFreedom != dof)
//{
// Console.WriteLine($"dof different. mlra.dof = {dof} expected = {degreesOfFreedom}");
//}
double s = Math.Sqrt(fullYDataDailyAvg.Subtract(predictedAccord).Pow(2).Sum() / degreesOfFreedom);
double ssxHdd = Math.Sqrt((avgHddsForEachReadingInYear.Subtract(avgHddsForEachReadingInYear.Mean())).Pow(2).Sum());
double ssxCdd = Math.Sqrt((avgCddsForEachReadingInYear.Subtract(avgCddsForEachReadingInYear.Mean())).Pow(2).Sum());
double seSubHdd = s / ssxHdd;
double seSubCdd = s / ssxCdd;
double tStatisticHdd = regressionAccord.Weights[0] / seSubHdd;
double tStatisticCdd = regressionAccord.Weights[1] / seSubCdd;
double tCriticalFivePercent = 2.262156;
double tCriticalTenPercent = 1.833113;
bool myTestHdd = Math.Abs(tStatisticHdd) >= tCriticalTenPercent;
bool myTestCdd = Math.Abs(tStatisticCdd) >= tCriticalTenPercent;
//if (myTestHdd != mlra.Coefficients[0].TTest.Significant && degreesOfFreedom != 9)
//{
// Console.WriteLine($"nope. mystat - {tStatisticHdd} accordstat - {mlra.Coefficients[0].TTest.Statistic} " +
// $"accordCritical - {mlra.Coefficients[0].TTest.CriticalValue}");
//}
//if (myTestCdd != mlra.Coefficients[1].TTest.Significant && degreesOfFreedom != 9)
//{
// Console.WriteLine($"nope. mystat - {tStatisticCdd} accordstat - {mlra.Coefficients[1].TTest.Statistic} " +
// $"accordCritical - {mlra.Coefficients[1].TTest.CriticalValue}");
//}
//if (mlra.Coefficients.All(x => x.TTest.Significant) &&
// mlra.Coefficients.All(x => x.Value > 0) &&
// mlra.Regression.Intercept > 0 &&
// r2Accord >= 0.7500)
//{
// accordResults.Add(accordResult);
//}
if (
myTestHdd &&
myTestCdd &&
mlra.Coefficients.All(x => x.Value > 0) &&
mlra.Regression.Intercept > 0
//&& accordResult.R2Accord >= 0.75
)
{
accordResults.Add(accordResult);
}
}
catch (Exception e)
{
Log.Debug($"AccID/UtilID/UnitID: {normalParamsKey.AccID}/{normalParamsKey.UtilID}/{normalParamsKey.UnitID} >> " +
$"MultipleLinearRegressionAnalysis Exception: {e.Message}");
}
}
else if (_pointPair.HeatingBalancePoint > 0)
{
OrdinaryLeastSquares ols = new OrdinaryLeastSquares()
{
UseIntercept = true
};
SimpleLinearRegression regressionAccord = ols.Learn(avgHddsForEachReadingInYear, fullYDataDailyAvg);
double[] predictedAccord = regressionAccord.Transform(avgHddsForEachReadingInYear);
double r2Accord = new RSquaredLoss(1, fullYDataDailyAvg).Loss(predictedAccord);
//int degreesOfFreedom = normalParamsKey.MoCt - 2;
double degreesOfFreedomAsDouble = regressionAccord.GetDegreesOfFreedom(readingsCount);
int degreesOfFreedom = Convert.ToInt32(degreesOfFreedomAsDouble);
//if (degreesOfFreedom != 10)
//{
// Log.Warning($"Single variable regression. DOF expected to be 10. is: {degreesOfFreedom}");
//}
double ssx = Math.Sqrt((avgHddsForEachReadingInYear.Subtract(avgHddsForEachReadingInYear.Mean())).Pow(2).Sum());
double s = Math.Sqrt(fullYDataDailyAvg.Subtract(predictedAccord).Pow(2).Sum() / degreesOfFreedom);
double error = regressionAccord.GetStandardError(avgHddsForEachReadingInYear, fullYDataDailyAvg);
double seSubB = s / ssx;
double hypothesizedValue = 0;
double tStatistic = regressionAccord.Slope / seSubB;
double tCriticalFivePercent = 2.228138;
double tCriticalTenPercent = 1.812461;
bool myTest = Math.Abs(tStatistic) >= tCriticalTenPercent;
//TTest tTest = new TTest(
// estimatedValue: regressionAccord.Slope, standardError: seSubB, degreesOfFreedom: degreesOfFreedom,
// hypothesizedValue: hypothesizedValue, alternate: OneSampleHypothesis.ValueIsDifferentFromHypothesis
// );
//if (myTest != tTest.Significant)
//{
// Console.WriteLine($"nope. mystat - {tStatistic} accordstat - {tTest.Statistic} accordCritical - {tTest.CriticalValue}");
//}
AccordResult accordResult = new AccordResult()
{
IsSimpleSingleRegression = true,
HeatingBP = _pointPair.HeatingBalancePoint,
Intercept = regressionAccord.Intercept,
B2 = regressionAccord.Slope,
R2Accord = r2Accord
};
//if (tTest.Significant && accordResult.B2 > 0 && r2Accord >= 0.7500)
//{
// accordResults.Add(accordResult);
//}
if (myTest &&
accordResult.B2 > 0 &&
accordResult.Intercept > 0
//&& r2Accord >= 0.7500
)
{
accordResults.Add(accordResult);
}
}
else if (_pointPair.CoolingBalancePoint > 0)
{
OrdinaryLeastSquares ols = new OrdinaryLeastSquares()
{
UseIntercept = true
};
SimpleLinearRegression regressionAccord = ols.Learn(avgCddsForEachReadingInYear, fullYDataDailyAvg);
double[] predictedAccord = regressionAccord.Transform(avgCddsForEachReadingInYear);
double r2Accord = new RSquaredLoss(1, fullYDataDailyAvg).Loss(predictedAccord);
//int degreesOfFreedom = normalParamsKey.MoCt - 2;
double degreesOfFreedomAsDouble = regressionAccord.GetDegreesOfFreedom(readingsCount);
int degreesOfFreedom = Convert.ToInt32(degreesOfFreedomAsDouble);
//if (degreesOfFreedom != 10)
//{
// Log.Warning($"Single variable regression. DOF expected to be 10. is: {degreesOfFreedom}");
//}
double ssx = Math.Sqrt(avgCddsForEachReadingInYear.Subtract(avgCddsForEachReadingInYear.Mean()).Pow(2).Sum());
double s = Math.Sqrt(fullYDataDailyAvg.Subtract(predictedAccord).Pow(2).Sum() / degreesOfFreedom);
double seSubB = s / ssx;
double hypothesizedValue = 0;
double tStatistic = regressionAccord.Slope / seSubB;
double tCriticalFivePercent = 2.22813885198627;
double tCriticalTenPercent = 1.812461;
bool myTest = Math.Abs(tStatistic) >= tCriticalTenPercent;
//TTest tTest = new TTest(
// estimatedValue: regressionAccord.Slope, standardError: seSubB, degreesOfFreedom: degreesOfFreedom,
// hypothesizedValue: hypothesizedValue, alternate: OneSampleHypothesis.ValueIsDifferentFromHypothesis
// );
//if (myTest != tTest.Significant)
//{
// Console.WriteLine($"nope. mystat - {tStatistic} accordstat - {tTest.Statistic} accordCritical - {tTest.CriticalValue}");
//}
AccordResult accordResult = new AccordResult()
{
IsSimpleSingleRegression = true,
CoolingBP = _pointPair.CoolingBalancePoint,
Intercept = regressionAccord.Intercept,
B4 = regressionAccord.Slope,
R2Accord = r2Accord
};
//if (tTest.Significant && accordResult.B4 > 0 && r2Accord >= 0.7500)
//{
// accordResults.Add(accordResult);
//}
if (
myTest &&
accordResult.B4 > 0
//&& r2Accord >= 0.7500
)
{
accordResults.Add(accordResult);
}
}
}
catch (Exception e)
{
Log.Debug($"AccID/UtilID/UnitID: {normalParamsKey.AccID}/{normalParamsKey.UtilID}/{normalParamsKey.UnitID} >> {e.Message} {e.StackTrace}");
}
}
AccordResult accordWinner = accordResults
.Where(s => s.Intercept >= 0)
.OrderByDescending(s => s.R2Accord).ToList().FirstOrDefault();
return(accordWinner);
}