public IAnalysisData <IAdjustedDataRow> GetAdjustedData(IAnalysisData <IAnalysisDataRow> rawAnalysisModel)
{
//Returns X, Y and Y^ - adjusted Y.
var fullAnalysis = (FullAnalysis <IAnalysisDataRow>)rawAnalysisModel;
var analysisInfo = controller.GetEntityById <AnalysisInformation>(fullAnalysis.DatabaseId);
var analysisData = analysisInfo.Data;
var xdata = rawAnalysisModel.Data.Select(d => d.X).ToArray();
var ydata = rawAnalysisModel.Data.Select(d => d.Y).ToArray();
var businessLogicObject = new LinearRegression.BusinessLogic.Regression(xdata.ToList(), ydata.ToList());
var adjustedYValues = new List <double>();
//Checking if we already have this data in the database.
if (controller.GetEntityById <AnalysisInformation>(fullAnalysis.DatabaseId) != null)
{
try
{
//If we have this data, try to get the adjusted Y values from the analysis calculations.
adjustedYValues = analysisData.AnalysisCalculations.AdjustedY.ToList();
}
catch (Exception)
{
//If we can't get the already calculated adjusted values, calculate them.
adjustedYValues = businessLogicObject.GetAdjustedYsValues();
}
}
else
{
//Else if we don't have the data calculate the adjusted Y values.
adjustedYValues = businessLogicObject.GetAdjustedYsValues();
}
int iterator = 0;
var adjustedDataRows = new ObservableCollection <IAdjustedDataRow>();
foreach (var row in rawAnalysisModel.Data)
{
adjustedDataRows.Add(new AdjustedDataRow(row.Index, row.X, row.Y, adjustedYValues[iterator]));
iterator++;
}
var adjustedAnalysis = new AdjustedAnalysis(rawAnalysisModel.XMeaning, rawAnalysisModel.YMeaning, adjustedDataRows);
return(adjustedAnalysis);
}
public IAnalysisCalculations GetAnalysisCalculations(IFullAnalysis <IAnalysisDataRow> analysis)
{
var xdata = analysis.Data.Select(d => d.X).ToArray();
var ydata = analysis.Data.Select(d => d.Y).ToArray();
var fullAnalysis = (FullAnalysis <IAnalysisDataRow>)analysis;
var analysisInfo = controller.GetEntityById <AnalysisInformation>(fullAnalysis.DatabaseId);
var analysisData = analysisInfo.Data;
//Checking if we already have this data in the database.
if (controller.GetEntityById <AnalysisInformation>(fullAnalysis.DatabaseId) != null)
{
//If we have this data, try to get the calculations from the analysis calculations.
try
{
var calculations = analysisData.AnalysisCalculations;
return(calculations.Entity);
}
catch (Exception)
{
//If we can't get the calculations, calculate them.
var businessLogicObject = new LinearRegression.BusinessLogic.Regression(xdata.ToList(), ydata.ToList());
var b0 = businessLogicObject.Parameter0;
var b1 = businessLogicObject.Parameter1;
var adjustedYs = businessLogicObject.GetAdjustedYsValues().ToArray();
double residualDispersion = businessLogicObject.CheckAdequacyOfModel().residualDispersion;
double explainedDispersion = businessLogicObject.CheckAdequacyOfModel().explainedDispersion;
double fEmpirical = businessLogicObject.CheckAdequacyOfModel().fEmpirical;
double fTheoretical = businessLogicObject.CheckAdequacyOfModel().fTheoretical;
double averageErrorB0 = businessLogicObject.GetAverageErrorOfParameters().averageErrorOfFirstParameter;
double averageErrorB1 = businessLogicObject.GetAverageErrorOfParameters().averageErrorOfSecondParameter;
double maximalErrorB0 = businessLogicObject.GetMaximumErrorOfParameters().maximumErrorOfFirstParameter;
double maximalErrorB1 = businessLogicObject.GetMaximumErrorOfParameters().maximumErrorOfSecondParameter;
AnalysisCalculations c = new AnalysisCalculations(analysisData, adjustedYs, b0, b1, residualDispersion, explainedDispersion,
fEmpirical, fTheoretical, averageErrorB0, averageErrorB1, maximalErrorB0, maximalErrorB1, controller);
c.Save();
return(c.Entity);
}
}
else
{
//Else if we don't have the data, make the calculatons.
var businessLogicObject = new LinearRegression.BusinessLogic.Regression(xdata.ToList(), ydata.ToList());
var b0 = businessLogicObject.Parameter0;
var b1 = businessLogicObject.Parameter1;
var adjustedYs = businessLogicObject.GetAdjustedYsValues().ToArray();
double residualDispersion = businessLogicObject.CheckAdequacyOfModel().residualDispersion;
double explainedDispersion = businessLogicObject.CheckAdequacyOfModel().explainedDispersion;
double fEmpirical = businessLogicObject.CheckAdequacyOfModel().fEmpirical;
double fTheoretical = businessLogicObject.CheckAdequacyOfModel().fTheoretical;
double averageErrorB0 = businessLogicObject.GetAverageErrorOfParameters().averageErrorOfFirstParameter;
double averageErrorB1 = businessLogicObject.GetAverageErrorOfParameters().averageErrorOfSecondParameter;
double maximalErrorB0 = businessLogicObject.GetMaximumErrorOfParameters().maximumErrorOfFirstParameter;
double maximalErrorB1 = businessLogicObject.GetMaximumErrorOfParameters().maximumErrorOfSecondParameter;
var calculation = new AnalysisCalculations(
analysisData, adjustedYs, b0, b1, residualDispersion, explainedDispersion,
fEmpirical, fTheoretical, averageErrorB0, averageErrorB1, maximalErrorB0, maximalErrorB1, controller
);
calculation.Save();
return(calculation.Entity);
}
}