public DataAdequacyPage(IFullAnalysis <IAdjustedDataRow> analysisData, IAnalysisCalculations calculations)
{
InitializeComponent();
this.analysisData = analysisData;
this.calculations = calculations;
GenerateStrings();
}
public IFullAnalysis <IAdjustedDataRow> GetFullAnalysisAdjustedData(IFullAnalysis <IAnalysisDataRow> fullRawAnalysisModel)
{
//Returns all things from the regression analysis + adjusted Ys
var adjustedData = GetAdjustedData(fullRawAnalysisModel);
var fullAnalysisCast = (FullAnalysis <IAnalysisDataRow>)fullRawAnalysisModel;
var fullAdjusted = new FullAnalysis <IAdjustedDataRow>(fullAnalysisCast.DatabaseId, fullRawAnalysisModel.Title, fullRawAnalysisModel.Description, fullRawAnalysisModel.XMeaning, fullRawAnalysisModel.YMeaning, adjustedData.Data);
return(fullAdjusted);
}
public long SaveEntity(IFullAnalysis <IAnalysisDataRow> analysisModel)
{
var analysisInformation = SaveAnalysisInformation(analysisModel);
analysisModel.DatabaseId = analysisInformation.Id;
SaveAnalysisData(analysisModel, analysisInformation);
return(analysisInformation.Id);
}
public ComputedAnalysis(IServiceProvider services, IFullAnalysis <IAnalysisDataRow> analysisModel)
{
InitializeComponent();
this.Services = services;
this.analysisLogicService = Services.GetService(typeof(IAnalysisLogicService)) as IAnalysisLogicService;
this.analysisModel = analysisModel;
//TODO: Find if the data had allready been computed and provide the computational data instead of computing it again. It is a good idea to make such constructors.
}
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);
}
}
