public List<Operation> operations; //List of operations to be considered in the combinatorics part
#endregion Fields
#region Constructors
public Config()
{
exponents = new List<double>();
operations = new List<Operation>();
operations.Add(Operation.Multiplication); //Multiplication has always to be present
fitConfig = new FitConfig();
limitVals = new LimitValues();
}
//Method returning the FitConfig instance (i.e., including the basic rules determining when a fit is valid) associated with the given input conditions
private FitConfig getAssociatedFitConfig(Accuracy expectedAccuracy)
{
FitConfig curFitConfig = new FitConfig();
if (expectedAccuracy == Accuracy.High)
{
curFitConfig.averLimit = 0.05;
curFitConfig.minPercBelowLimit = 0.85;
curFitConfig.globalAver = 0.10;
curFitConfig.minNoCases = 50;
}
else if (expectedAccuracy == Accuracy.Medium)
{
curFitConfig.averLimit = 0.15;
curFitConfig.minPercBelowLimit = 0.8;
curFitConfig.globalAver = 0.25;
curFitConfig.minNoCases = 35;
}
else if (expectedAccuracy == Accuracy.Low)
{
curFitConfig.averLimit = 0.3;
curFitConfig.minPercBelowLimit = 0.7;
curFitConfig.globalAver = 0.35;
curFitConfig.minNoCases = 20;
}
curFitConfig.expectedAccuracy = expectedAccuracy;
return curFitConfig;
}
//Method starting all the calculations (i.e., calling the corresponding method in the Combinatorics class)
public Results startCalcs(List<Input> inputCols, int indepIndex, FitConfig curFitConfig)
{
Combinatorics curCombinatorics = new Combinatorics();
Results curResults = new Results();
curResults.allInputs = inputCols;
curResults.config = new Config();
curResults.config.operations.Add(Operation.Addition);
curResults.config.exponents = createListExponents();
curResults.config.maxNoCombs = 20;
curResults.config.fitConfig = curFitConfig;
//Due to the huge amount of (potential) information to be managed, the a-apriori logical structure "combinations -> calculations (regressions) -> analysis" is not present.
//Both calculations and analysis are performed for each single combination and only the "good-enough" ones are kept in memory
curResults = curCombinatorics.startCombinatorics(curResults, indepIndex);
curResults.combinations = curResults.combinations.OrderByDescending(x => x.assessment.globalRating).ThenBy(x => x.averError).ThenBy(x => x.independentVar.input.displayedName).ThenBy(x => x.dependentVars.items.Count).ToList();
return curResults;
}
//Method creating a ListView including all the required information about the currently selected accuracy level.
//This ListView will be added to the popup form created right before calling this function
private ListView createFitConfigLstVw(int curHeight, FitConfig curFitConfig)
{
ListView curLstVw = new ListView();
curLstVw.Width = 250;
curLstVw.Height = curHeight;
curLstVw.View = View.Details;
curLstVw.Columns.Add("Factor to define a valid trend").Width = 150;
curLstVw.Columns.Add("Value").TextAlign = HorizontalAlignment.Center;
ListViewItem curItem = new ListViewItem();
curItem.Text = "Target error/case (%)";
curItem.SubItems.Add((curFitConfig.averLimit * 100).ToString("N0", Common.curCulture));
curLstVw.Items.Add(curItem);
curItem = new ListViewItem();
curItem.Text = "Min. cases below target (%)";
curItem.SubItems.Add((curFitConfig.minPercBelowLimit * 100).ToString("N0", Common.curCulture));
curLstVw.Items.Add(curItem);
curItem = new ListViewItem();
curItem.Text = "Max. aver. global error (%)";
curItem.SubItems.Add((curFitConfig.globalAver * 100).ToString("N0", Common.curCulture));
curLstVw.Items.Add(curItem);
curItem = new ListViewItem();
curItem.Text = "Min. number of cases";
curItem.SubItems.Add(curFitConfig.minNoCases.ToString("N0", Common.curCulture));
curLstVw.Items.Add(curItem);
return curLstVw;
}