• 🧩Calculator.cs2.85 KB Download
• 🧩ChartHelper.cs0 KB Download

Calculator.cs

namespace Duesk.Utils;

public static class Calculator
{
    public static int[] CalculateSums(int[] items)
    {
        var sums = new int[7];
        
        sums[1] = 0;
        for (int i = 0; i < 10; i++) sums[1] += items[i];
        
        sums[2] = 0;
        for (int i = 10; i < 20; i++) sums[2] += items[i];
        
        sums[3] = 0;
        for (int i = 20; i < 28; i++) sums[3] += items[i];
        sums[3] += items[8] + items[9];
        
        sums[4] = 0;
        for (int i = 28; i < 36; i++) sums[4] += items[i];
        
        sums[5] = items[0] + items[1] + items[5] + items[6] + items[7] + items[8] + items[9] +
                   items[11] + items[12] + items[13] + items[14];
        
        sums[6] = items[2] + items[3] + items[4] + items[8] + items[9] + items[10] + items[16] + items[17];
        
        return sums;
    }
    
    public static int[] CalculateProfileValues(int[] sums, double[,] norm)
    {
        var values = new int[6];
        
        for (int k = 1; k <= 6; k++)
        {
            values[k - 1] = 4;
            for (int p = 0; p < 5; p++)
            {
                if (sums[k] < norm[k - 1, p])
                {
                    values[k - 1] = p;
                    break;
                }
            }
        }
        
        return values;
    }
    
    public static double CalculateCorrelation(int[] seValues, int[] feValues)
    {
        double[] se = new double[6];
        double[] fe = new double[6];
        
        for (int i = 0; i < 6; i++)
        {
            se[i] = seValues[i] + 1;
            fe[i] = feValues[i] + 1;
        }
        
        double seMean = se.Average();
        double feMean = fe.Average();
        
        double numerator = 0;
        double seVar = 0;
        double feVar = 0;
        
        for (int i = 0; i < 6; i++)
        {
            double seDiff = se[i] - seMean;
            double feDiff = fe[i] - feMean;
            numerator += seDiff * feDiff;
            seVar += seDiff * seDiff;
            feVar += feDiff * feDiff;
        }
        
        if (seVar == 0 || feVar == 0) return 0;
        return numerator / Math.Sqrt(seVar * feVar);
    }
    
    public static double CalculateAgreement(int[] seItems, int[] feItems)
    {
        int matches = 0;
        for (int i = 0; i < 36; i++)
        {
            if (seItems[i] == feItems[i]) matches++;
        }
        return matches * 100.0 / 36;
    }
    
    public static string GetRating(int value)
    {
        return value switch
        {
            1 => "weit unterdurchschnittlich",
            2 => "unterdurchschnittlich",
            3 => "durchschnittlich",
            4 => "überdurchschnittlich",
            5 => "weit überdurchschnittlich",
            _ => "unbekannt"
        };
    }
}