using System;
using System.Collections.Generic;
using System.ComponentModel;
using System.Data;
using System.Drawing;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using System.Windows.Forms;
using Accord;
using Accord.Statistics;
using Accord.Statistics.Distributions.Univariate; 
using Accord.Statistics.Visualizations;
using Accord.Statistics.Analysis;
using ZedGraph;

namespace WindowsFormsApplication1
{
    public partial class Form1 : Form
    {
        public Form1()
        {
            InitializeComponent();
        }

        private void Form1_Load(object sender, EventArgs e)
        {

            Double[] Dataset1 = { 8.141, 8.516, 7.049, 7.555, 7.999, 9.638, 7.445, 8.322, 8.184, 9.138, 8.489, 7.138, 7.855, 8.354, 10.648, 9.036, 9.371, 7.243, 6.967, 7.570, 8.636, 9.734, 8.713, 8.898, 7.969, 7.223, 7.162, 9.536, 8.919, 8.304, 7.746, 8.911, 7.857, 9.024, 7.383, 8.928, 7.410, 9.033, 7.912, 7.751, 7.359, 7.920, 7.294, 7.583, 8.122, 7.586, 7.011, 8.460, 9.126, 7.247, 9.816, 8.411, 8.833, 9.028, 8.271, 7.698, 7.399, 9.823, 8.202, 8.413, 7.384, 7.721, 7.384, 7.660, 7.698, 8.396, 8.038, 7.295, 8.202, 9.214, 10.263, 7.990, 7.502, 8.502, 8.022, 7.824, 9.193, 9.490, 9.279, 8.961, 8.213, 7.448, 8.385, 9.276, 8.178, 7.102, 7.206, 7.594, 7.718, 7.770, 7.997, 7.866, 8.157, 9.319, 7.449, 8.559, 7.617, 8.074, 7.922, 9.178, 8.738, 7.679, 7.983, 8.307, 8.022, 9.407, 7.667, 8.844, 8.134, 8.383, 8.395, 8.004, 9.252, 8.130, 7.934, 8.140, 7.924, 8.893, 6.850, 8.238, 9.762, 7.544, 8.845, 7.595, 8.453, 7.892, 8.007, 8.352, 8.537, 9.402 };
            Double[] Dataset2 = { 0.999, 0.996, 1.066, 1.041, 1.052, 1.043, 1.052, 1.046, 1.032, 1.038, 1.052, 1.038, 1.040, 1.056, 1.043, 1.044, 1.058, 1.044, 1.053, 1.046, 1.045, 1.046, 1.048, 1.051, 1.056, 1.058, 1.065, 1.051, 1.049, 1.049, 1.043, 1.042, 1.049, 1.042, 1.033, 1.042, 1.028, 1.031, 1.036, 1.044, 1.037, 1.054, 1.046, 1.061, 1.048, 1.048, 1.028, 1.030, 1.049, 1.038, 1.042, 1.057, 1.028, 1.047, 1.044, 1.040, 1.038, 1.044, 1.046, 1.035, 1.040, 1.039, 1.046, 1.050, 1.033, 1.032, 1.040, 1.040, 1.032, 1.045, 1.054, 1.040, 1.045, 1.045, 1.043, 1.066, 1.057, 1.052, 1.060, 1.069, 1.046, 1.041, 1.048, 1.057, 1.059, 1.076, 1.051, 1.057, 1.067, 1.062, 1.025, 1.072, 1.061, 1.067, 1.062, 1.055, 1.065, 1.047, 1.046, 1.047, 1.045, 1.038, 1.056, 1.037, 1.042, 1.044, 1.047, 1.037, 1.047, 1.041, 1.042, 1.042, 1.042, 1.040, 1.060, 1.066, 1.067, 1.077, 1.059, 1.067 };
            Double[] Dataset= Dataset2;

            // with Accord.NET the results of the gamma fit are
            // Dataset1: k = 119.306665626699, θ = 0.0690958879514208  (rate=1/θ = 14.4726412764688)
            // Dataset2: k = 6952.29276909337, θ = 0.00015060019786871 (rate=1/θ = 6640.0975174798) 

            // with the same data a gamma distribution fit was performed online via "http://www.wessa.net/rwasp_fitdistrgamma.wasp"
            // Dataset1: shape= 115.405346712493, rate = 13.9994954351296 (θ= 1/shape= 0.07143114583191708605319342679921)
            // Dataset2: shape= 6930.15592532156 , rate = 6618.95473828367 (θ= 1/shape= 0.00015108125671506031378872360567992)

            //Conclusion
            //The fittet parameter are very similar 
            // Dataset 1: k, θ = 3% difference
            // Dataset 2: k, θ = 0.3% difference

        var da = new DistributionAnalysis();
            da.Learn(Dataset);
        var result = da.GoodnessOfFit[0].Distribution.ToString();

        var hist = new Histogram();  
            hist.Compute(Dataset);

        var DistGamma1 = new GammaDistribution();
            DistGamma1.Fit(Dataset);

        var ppl = new PointPairList();

            double x = hist.Range.Min;
            double stepx = (hist.Range.Max - hist.Range.Min) / 100;
            double  y;

            for (int i = 0; i < 100; i++)
            {
                y = DistGamma1.ProbabilityDensityFunction(x);
                x = x + stepx;
                ppl.Add(x, y);
            }

        }
    }
}