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using System;
using MathNet.Numerics.Distributions;

namespace Examples.ContinuousDistributionsExamples
{
    /// <summary>
    /// Triangular distribution example
    /// </summary>
    public class TriangularDistribution : IExample
    {
        /// <summary>
        /// Gets the name of this example
        /// </summary>
        /// <seealso cref="http://reference.wolfram.com/mathematica/ref/TriangularDistribution.html"/>
        public string Name
        {
            get
            {
                return "Triangular distribution";
            }
        }

        /// <summary>
        /// Gets the description of this example
        /// </summary>
        public string Description
        {
            get
            {
                return "Triangular distribution properties and samples generating examples";
            }
        }

        /// <summary>
        /// Run example
        /// </summary>
        /// <a href="https://en.wikipedia.org/wiki/Triangular_distribution">Triangular distribution</a>
        public void Run()
        {
            // 1. Initialize
            var triangular = new Triangular(0, 1, 0.3);
            Console.WriteLine(@"1. Initialize the new instance of the Triangular distribution class with parameters Lower = {0}, Upper = {1}, Mode = {2}", triangular.LowerBound, triangular.UpperBound, triangular.Mode);
            Console.WriteLine();

            // 2. Distributuion properties:
            Console.WriteLine(@"2. {0} distributuion properties:", triangular);

            // Cumulative distribution function
            Console.WriteLine(@"{0} - Сumulative distribution at location '0.3'", triangular.CumulativeDistribution(0.3).ToString(" #0.00000;-#0.00000"));

            // Probability density
            Console.WriteLine(@"{0} - Probability density at location '0.3'", triangular.Density(0.3).ToString(" #0.00000;-#0.00000"));

            // Log probability density
            Console.WriteLine(@"{0} - Log probability density at location '0.3'", triangular.DensityLn(0.3).ToString(" #0.00000;-#0.00000"));

            // Entropy
            Console.WriteLine(@"{0} - Entropy", triangular.Entropy.ToString(" #0.00000;-#0.00000"));

            // Largest element in the domain
            Console.WriteLine(@"{0} - Largest element in the domain", triangular.Maximum.ToString(" #0.00000;-#0.00000"));

            // Smallest element in the domain
            Console.WriteLine(@"{0} - Smallest element in the domain", triangular.Minimum.ToString(" #0.00000;-#0.00000"));

            // Mean
            Console.WriteLine(@"{0} - Mean", triangular.Mean.ToString(" #0.00000;-#0.00000"));

            // Median
            Console.WriteLine(@"{0} - Median", triangular.Median.ToString(" #0.00000;-#0.00000"));

            // Mode
            Console.WriteLine(@"{0} - Mode", triangular.Mode.ToString(" #0.00000;-#0.00000"));

            // Variance
            Console.WriteLine(@"{0} - Variance", triangular.Variance.ToString(" #0.00000;-#0.00000"));

            // Standard deviation
            Console.WriteLine(@"{0} - Standard deviation", triangular.StdDev.ToString(" #0.00000;-#0.00000"));

            // Skewness
            Console.WriteLine(@"{0} - Skewness", triangular.Skewness.ToString(" #0.00000;-#0.00000"));
            Console.WriteLine();

            // 10 samples
            Console.WriteLine(@"3. Generate 10 samples of the Triangular distribution");
            for (var i = 0; i < 10; i++)
            {
                Console.Write(triangular.Sample().ToString("N05") + @" ");
            }

            Console.WriteLine();
            Console.WriteLine();

            // 10000 samples with starting parameters
            Console.WriteLine(@"4. Generate 100000 samples of the Triangular(0, 1, 0.3) distribution and display histogram");
            var data = new double[100000];
            Triangular.Samples(data, 0.0, 1.0, 0.3);
            ConsoleHelper.DisplayHistogram(data);
            Console.WriteLine();

            // 10000 with different parameters
            Console.WriteLine(@"4. Generate 100000 samples of the Triangular(2, 10, 8) distribution and display histogram");
            Triangular.Samples(data, 2.0, 10.0, 8.0);
            ConsoleHelper.DisplayHistogram(data);
        }
    }
}