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C# ContinuousUniform.DensityLn方法代码示例

本文整理汇总了C#中MathNet.Numerics.Distributions.ContinuousUniform.DensityLn方法的典型用法代码示例。如果您正苦于以下问题:C# ContinuousUniform.DensityLn方法的具体用法?C# ContinuousUniform.DensityLn怎么用?C# ContinuousUniform.DensityLn使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在MathNet.Numerics.Distributions.ContinuousUniform的用法示例。


在下文中一共展示了ContinuousUniform.DensityLn方法的3个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的C#代码示例。

示例1: Run

        /// <summary>
        /// Run example
        /// </summary>
        /// <a href="http://en.wikipedia.org/wiki/Uniform_distribution_%28continuous%29">ContinuousUniform distribution</a>
        public void Run()
        {
            // 1. Initialize the new instance of the ContinuousUniform distribution class with default parameters.
            var continuousUniform = new ContinuousUniform();
            Console.WriteLine(@"1. Initialize the new instance of the ContinuousUniform distribution class with parameters Lower = {0}, Upper = {1}", continuousUniform.Lower, continuousUniform.Upper);
            Console.WriteLine();

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

            // 4. Generate 100000 samples of the ContinuousUniform(0, 1) distribution and display histogram
            Console.WriteLine(@"4. Generate 100000 samples of the ContinuousUniform(0, 1) distribution and display histogram");
            var data = new double[100000];
            for (var i = 0; i < data.Length; i++)
            {
                data[i] = continuousUniform.Sample();
            }

            ConsoleHelper.DisplayHistogram(data);
            Console.WriteLine();

            // 5. Generate 100000 samples of the ContinuousUniform(2, 10) distribution and display histogram
            Console.WriteLine(@"5. Generate 100000 samples of the ContinuousUniform(2, 10) distribution and display histogram");
            continuousUniform.Upper = 10;
            continuousUniform.Lower = 2;
            for (var i = 0; i < data.Length; i++)
            {
                data[i] = continuousUniform.Sample();
            }

            ConsoleHelper.DisplayHistogram(data);
        }
开发者ID:Mistrall,项目名称:Solvation,代码行数:83,代码来源:ContinuousUniformDistribution.cs

示例2: ValidateDensityLn

 public void ValidateDensityLn(double lower, double upper)
 {
     var n = new ContinuousUniform(lower, upper);
     for (var i = 0; i < 11; i++)
     {
         var x = i - 5.0;
         if (x >= lower && x <= upper)
         {
             Assert.AreEqual(-Math.Log(upper - lower), n.DensityLn(x));
             Assert.AreEqual(-Math.Log(upper - lower), ContinuousUniform.PDFLn(lower, upper, x));
         }
         else
         {
             Assert.AreEqual(double.NegativeInfinity, n.DensityLn(x));
             Assert.AreEqual(double.NegativeInfinity, ContinuousUniform.PDFLn(lower, upper, x));
         }
     }
 }
开发者ID:rmundy,项目名称:mathnet-numerics,代码行数:18,代码来源:ContinuousUniformTests.cs

示例3: ValidateDensityLn

 public void ValidateDensityLn(double lower, double upper)
 {
     var n = new ContinuousUniform(lower, upper);
     for (int i = 0; i < 11; i++)
     {
         double x = i - 5.0;
         if (x >= lower && x <= upper)
         {
             AssertEx.AreEqual<double>(-Math.Log(upper - lower), n.DensityLn(x));
         }
         else
         {
             AssertEx.AreEqual<double>(double.NegativeInfinity, n.DensityLn(x));
         }
     }
 }
开发者ID:joeynelson,项目名称:mathnet-numerics,代码行数:16,代码来源:ContinuousUniformTests.cs


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