C# (CSharp) MathNet.Numerics.Distributions.Poisson.Samples Exemples

Exemple #1

Fichier : PerformanceTest.cs Projet : bartczernicki/Test-Blazor-WebAssembly-StatisticsAndML-DotNet5

        public double TakeSamples()
        {
            var dateTimeElapsed = 0.0;
            var dateTime        = DateTime.Now;

            if (this.DistributionName == "Binomial")
            {
                fullName = $"{DistributionName}-Samples:{SamplesNumber}-Trials:{TrialsNumber}";

                var binomaial        = new MathNet.Numerics.Distributions.Binomial(0.5, this.TrialsNumber);
                var generatedsamples = binomaial.Samples().Take(SamplesNumber).ToArray();
            }
            else if (this.DistributionName == "Geometric")
            {
                fullName = $"{DistributionName}-Samples:{SamplesNumber}";

                var geometric        = new MathNet.Numerics.Distributions.Geometric(0.5);
                var generatedsamples = geometric.Samples().Take(SamplesNumber).ToArray();
            }
            else if (this.DistributionName == "Poisson")
            {
                fullName = $"{DistributionName}-Samples:{SamplesNumber}";

                var poisson          = new MathNet.Numerics.Distributions.Poisson(0.5);
                var generatedsamples = poisson.Samples().Take(SamplesNumber).ToArray();
            }
            else if (this.DistributionName == "Normal")
            {
                fullName = $"{DistributionName}-Samples:{SamplesNumber}";

                var normal           = new MathNet.Numerics.Distributions.Normal(0.5, 2);
                var generatedsamples = normal.Samples().Take(SamplesNumber).ToArray();
            }

            dateTimeElapsed = (DateTime.Now - dateTime).TotalMilliseconds;
            return(dateTimeElapsed);
        }

Exemple #2

Fichier : PerformanceTest.cs Projet : bartczernicki/Test-Blazor-WebAssembly-StatisticsAndML-DotNet6

        public double TakeSamples()
        {
            var dateTimeElapsed = 0.0;
            var dateTime        = DateTime.Now;

            //IEnumerable<int> generatedSamplesEnumerable = Enumerable.Empty<int>();
            //IEnumerable<double> generatedSamplesDoubleEnumerable = Enumerable.Empty<double>();

            if (this.DistributionName == "Binomial")
            {
                fullName = $"{DistributionName}-Samples:{SamplesNumber}-Trials:{TrialsNumber}";

                var binomaial        = new MathNet.Numerics.Distributions.Binomial(0.5, this.TrialsNumber);
                var generatedsamples = binomaial.Samples().Take(SamplesNumber).ToArray();

                //generatedSamplesEnumerable = binomaial.Samples().Take(SamplesNumber);
                //foreach (var item in generatedSamplesEnumerable)
                //{
                //    var test = item;
                //}
            }
            else if (this.DistributionName == "Geometric")
            {
                fullName = $"{DistributionName}-Samples:{SamplesNumber}";

                var geometric        = new MathNet.Numerics.Distributions.Geometric(0.5);
                var generatedsamples = geometric.Samples().Take(SamplesNumber).ToArray();

                //generatedSamplesEnumerable = geometric.Samples().Take(SamplesNumber);
                //foreach (var item in generatedSamplesEnumerable)
                //{
                //    var test = item;
                //}
            }
            else if (this.DistributionName == "Poisson")
            {
                fullName = $"{DistributionName}-Samples:{SamplesNumber}";

                var poisson          = new MathNet.Numerics.Distributions.Poisson(0.5);
                var generatedsamples = poisson.Samples().Take(SamplesNumber).ToArray();

                //generatedSamplesEnumerable = poisson.Samples().Take(SamplesNumber);
                //foreach (var item in generatedSamplesEnumerable)
                //{
                //    var test = item;
                //}
            }
            else if (this.DistributionName == "Normal")
            {
                fullName = $"{DistributionName}-Samples:{SamplesNumber}";

                var normal           = new MathNet.Numerics.Distributions.Normal(0.5, 2);
                var generatedsamples = normal.Samples().Take(SamplesNumber).ToArray();

                //generatedSamplesDoubleEnumerable = normal.Samples().Take(SamplesNumber);
                //foreach(var item in generatedSamplesDoubleEnumerable)
                //{
                //    var test = item;
                //}
            }

            dateTimeElapsed = (DateTime.Now - dateTime).TotalMilliseconds;
            return(dateTimeElapsed);
        }