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How to use LinearRegression method of Microsoft.Coyote.Benchmarking.MathHelpers class

Best Coyote code snippet using Microsoft.Coyote.Benchmarking.MathHelpers.LinearRegression

Storage.cs

Source:Storage.cs

...337                meanStdDevTime = MathHelpers.StandardDeviation(from i in data select i.Time);338                meanStdDevMemory = MathHelpers.StandardDeviation(from i in data select i.Memory);339                meanStdDevCpu = MathHelpers.StandardDeviation(from i in data select i.Cpu);340            }341            double timeSlope = MathHelpers.LinearRegression(MathHelpers.ToDataPoints(from i in data select i.Time)).Slope / meanTime;342            double memSlope = MathHelpers.LinearRegression(MathHelpers.ToDataPoints(from i in data select i.Memory)).Slope / meanMemory;343            double cpuSlope = MathHelpers.LinearRegression(MathHelpers.ToDataPoints(from i in data select i.Cpu)).Slope / meanCpu;344            // more than 10% slope we have a problem!345            if (timeSlope > 0.1)346            {347                this.Comments = "Slow down?";348            }349            else if (memSlope > 0.1)350            {351                this.Comments = "Memory leak?";352            }353            else if (cpuSlope > 0.1)354            {355                this.Comments = "Thread leak?";356            }357            this.TimeMean = meanTime;...

MathHelpers.cs

Source:MathHelpers.cs

...174        /// Compute the trend line through the given points, and return the line in the form:175        /// y = a + b.x.176        /// </summary>177        /// <param name="pts">The data to analyze.</param>178        public static Line LinearRegression(IEnumerable<DataPoint> pts)179        {180            double xMean = Mean(from p in pts select p.X);181            double yMean = Mean(from p in pts select p.Y);182            double xVariance = Variance(from p in pts select p.X);183            double yVariance = Variance(from p in pts select p.Y);184            double covariance = Covariance(pts);185            double a = 0;186            double b = 0;187            if (xVariance is 0)188            {189                a = yMean;190                b = 1;191            }192            else...

LinearRegression

Using AI Code Generation

1using Microsoft.Coyote.Benchmarking;2using System;3using System.Collections.Generic;4using System.Linq;5using System.Text;6using System.Threading.Tasks;7{8    {9        static void Main(string[] args)10        {11            double[] x = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };12            double[] y = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };13            double[] coefficients = MathHelpers.LinearRegression(x, y);14            Console.WriteLine("Slope = {0}", coefficients[0]);15            Console.WriteLine("Intercept = {0}", coefficients[1]);16            Console.ReadKey();17        }18    }19}20using Microsoft.Coyote.Benchmarking;21using System;22using System.Collections.Generic;23using System.Linq;24using System.Text;25using System.Threading.Tasks;26{27    {28        static void Main(string[] args)29        {30            double[] x = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };31            double[] y = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };32            double correlation = MathHelpers.PearsonCorrelation(x, y);33            Console.WriteLine("Correlation = {0}", correlation);34            Console.ReadKey();35        }36    }37}38using Microsoft.Coyote.Benchmarking;39using System;40using System.Collections.Generic;41using System.Linq;42using System.Text;43using System.Threading.Tasks;44{45    {46        static void Main(string[] args)47        {48            double[] x = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };49            double[] y = { 1, 2, 3, 4, 5,

LinearRegression

Using AI Code Generation

1using Microsoft.Coyote.Benchmarking;2using System;3{4    {5        static void Main(string[] args)6        {7            double[] x = { 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 };8            double[] y = { 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 };9            var (a, b) = MathHelpers.LinearRegression(x, y);10            Console.WriteLine($"y = {a} + {b} * x");11        }12    }13}

LinearRegression

Using AI Code Generation

1using Microsoft.Coyote.Benchmarking;2{3    public static void Main()4    {5        double[] x = { 1, 2, 3, 4, 5 };6        double[] y = { 1, 2, 3, 4, 5 };7        double[] result = MathHelpers.LinearRegression(x, y);8    }9}10using Microsoft.Coyote.Benchmarking;11{12    public static void Main()13    {14        double[] x = { 1, 2, 3, 4, 5 };15        double[] y = { 1, 2, 3, 4, 5 };16        double[] result = MathHelpers.LinearRegression(x, y);17    }18}19using Microsoft.Coyote.Benchmarking;20{21    public static void Main()22    {23        double[] x = { 1, 2, 3, 4, 5 };24        double[] y = { 1, 2, 3, 4, 5 };25        double[] result = MathHelpers.LinearRegression(x, y);26    }27}28using Microsoft.Coyote.Benchmarking;29{30    public static void Main()31    {32        double[] x = { 1, 2, 3, 4, 5 };33        double[] y = { 1, 2, 3, 4, 5 };34        double[] result = MathHelpers.LinearRegression(x, y);35    }36}

LinearRegression

Using AI Code Generation

1using Microsoft.Coyote.Benchmarking;2using System;3using System.Collections.Generic;4using System.Linq;5using System.Text;6using System.Threading.Tasks;7{8    {9        static void Main(string[] args)10        {11            double[] x = new double[] { 1, 2, 3, 4, 5 };12            double[] y = new double[] { 2, 4, 6, 8, 10 };13            var result = MathHelpers.LinearRegression(x, y);14            Console.WriteLine("Slope: {0}, Intercept: {1}, R^2: {2}", result.Slope, result.Intercept, result.RSquared);15            Console.ReadLine();16        }17    }18}19using Microsoft.Coyote.Benchmarking;20using System;21using System.Collections.Generic;22using System.Linq;23using System.Text;24using System.Threading.Tasks;25{26    {27        static void Main(string[] args)28        {29            double[] x = new double[] { 1, 2, 3, 4, 5 };30            double[] y = new double[] { 2, 4, 6, 8, 10 };31            var result = MathHelpers.LinearRegression(x, y);32            Console.WriteLine("Slope: {0}, Intercept: {1}, R^2: {2}", result.Slope, result.Intercept, result.RSquared);33            Console.ReadLine();34        }35    }36}37using Microsoft.Coyote.Benchmarking;38using System;39using System.Collections.Generic;40using System.Linq;41using System.Text;42using System.Threading.Tasks;43{44    {45        static void Main(string[] args)46        {47            double[] x = new double[] { 1, 2, 3, 4, 5 };48            double[] y = new double[] { 2, 4, 6, 8, 10 };49            var result = MathHelpers.LinearRegression(x, y);50            Console.WriteLine("Slope: {0}, Intercept: {1}, R^2:

LinearRegression

Using AI Code Generation

1var x = new double[] { 1, 2, 3, 4, 5 };2var y = new double[] { 1, 2, 3, 4, 5 };3var result = LinearRegression(x, y);4var x = new double[] { 1, 2, 3, 4, 5 };5var y = new double[] { 1, 2, 3, 4, 5 };6var result = LinearRegression(x, y);7var x = new double[] { 1, 2, 3, 4, 5 };8var y = new double[] { 1, 2, 3, 4, 5 };9var result = LinearRegression(x, y);10var x = new double[] { 1, 2, 3, 4, 5 };11var y = new double[] { 1, 2, 3, 4, 5 };12var result = LinearRegression(x, y);13var x = new double[] { 1, 2, 3, 4, 5 };14var y = new double[] { 1, 2, 3, 4, 5 };15var result = LinearRegression(x, y);16var x = new double[] { 1, 2, 3, 4, 5 };17var y = new double[] { 1, 2, 3, 4, 5 };18var result = LinearRegression(x, y);

LinearRegression

Using AI Code Generation

1using Microsoft.Coyote.Benchmarking;2{3    static void Main(string[] args)4    {5        var data = new double[10, 2];6        for (int i = 0; i < 10; i++)7        {8            data[i, 0] = i;9            data[i, 1] = i;10        }11        var result = MathHelpers.LinearRegression(data);12    }13}

LinearRegression

Using AI Code Generation

1using System;2using System.Collections.Generic;3using Microsoft.Coyote.Benchmarking;4{5    {6        static void Main(string[] args)7        {8            List<double> x = new List<double>();9            List<double> y = new List<double>();10            x.Add(1);11            y.Add(1);12            x.Add(2);13            y.Add(2);14            x.Add(3);15            y.Add(3);16            x.Add(4);17            y.Add(4);18            x.Add(5);19            y.Add(5);20            x.Add(6);21            y.Add(6);22            x.Add(7);23            y.Add(7);24            x.Add(8);25            y.Add(8);26            x.Add(9);27            y.Add(9);28            x.Add(10);29            y.Add(10);30            x.Add(11);31            y.Add(11);32            x.Add(12);33            y.Add(12);34            x.Add(13);35            y.Add(13);36            x.Add(14);37            y.Add(14);38            x.Add(15);39            y.Add(15);40            x.Add(16);41            y.Add(16);42            x.Add(17);43            y.Add(17);44            x.Add(18);45            y.Add(18);46            x.Add(19);47            y.Add(19);48            x.Add(20);49            y.Add(20);50            x.Add(21);51            y.Add(21);52            x.Add(22);53            y.Add(22);54            x.Add(23);55            y.Add(23);56            x.Add(24);57            y.Add(24);58            x.Add(25);59            y.Add(25);60            x.Add(26);61            y.Add(26);62            x.Add(27);63            y.Add(27);64            x.Add(28);65            y.Add(28);66            x.Add(29);67            y.Add(29);68            x.Add(30);69            y.Add(30);70            x.Add(31);71            y.Add(31);72            x.Add(32);73            y.Add(32);74            x.Add(33);75            y.Add(33);76            x.Add(34);77            y.Add(34);78            x.Add(35);79            y.Add(35);80            x.Add(36);

LinearRegression

Using AI Code Generation

1using System;2using System.Collections.Generic;3using System.IO;4using System.Linq;5using System.Text;6using System.Threading.Tasks;7using Microsoft.Coyote.Benchmarking;8{9    {10        static void Main(string[] args)11        {12            List<double> X = new List<double>();13            List<double> Y = new List<double>();14            using (StreamReader sr = new StreamReader("data.txt"))15            {16                string line;17                while ((line = sr.ReadLine()) != null)18                {19                    string[] values = line.Split(' ');20                    X.Add(Double.Parse(values[0]));21                    Y.Add(Double.Parse(values[1]));22                }23            }24            double[] results = MathHelpers.LinearRegression(X.ToArray(), Y.ToArray());25            Console.WriteLine("Slope: " + results[0]);26            Console.WriteLine("Intercept: " + results[1]);27            Console.WriteLine("R^2: " + results[2]);28            Console.WriteLine("Standard error: " + results[3]);29            Console.ReadKey();30        }31    }32}33using System;34using System.Collections.Generic;35using System.Text;36{37    {38        public static double[] LinearRegression(double[] x, double[] y)39        {40            int n = x.Length;41            double[] results = new double[4];

LinearRegression

Using AI Code Generation

1using System;2using Microsoft.Coyote.Benchmarking;3{4    {5        static void Main(string[] args)6        {7            double[] x = { 1.0, 2.0, 3.0, 4.0, 5.0 };8            double[] y = { 2.0, 4.0, 6.0, 8.0, 10.0 };9            double m, b;10            if (MathHelpers.LinearRegression(x, y, out m, out b))11            {12                Console.WriteLine("Slope: {0}", m);13                Console.WriteLine("Intercept: {0}", b);14            }15            {16                Console.WriteLine("Error calculating regression line.");17            }18        }19    }20}21LinearRegression(Double[], Double[], Double ByRef, Double ByRef)

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