コード例 #1
0
 /// <summary>
 /// Non-linear least-squares fitting the points (x,y) to an arbitrary function y : x -> f(p0, p1, p2, x),
 /// returning its best fitting parameter p0, p1 and p2.
 /// </summary>
 public static Tuple <double, double, double> Curve(double[] x, double[] y, Func <double, double, double, double, double> f, double initialGuess0, double initialGuess1, double initialGuess2, double tolerance = 1e-8, int maxIterations = 1000)
 {
     return(FindMinimum.OfFunction((p0, p1, p2) => Distance.Euclidean(Generate.Map(x, t => f(p0, p1, p2, t)), y), initialGuess0, initialGuess1, initialGuess2, tolerance, maxIterations));
 }
コード例 #2
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 /// <summary>
 /// Least-Squares fitting the points (x,y) to a logarithm y : x -> a + b*ln(x),
 /// returning its best fitting parameters as (a, b) tuple.
 /// </summary>
 public static Tuple <double, double> Logarithm(double[] x, double[] y, DirectRegressionMethod method = DirectRegressionMethod.QR)
 {
     double[] lnx = Generate.Map(x, Math.Log);
     double[] p   = LinearCombination(lnx, y, method, t => 1.0, t => t);
     return(Tuple.Create(p[0], p[1]));
 }
コード例 #3
0
 /// <summary>
 /// Non-linear least-squares fitting the points (x,y) to an arbitrary function y : x -> f(p, x),
 /// returning its best fitting parameter p.
 /// </summary>
 public static double Curve(double[] x, double[] y, Func <double, double, double> f, double initialGuess, double tolerance = 1e-8, int maxIterations = 1000)
 {
     return(FindMinimum.OfScalarFunction(p => Distance.Euclidean(Generate.Map(x, t => f(p, t)), y), initialGuess, tolerance, maxIterations));
 }