From 3999c5ebc2c1faa70c996f5eb1742cf047e70e63 Mon Sep 17 00:00:00 2001 From: tibel Date: Thu, 10 Oct 2013 20:24:11 +0200 Subject: [PATCH] Fit: use generic classes and optimize Polynomial() matrix creation --- src/Numerics/Fit.cs | 16 +++++++++------- 1 file changed, 9 insertions(+), 7 deletions(-) diff --git a/src/Numerics/Fit.cs b/src/Numerics/Fit.cs index f68006b4..92633274 100644 --- a/src/Numerics/Fit.cs +++ b/src/Numerics/Fit.cs @@ -30,7 +30,7 @@ using System; using System.Linq; -using MathNet.Numerics.LinearAlgebra.Double; +using MathNet.Numerics.LinearAlgebra; using MathNet.Numerics.LinearRegression; namespace MathNet.Numerics @@ -67,8 +67,8 @@ namespace MathNet.Numerics /// public static double[] Polynomial(double[] x, double[] y, int order) { - var design = DenseMatrix.OfColumns(x.Length, order + 1, Enumerable.Range(0, order + 1).Select(j => DenseVector.Create(x.Length, i => Math.Pow(x[i], j)))); - return MultipleRegression.QR(design, new DenseVector(y)).ToArray(); + var design = Matrix.Build.DenseOfColumns(x.Length, order + 1, Enumerable.Range(0, order + 1).Select(j => x.Select(xi => Math.Pow(xi, j)))); + return MultipleRegression.QR(design, Vector.Build.Dense(y)).ToArray(); } /// @@ -87,8 +87,8 @@ namespace MathNet.Numerics /// public static double[] LinearCombination(double[] x, double[] y, params Func[] functions) { - var design = DenseMatrix.OfColumns(x.Length, functions.Length, functions.Select(f => DenseVector.Create(x.Length, i => f(x[i])))); - return MultipleRegression.QR(design, new DenseVector(y)).ToArray(); + var design = Matrix.Build.DenseOfColumns(x.Length, functions.Length, functions.Select(f => x.Select(xi => f(xi)))); + return MultipleRegression.QR(design, Vector.Build.Dense(y)).ToArray(); } /// @@ -107,7 +107,8 @@ namespace MathNet.Numerics /// public static double[] LinearMultiDim(double[][] x, double[] y, params Func[] functions) { - return MultipleRegression.QR(x.Select(xi => functions.Select(f => f(xi)).ToArray()).ToArray(), y); + var design = Matrix.Build.DenseOfRows(x.Select(xi => functions.Select(f => f(xi)))); + return MultipleRegression.QR(design, Vector.Build.Dense(y)).ToArray(); } /// @@ -126,7 +127,8 @@ namespace MathNet.Numerics /// public static double[] LinearGeneric(T[] x, double[] y, params Func[] functions) { - return MultipleRegression.QR(x.Select(xi => functions.Select(f => f(xi)).ToArray()).ToArray(), y); + var design = Matrix.Build.DenseOfRows(x.Select(xi => functions.Select(f => f(xi)))); + return MultipleRegression.QR(design, Vector.Build.Dense(y)).ToArray(); } ///