// <copyright file="Matrix.cs" company="Math.NET">
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// Math.NET Numerics, part of the Math.NET Project
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// http://numerics.mathdotnet.com
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// http://github.com/mathnet/mathnet-numerics
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//
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// Copyright (c) 2009-2015 Math.NET
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//
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// Permission is hereby granted, free of charge, to any person
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// obtaining a copy of this software and associated documentation
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// files (the "Software"), to deal in the Software without
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// restriction, including without limitation the rights to use,
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// copy, modify, merge, publish, distribute, sublicense, and/or sell
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// copies of the Software, and to permit persons to whom the
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// Software is furnished to do so, subject to the following
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// conditions:
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//
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// The above copyright notice and this permission notice shall be
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// included in all copies or substantial portions of the Software.
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//
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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// OTHER DEALINGS IN THE SOFTWARE.
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// </copyright>
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using System;
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using IStation.Numerics.LinearAlgebra.Double.Factorization;
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using IStation.Numerics.LinearAlgebra.Factorization;
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using IStation.Numerics.LinearAlgebra.Storage;
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namespace IStation.Numerics.LinearAlgebra.Double
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{
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/// <summary>
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/// <c>double</c> version of the <see cref="Matrix{T}"/> class.
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/// </summary>
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[Serializable]
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public abstract class Matrix : Matrix<double>
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{
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/// <summary>
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/// Initializes a new instance of the Matrix class.
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/// </summary>
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protected Matrix(MatrixStorage<double> storage)
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: base(storage)
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{
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}
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/// <summary>
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/// Set all values whose absolute value is smaller than the threshold to zero.
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/// </summary>
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public override void CoerceZero(double threshold)
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{
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MapInplace(x => Math.Abs(x) < threshold ? 0d : x, Zeros.AllowSkip);
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}
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/// <summary>
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/// Returns the conjugate transpose of this matrix.
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/// </summary>
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/// <returns>The conjugate transpose of this matrix.</returns>
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public sealed override Matrix<double> ConjugateTranspose()
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{
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return Transpose();
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}
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/// <summary>
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/// Puts the conjugate transpose of this matrix into the result matrix.
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/// </summary>
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public sealed override void ConjugateTranspose(Matrix<double> result)
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{
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Transpose(result);
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}
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/// <summary>
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/// Complex conjugates each element of this matrix and place the results into the result matrix.
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/// </summary>
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/// <param name="result">The result of the conjugation.</param>
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protected sealed override void DoConjugate(Matrix<double> result)
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{
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if (ReferenceEquals(this, result))
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{
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return;
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}
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CopyTo(result);
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}
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/// <summary>
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/// Negate each element of this matrix and place the results into the result matrix.
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/// </summary>
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/// <param name="result">The result of the negation.</param>
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protected override void DoNegate(Matrix<double> result)
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{
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Map(x => -x, result, Zeros.AllowSkip);
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}
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/// <summary>
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/// Add a scalar to each element of the matrix and stores the result in the result vector.
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/// </summary>
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/// <param name="scalar">The scalar to add.</param>
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/// <param name="result">The matrix to store the result of the addition.</param>
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protected override void DoAdd(double scalar, Matrix<double> result)
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{
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Map(x => x + scalar, result, Zeros.Include);
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}
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/// <summary>
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/// Adds another matrix to this matrix.
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/// </summary>
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/// <param name="other">The matrix to add to this matrix.</param>
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/// <param name="result">The matrix to store the result of the addition.</param>
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/// <exception cref="ArgumentNullException">If the other matrix is <see langword="null"/>.</exception>
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/// <exception cref="ArgumentOutOfRangeException">If the two matrices don't have the same dimensions.</exception>
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protected override void DoAdd(Matrix<double> other, Matrix<double> result)
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{
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Map2((x, y) => x + y, other, result, Zeros.AllowSkip);
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}
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/// <summary>
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/// Subtracts a scalar from each element of the vector and stores the result in the result vector.
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/// </summary>
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/// <param name="scalar">The scalar to subtract.</param>
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/// <param name="result">The matrix to store the result of the subtraction.</param>
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protected override void DoSubtract(double scalar, Matrix<double> result)
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{
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Map(x => x - scalar, result, Zeros.Include);
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}
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/// <summary>
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/// Subtracts another matrix from this matrix.
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/// </summary>
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/// <param name="other">The matrix to subtract to this matrix.</param>
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/// <param name="result">The matrix to store the result of subtraction.</param>
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/// <exception cref="ArgumentNullException">If the other matrix is <see langword="null"/>.</exception>
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/// <exception cref="ArgumentOutOfRangeException">If the two matrices don't have the same dimensions.</exception>
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protected override void DoSubtract(Matrix<double> other, Matrix<double> result)
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{
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Map2((x, y) => x - y, other, result, Zeros.AllowSkip);
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}
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/// <summary>
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/// Multiplies each element of the matrix by a scalar and places results into the result matrix.
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/// </summary>
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/// <param name="scalar">The scalar to multiply the matrix with.</param>
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/// <param name="result">The matrix to store the result of the multiplication.</param>
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protected override void DoMultiply(double scalar, Matrix<double> result)
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{
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Map(x => x*scalar, result, Zeros.AllowSkip);
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}
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/// <summary>
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/// Multiplies this matrix with a vector and places the results into the result vector.
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/// </summary>
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/// <param name="rightSide">The vector to multiply with.</param>
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/// <param name="result">The result of the multiplication.</param>
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protected override void DoMultiply(Vector<double> rightSide, Vector<double> result)
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{
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for (var i = 0; i < RowCount; i++)
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{
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var s = 0.0;
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for (var j = 0; j < ColumnCount; j++)
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{
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s += At(i, j)*rightSide[j];
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}
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result[i] = s;
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}
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}
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/// <summary>
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/// Divides each element of the matrix by a scalar and places results into the result matrix.
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/// </summary>
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/// <param name="divisor">The scalar to divide the matrix with.</param>
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/// <param name="result">The matrix to store the result of the division.</param>
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protected override void DoDivide(double divisor, Matrix<double> result)
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{
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Map(x => x/divisor, result, divisor == 0.0 ? Zeros.Include : Zeros.AllowSkip);
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}
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/// <summary>
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/// Divides a scalar by each element of the matrix and stores the result in the result matrix.
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/// </summary>
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/// <param name="dividend">The scalar to divide by each element of the matrix.</param>
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/// <param name="result">The matrix to store the result of the division.</param>
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protected override void DoDivideByThis(double dividend, Matrix<double> result)
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{
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Map(x => dividend/x, result, Zeros.Include);
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}
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/// <summary>
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/// Multiplies this matrix with another matrix and places the results into the result matrix.
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/// </summary>
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/// <param name="other">The matrix to multiply with.</param>
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/// <param name="result">The result of the multiplication.</param>
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protected override void DoMultiply(Matrix<double> other, Matrix<double> result)
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{
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for (var i = 0; i < RowCount; i++)
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{
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for (var j = 0; j < other.ColumnCount; j++)
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{
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var s = 0.0;
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for (var k = 0; k < ColumnCount; k++)
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{
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s += At(i, k)*other.At(k, j);
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}
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result.At(i, j, s);
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}
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}
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}
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/// <summary>
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/// Multiplies this matrix with transpose of another matrix and places the results into the result matrix.
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/// </summary>
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/// <param name="other">The matrix to multiply with.</param>
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/// <param name="result">The result of the multiplication.</param>
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protected override void DoTransposeAndMultiply(Matrix<double> other, Matrix<double> result)
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{
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for (var j = 0; j < other.RowCount; j++)
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{
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for (var i = 0; i < RowCount; i++)
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{
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var s = 0.0;
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for (var k = 0; k < ColumnCount; k++)
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{
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s += At(i, k)*other.At(j, k);
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}
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result.At(i, j, s);
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}
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}
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}
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/// <summary>
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/// Multiplies this matrix with the conjugate transpose of another matrix and places the results into the result matrix.
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/// </summary>
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/// <param name="other">The matrix to multiply with.</param>
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/// <param name="result">The result of the multiplication.</param>
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protected sealed override void DoConjugateTransposeAndMultiply(Matrix<double> other, Matrix<double> result)
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{
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DoTransposeAndMultiply(other, result);
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}
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/// <summary>
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/// Multiplies the transpose of this matrix with another matrix and places the results into the result matrix.
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/// </summary>
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/// <param name="other">The matrix to multiply with.</param>
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/// <param name="result">The result of the multiplication.</param>
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protected override void DoTransposeThisAndMultiply(Matrix<double> other, Matrix<double> result)
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{
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for (var j = 0; j < other.ColumnCount; j++)
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{
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for (var i = 0; i < ColumnCount; i++)
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{
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var s = 0.0;
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for (var k = 0; k < RowCount; k++)
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{
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s += At(k, i)*other.At(k, j);
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}
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result.At(i, j, s);
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}
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}
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}
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/// <summary>
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/// Multiplies the transpose of this matrix with another matrix and places the results into the result matrix.
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/// </summary>
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/// <param name="other">The matrix to multiply with.</param>
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/// <param name="result">The result of the multiplication.</param>
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protected sealed override void DoConjugateTransposeThisAndMultiply(Matrix<double> other, Matrix<double> result)
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{
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DoTransposeThisAndMultiply(other, result);
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}
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/// <summary>
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/// Multiplies the transpose of this matrix with a vector and places the results into the result vector.
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/// </summary>
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/// <param name="rightSide">The vector to multiply with.</param>
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/// <param name="result">The result of the multiplication.</param>
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protected override void DoTransposeThisAndMultiply(Vector<double> rightSide, Vector<double> result)
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{
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for (var j = 0; j < ColumnCount; j++)
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{
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var s = 0.0;
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for (var i = 0; i < RowCount; i++)
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{
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s += At(i, j)*rightSide[i];
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}
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result[j] = s;
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}
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}
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/// <summary>
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/// Multiplies the conjugate transpose of this matrix with a vector and places the results into the result vector.
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/// </summary>
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/// <param name="rightSide">The vector to multiply with.</param>
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/// <param name="result">The result of the multiplication.</param>
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protected sealed override void DoConjugateTransposeThisAndMultiply(Vector<double> rightSide, Vector<double> result)
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{
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DoTransposeThisAndMultiply(rightSide, result);
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}
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/// <summary>
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/// Computes the canonical modulus, where the result has the sign of the divisor,
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/// for the given divisor each element of the matrix.
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/// </summary>
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/// <param name="divisor">The scalar denominator to use.</param>
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/// <param name="result">Matrix to store the results in.</param>
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protected override void DoModulus(double divisor, Matrix<double> result)
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{
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Map(x => Euclid.Modulus(x, divisor), result, Zeros.Include);
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}
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/// <summary>
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/// Computes the canonical modulus, where the result has the sign of the divisor,
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/// for the given dividend for each element of the matrix.
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/// </summary>
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/// <param name="dividend">The scalar numerator to use.</param>
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/// <param name="result">A vector to store the results in.</param>
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protected override void DoModulusByThis(double dividend, Matrix<double> result)
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{
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Map(x => Euclid.Modulus(dividend, x), result, Zeros.Include);
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}
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/// <summary>
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/// Computes the remainder (% operator), where the result has the sign of the dividend,
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/// for the given divisor each element of the matrix.
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/// </summary>
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/// <param name="divisor">The scalar denominator to use.</param>
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/// <param name="result">Matrix to store the results in.</param>
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protected override void DoRemainder(double divisor, Matrix<double> result)
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{
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Map(x => Euclid.Remainder(x, divisor), result, Zeros.Include);
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}
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/// <summary>
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/// Computes the remainder (% operator), where the result has the sign of the dividend,
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/// for the given dividend for each element of the matrix.
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/// </summary>
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/// <param name="dividend">The scalar numerator to use.</param>
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/// <param name="result">A vector to store the results in.</param>
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protected override void DoRemainderByThis(double dividend, Matrix<double> result)
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{
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Map(x => Euclid.Remainder(dividend, x), result, Zeros.Include);
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}
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/// <summary>
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/// Pointwise multiplies this matrix with another matrix and stores the result into the result matrix.
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/// </summary>
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/// <param name="other">The matrix to pointwise multiply with this one.</param>
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/// <param name="result">The matrix to store the result of the pointwise multiplication.</param>
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protected override void DoPointwiseMultiply(Matrix<double> other, Matrix<double> result)
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{
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Map2((x, y) => x*y, other, result, Zeros.AllowSkip);
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}
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/// <summary>
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/// Pointwise divide this matrix by another matrix and stores the result into the result matrix.
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/// </summary>
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/// <param name="divisor">The matrix to pointwise divide this one by.</param>
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/// <param name="result">The matrix to store the result of the pointwise division.</param>
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protected override void DoPointwiseDivide(Matrix<double> divisor, Matrix<double> result)
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{
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Map2((x, y) => x/y, divisor, result, Zeros.Include);
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}
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/// <summary>
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/// Pointwise raise this matrix to an exponent and store the result into the result matrix.
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/// </summary>
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/// <param name="exponent">The exponent to raise this matrix values to.</param>
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/// <param name="result">The matrix to store the result of the pointwise power.</param>
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protected override void DoPointwisePower(double exponent, Matrix<double> result)
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{
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Map(x => Math.Pow(x, exponent), result, exponent > 0.0 ? Zeros.AllowSkip : Zeros.Include);
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}
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/// <summary>
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/// Pointwise raise this matrix to an exponent and store the result into the result matrix.
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/// </summary>
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/// <param name="exponent">The exponent to raise this matrix values to.</param>
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/// <param name="result">The vector to store the result of the pointwise power.</param>
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protected override void DoPointwisePower(Matrix<double> exponent, Matrix<double> result)
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{
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Map2(Math.Pow, result, Zeros.Include);
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}
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/// <summary>
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/// Pointwise canonical modulus, where the result has the sign of the divisor,
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/// of this matrix with another matrix and stores the result into the result matrix.
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/// </summary>
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/// <param name="divisor">The pointwise denominator matrix to use</param>
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/// <param name="result">The result of the modulus.</param>
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protected override void DoPointwiseModulus(Matrix<double> divisor, Matrix<double> result)
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{
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Map2(Euclid.Modulus, divisor, result, Zeros.Include);
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}
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/// <summary>
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/// Pointwise remainder (% operator), where the result has the sign of the dividend,
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/// of this matrix with another matrix and stores the result into the result matrix.
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/// </summary>
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/// <param name="divisor">The pointwise denominator matrix to use</param>
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/// <param name="result">The result of the modulus.</param>
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protected override void DoPointwiseRemainder(Matrix<double> divisor, Matrix<double> result)
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{
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Map2(Euclid.Remainder, divisor, result, Zeros.Include);
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}
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/// <summary>
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/// Pointwise applies the exponential function to each value and stores the result into the result matrix.
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/// </summary>
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/// <param name="result">The matrix to store the result.</param>
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protected override void DoPointwiseExp(Matrix<double> result)
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{
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Map(Math.Exp, result, Zeros.Include);
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}
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/// <summary>
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/// Pointwise applies the natural logarithm function to each value and stores the result into the result matrix.
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/// </summary>
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/// <param name="result">The matrix to store the result.</param>
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protected override void DoPointwiseLog(Matrix<double> result)
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{
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Map(Math.Log, result, Zeros.Include);
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}
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protected override void DoPointwiseAbs(Matrix<double> result)
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{
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Map(Math.Abs, result, Zeros.AllowSkip);
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}
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protected override void DoPointwiseAcos(Matrix<double> result)
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{
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Map(Math.Acos, result, Zeros.Include);
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}
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protected override void DoPointwiseAsin(Matrix<double> result)
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{
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Map(Math.Asin, result, Zeros.AllowSkip);
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}
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protected override void DoPointwiseAtan(Matrix<double> result)
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{
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Map(Math.Atan, result, Zeros.AllowSkip);
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}
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protected override void DoPointwiseAtan2(Matrix<double> other, Matrix<double> result)
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{
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Map2(Math.Atan2, other, result, Zeros.Include);
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}
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protected override void DoPointwiseCeiling(Matrix<double> result)
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{
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Map(Math.Ceiling, result, Zeros.AllowSkip);
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}
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protected override void DoPointwiseCos(Matrix<double> result)
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{
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Map(Math.Cos, result, Zeros.Include);
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}
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protected override void DoPointwiseCosh(Matrix<double> result)
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{
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Map(Math.Cosh, result, Zeros.Include);
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}
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protected override void DoPointwiseFloor(Matrix<double> result)
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{
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Map(Math.Floor, result, Zeros.AllowSkip);
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}
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protected override void DoPointwiseLog10(Matrix<double> result)
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{
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Map(Math.Log10, result, Zeros.Include);
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}
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protected override void DoPointwiseRound(Matrix<double> result)
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{
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Map(Math.Round, result, Zeros.AllowSkip);
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}
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protected override void DoPointwiseSign(Matrix<double> result)
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{
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Map(x => (double)Math.Sign(x), result, Zeros.AllowSkip);
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}
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protected override void DoPointwiseSin(Matrix<double> result)
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{
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Map(Math.Sin, result, Zeros.AllowSkip);
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}
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protected override void DoPointwiseSinh(Matrix<double> result)
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{
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Map(Math.Sinh, result, Zeros.AllowSkip);
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}
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protected override void DoPointwiseSqrt(Matrix<double> result)
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{
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Map(Math.Sqrt, result, Zeros.AllowSkip);
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}
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protected override void DoPointwiseTan(Matrix<double> result)
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{
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Map(Math.Tan, result, Zeros.AllowSkip);
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}
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protected override void DoPointwiseTanh(Matrix<double> result)
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{
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Map(Math.Tanh, result, Zeros.AllowSkip);
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}
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/// <summary>
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/// Computes the Moore-Penrose Pseudo-Inverse of this matrix.
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/// </summary>
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public override Matrix<double> PseudoInverse()
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{
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var svd = Svd(true);
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var w = svd.W;
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var s = svd.S;
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double tolerance = Math.Max(RowCount, ColumnCount) * svd.L2Norm * Precision.DoublePrecision;
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for (int i = 0; i < s.Count; i++)
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{
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s[i] = s[i] < tolerance ? 0 : 1/s[i];
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}
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w.SetDiagonal(s);
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return (svd.U * (w * svd.VT)).Transpose();
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}
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/// <summary>
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/// Computes the trace of this matrix.
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/// </summary>
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/// <returns>The trace of this matrix</returns>
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/// <exception cref="ArgumentException">If the matrix is not square</exception>
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public override double Trace()
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{
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if (RowCount != ColumnCount)
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{
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throw new ArgumentException("Matrix must be square.");
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}
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var sum = 0.0;
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for (var i = 0; i < RowCount; i++)
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{
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sum += At(i, i);
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}
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return sum;
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}
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protected override void DoPointwiseMinimum(double scalar, Matrix<double> result)
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{
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Map(x => Math.Min(scalar, x), result, scalar >= 0d ? Zeros.AllowSkip : Zeros.Include);
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}
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protected override void DoPointwiseMaximum(double scalar, Matrix<double> result)
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{
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Map(x => Math.Max(scalar, x), result, scalar <= 0d ? Zeros.AllowSkip : Zeros.Include);
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}
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protected override void DoPointwiseAbsoluteMinimum(double scalar, Matrix<double> result)
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{
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double absolute = Math.Abs(scalar);
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Map(x => Math.Min(absolute, Math.Abs(x)), result, Zeros.AllowSkip);
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}
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protected override void DoPointwiseAbsoluteMaximum(double scalar, Matrix<double> result)
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{
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double absolute = Math.Abs(scalar);
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Map(x => Math.Max(absolute, Math.Abs(x)), result, Zeros.Include);
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}
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protected override void DoPointwiseMinimum(Matrix<double> other, Matrix<double> result)
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{
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Map2(Math.Min, other, result, Zeros.AllowSkip);
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}
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protected override void DoPointwiseMaximum(Matrix<double> other, Matrix<double> result)
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{
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Map2(Math.Max, other, result, Zeros.AllowSkip);
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}
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protected override void DoPointwiseAbsoluteMinimum(Matrix<double> other, Matrix<double> result)
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{
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Map2((x, y) => Math.Min(Math.Abs(x), Math.Abs(y)), other, result, Zeros.AllowSkip);
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}
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protected override void DoPointwiseAbsoluteMaximum(Matrix<double> other, Matrix<double> result)
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{
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Map2((x, y) => Math.Max(Math.Abs(x), Math.Abs(y)), other, result, Zeros.AllowSkip);
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}
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/// <summary>Calculates the induced L1 norm of this matrix.</summary>
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/// <returns>The maximum absolute column sum of the matrix.</returns>
|
public override double L1Norm()
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{
|
var norm = 0d;
|
for (var j = 0; j < ColumnCount; j++)
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{
|
var s = 0d;
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for (var i = 0; i < RowCount; i++)
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{
|
s += Math.Abs(At(i, j));
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}
|
norm = Math.Max(norm, s);
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}
|
return norm;
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}
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|
/// <summary>Calculates the induced infinity norm of this matrix.</summary>
|
/// <returns>The maximum absolute row sum of the matrix.</returns>
|
public override double InfinityNorm()
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{
|
var norm = 0d;
|
for (var i = 0; i < RowCount; i++)
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{
|
var s = 0d;
|
for (var j = 0; j < ColumnCount; j++)
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{
|
s += Math.Abs(At(i, j));
|
}
|
norm = Math.Max(norm, s);
|
}
|
return norm;
|
}
|
|
/// <summary>Calculates the entry-wise Frobenius norm of this matrix.</summary>
|
/// <returns>The square root of the sum of the squared values.</returns>
|
public override double FrobeniusNorm()
|
{
|
var transpose = Transpose();
|
var aat = this*transpose;
|
var norm = 0d;
|
for (var i = 0; i < RowCount; i++)
|
{
|
norm += aat.At(i, i);
|
}
|
return Math.Sqrt(norm);
|
}
|
|
/// <summary>
|
/// Calculates the p-norms of all row vectors.
|
/// Typical values for p are 1.0 (L1, Manhattan norm), 2.0 (L2, Euclidean norm) and positive infinity (infinity norm)
|
/// </summary>
|
public override Vector<double> RowNorms(double norm)
|
{
|
if (norm <= 0.0)
|
{
|
throw new ArgumentOutOfRangeException(nameof(norm), "Value must be positive.");
|
}
|
|
var ret = new double[RowCount];
|
if (norm == 2.0)
|
{
|
Storage.FoldByRowUnchecked(ret, (s, x) => s + x*x, (x, c) => Math.Sqrt(x), ret, Zeros.AllowSkip);
|
}
|
else if (norm == 1.0)
|
{
|
Storage.FoldByRowUnchecked(ret, (s, x) => s + Math.Abs(x), (x, c) => x, ret, Zeros.AllowSkip);
|
}
|
else if (double.IsPositiveInfinity(norm))
|
{
|
Storage.FoldByRowUnchecked(ret, (s, x) => Math.Max(s, Math.Abs(x)), (x, c) => x, ret, Zeros.AllowSkip);
|
}
|
else
|
{
|
double invnorm = 1.0/norm;
|
Storage.FoldByRowUnchecked(ret, (s, x) => s + Math.Pow(Math.Abs(x), norm), (x, c) => Math.Pow(x, invnorm), ret, Zeros.AllowSkip);
|
}
|
return Vector<double>.Build.Dense(ret);
|
}
|
|
/// <summary>
|
/// Calculates the p-norms of all column vectors.
|
/// Typical values for p are 1.0 (L1, Manhattan norm), 2.0 (L2, Euclidean norm) and positive infinity (infinity norm)
|
/// </summary>
|
public override Vector<double> ColumnNorms(double norm)
|
{
|
if (norm <= 0.0)
|
{
|
throw new ArgumentOutOfRangeException(nameof(norm), "Value must be positive.");
|
}
|
|
var ret = new double[ColumnCount];
|
if (norm == 2.0)
|
{
|
Storage.FoldByColumnUnchecked(ret, (s, x) => s + x*x, (x, c) => Math.Sqrt(x), ret, Zeros.AllowSkip);
|
}
|
else if (norm == 1.0)
|
{
|
Storage.FoldByColumnUnchecked(ret, (s, x) => s + Math.Abs(x), (x, c) => x, ret, Zeros.AllowSkip);
|
}
|
else if (double.IsPositiveInfinity(norm))
|
{
|
Storage.FoldByColumnUnchecked(ret, (s, x) => Math.Max(s, Math.Abs(x)), (x, c) => x, ret, Zeros.AllowSkip);
|
}
|
else
|
{
|
double invnorm = 1.0/norm;
|
Storage.FoldByColumnUnchecked(ret, (s, x) => s + Math.Pow(Math.Abs(x), norm), (x, c) => Math.Pow(x, invnorm), ret, Zeros.AllowSkip);
|
}
|
return Vector<double>.Build.Dense(ret);
|
}
|
|
/// <summary>
|
/// Normalizes all row vectors to a unit p-norm.
|
/// Typical values for p are 1.0 (L1, Manhattan norm), 2.0 (L2, Euclidean norm) and positive infinity (infinity norm)
|
/// </summary>
|
public sealed override Matrix<double> NormalizeRows(double norm)
|
{
|
var norminv = ((DenseVectorStorage<double>)RowNorms(norm).Storage).Data;
|
for (int i = 0; i < norminv.Length; i++)
|
{
|
norminv[i] = norminv[i] == 0d ? 1d : 1d/norminv[i];
|
}
|
|
var result = Build.SameAs(this, RowCount, ColumnCount);
|
Storage.MapIndexedTo(result.Storage, (i, j, x) => norminv[i]*x, Zeros.AllowSkip, ExistingData.AssumeZeros);
|
return result;
|
}
|
|
/// <summary>
|
/// Normalizes all column vectors to a unit p-norm.
|
/// Typical values for p are 1.0 (L1, Manhattan norm), 2.0 (L2, Euclidean norm) and positive infinity (infinity norm)
|
/// </summary>
|
public sealed override Matrix<double> NormalizeColumns(double norm)
|
{
|
var norminv = ((DenseVectorStorage<double>)ColumnNorms(norm).Storage).Data;
|
for (int i = 0; i < norminv.Length; i++)
|
{
|
norminv[i] = norminv[i] == 0d ? 1d : 1d/norminv[i];
|
}
|
|
var result = Build.SameAs(this, RowCount, ColumnCount);
|
Storage.MapIndexedTo(result.Storage, (i, j, x) => norminv[j]*x, Zeros.AllowSkip, ExistingData.AssumeZeros);
|
return result;
|
}
|
|
/// <summary>
|
/// Calculates the value sum of each row vector.
|
/// </summary>
|
public override Vector<double> RowSums()
|
{
|
var ret = new double[RowCount];
|
Storage.FoldByRowUnchecked(ret, (s, x) => s + x, (x, c) => x, ret, Zeros.AllowSkip);
|
return Vector<double>.Build.Dense(ret);
|
}
|
|
/// <summary>
|
/// Calculates the absolute value sum of each row vector.
|
/// </summary>
|
public override Vector<double> RowAbsoluteSums()
|
{
|
var ret = new double[RowCount];
|
Storage.FoldByRowUnchecked(ret, (s, x) => s + Math.Abs(x), (x, c) => x, ret, Zeros.AllowSkip);
|
return Vector<double>.Build.Dense(ret);
|
}
|
|
/// <summary>
|
/// Calculates the value sum of each column vector.
|
/// </summary>
|
public override Vector<double> ColumnSums()
|
{
|
var ret = new double[ColumnCount];
|
Storage.FoldByColumnUnchecked(ret, (s, x) => s + x, (x, c) => x, ret, Zeros.AllowSkip);
|
return Vector<double>.Build.Dense(ret);
|
}
|
|
/// <summary>
|
/// Calculates the absolute value sum of each column vector.
|
/// </summary>
|
public override Vector<double> ColumnAbsoluteSums()
|
{
|
var ret = new double[ColumnCount];
|
Storage.FoldByColumnUnchecked(ret, (s, x) => s + Math.Abs(x), (x, c) => x, ret, Zeros.AllowSkip);
|
return Vector<double>.Build.Dense(ret);
|
}
|
|
/// <summary>
|
/// Evaluates whether this matrix is Hermitian (conjugate symmetric).
|
/// </summary>
|
public sealed override bool IsHermitian()
|
{
|
return IsSymmetric();
|
}
|
|
public override Cholesky<double> Cholesky()
|
{
|
return UserCholesky.Create(this);
|
}
|
|
public override LU<double> LU()
|
{
|
return UserLU.Create(this);
|
}
|
|
public override QR<double> QR(QRMethod method = QRMethod.Thin)
|
{
|
return UserQR.Create(this, method);
|
}
|
|
public override GramSchmidt<double> GramSchmidt()
|
{
|
return UserGramSchmidt.Create(this);
|
}
|
|
public override Svd<double> Svd(bool computeVectors = true)
|
{
|
return UserSvd.Create(this, computeVectors);
|
}
|
|
public override Evd<double> Evd(Symmetricity symmetricity = Symmetricity.Unknown)
|
{
|
return UserEvd.Create(this, symmetricity);
|
}
|
}
|
}
|
