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C# UserDefinedMatrix类代码示例

原作者: [db:作者] 来自: [db:来源] 收藏 邀请

本文整理汇总了C#中UserDefinedMatrix的典型用法代码示例。如果您正苦于以下问题:C# UserDefinedMatrix类的具体用法?C# UserDefinedMatrix怎么用?C# UserDefinedMatrix使用的例子?那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。



UserDefinedMatrix类属于命名空间,在下文中一共展示了UserDefinedMatrix类的20个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于我们的系统推荐出更棒的C#代码示例。

示例1: CanFactorizeRandomMatrix

        public void CanFactorizeRandomMatrix(int row, int column)
        {
            var matrixA = new UserDefinedMatrix(Matrix<double>.Build.Random(row, column, 1).ToArray());
            var factorSvd = matrixA.Svd();
            var u = factorSvd.U;
            var vt = factorSvd.VT;
            var w = factorSvd.W;

            // Make sure the U has the right dimensions.
            Assert.AreEqual(row, u.RowCount);
            Assert.AreEqual(row, u.ColumnCount);

            // Make sure the VT has the right dimensions.
            Assert.AreEqual(column, vt.RowCount);
            Assert.AreEqual(column, vt.ColumnCount);

            // Make sure the W has the right dimensions.
            Assert.AreEqual(row, w.RowCount);
            Assert.AreEqual(column, w.ColumnCount);

            // Make sure the U*W*VT is the original matrix.
            var matrix = u*w*vt;
            for (var i = 0; i < matrix.RowCount; i++)
            {
                for (var j = 0; j < matrix.ColumnCount; j++)
                {
                    Assert.AreEqual(matrixA[i, j], matrix[i, j], 1.0e-11);
                }
            }
        }
开发者ID:Jungwon,项目名称:mathnet-numerics,代码行数:30,代码来源:UserSvdTests.cs


示例2: CanFactorizeRandomMatrix

        public void CanFactorizeRandomMatrix(int order)
        {
            var matrixA = new UserDefinedMatrix(Matrix<Complex>.Build.Random(order, order, 1).ToArray());
            var factorEvd = matrixA.Evd();
            var eigenVectors = factorEvd.EigenVectors;
            var d = factorEvd.D;

            Assert.AreEqual(order, eigenVectors.RowCount);
            Assert.AreEqual(order, eigenVectors.ColumnCount);

            Assert.AreEqual(order, d.RowCount);
            Assert.AreEqual(order, d.ColumnCount);

            // Make sure the A*V = λ*V 
            var matrixAv = matrixA * eigenVectors;
            var matrixLv = eigenVectors * d;

            for (var i = 0; i < matrixAv.RowCount; i++)
            {
                for (var j = 0; j < matrixAv.ColumnCount; j++)
                {
                    AssertHelpers.AlmostEqualRelative(matrixAv[i, j], matrixLv[i, j], 7);
                }
            }
        }
开发者ID:MaLiN2223,项目名称:mathnet-numerics,代码行数:25,代码来源:UserEvdTests.cs


示例3: CanFactorizeRandomMatrix

        public void CanFactorizeRandomMatrix(int order)
        {
            var matrixX = new UserDefinedMatrix(Matrix<float>.Build.RandomPositiveDefinite(order, 1).ToArray());
            var chol = matrixX.Cholesky();
            var factorC = chol.Factor;

            // Make sure the Cholesky factor has the right dimensions.
            Assert.AreEqual(order, factorC.RowCount);
            Assert.AreEqual(order, factorC.ColumnCount);

            // Make sure the Cholesky factor is lower triangular.
            for (var i = 0; i < factorC.RowCount; i++)
            {
                for (var j = i + 1; j < factorC.ColumnCount; j++)
                {
                    Assert.AreEqual(0.0, factorC[i, j]);
                }
            }

            // Make sure the cholesky factor times it's transpose is the original matrix.
            var matrixXfromC = factorC * factorC.Transpose();
            for (var i = 0; i < matrixXfromC.RowCount; i++)
            {
                for (var j = 0; j < matrixXfromC.ColumnCount; j++)
                {
                    Assert.AreEqual(matrixX[i, j], matrixXfromC[i, j], 1e-3);
                }
            }
        }
开发者ID:skair39,项目名称:mathnet-numerics,代码行数:29,代码来源:UserCholeskyTests.cs


示例4: CanCheckRankOfNonSquare

        public void CanCheckRankOfNonSquare(int row, int column)
        {
            var matrixA = new UserDefinedMatrix(Matrix<float>.Build.Random(row, column, 1).ToArray());
            var factorSvd = matrixA.Svd();

            var mn = Math.Min(row, column);
            Assert.AreEqual(factorSvd.Rank, mn);
        }
开发者ID:Jungwon,项目名称:mathnet-numerics,代码行数:8,代码来源:UserSvdTests.cs


示例5: CanCheckRankOfSquareSingular

        public void CanCheckRankOfSquareSingular(int order)
        {
            var matrixA = new UserDefinedMatrix(order, order);
            matrixA[0, 0] = 1;
            matrixA[order - 1, order - 1] = 1;
            for (var i = 1; i < order - 1; i++)
            {
                matrixA[i, i - 1] = 1;
                matrixA[i, i + 1] = 1;
                matrixA[i - 1, i] = 1;
                matrixA[i + 1, i] = 1;
            }

            var factorSvd = matrixA.Svd();

            Assert.AreEqual(factorSvd.Determinant, 0);
            Assert.AreEqual(factorSvd.Rank, order - 1);
        }
开发者ID:Jungwon,项目名称:mathnet-numerics,代码行数:18,代码来源:UserSvdTests.cs


示例6: CanCheckRankOfSquareSingular

        public void CanCheckRankOfSquareSingular([Values(10, 50, 100)] int order)
        {
            var matrixA = new UserDefinedMatrix(order, order);
            matrixA[0, 0] = 1;
            matrixA[order - 1, order - 1] = 1;
            for (var i = 1; i < order - 1; i++)
            {
                matrixA[i, i - 1] = 1;
                matrixA[i, i + 1] = 1;
                matrixA[i - 1, i] = 1;
                matrixA[i + 1, i] = 1;
            }

            var factorEvd = matrixA.Evd();

            Assert.AreEqual(factorEvd.Determinant, Complex32.Zero);
            Assert.AreEqual(factorEvd.Rank, order - 1);
        }
开发者ID:Amichai,项目名称:PhysicsPad,代码行数:18,代码来源:UserEvdTests.cs


示例7: CanWriteTabDelimitedData

 public void CanWriteTabDelimitedData()
 {
     var matrix = new UserDefinedMatrix(new[,] { { 1.1, 2.2, 3.3 }, { 4.4, 5.5, 6.6 }, { 7.7, 8.8, 9.9 } });
     var headers = new[] { "a", "b", "c" };
     var writer = new DelimitedWriter('\t')
                  {
                      ColumnHeaders = headers
                  };
     var stream = new MemoryStream();
     writer.WriteMatrix(matrix, stream);
     var data = stream.ToArray();
     var reader = new StreamReader(new MemoryStream(data));
     var text = reader.ReadToEnd();
     var expected = "a\tb\tc"
         + Environment.NewLine
         + "1.1\t2.2\t3.3"
         + Environment.NewLine
         + "4.4\t5.5\t6.6"
         + Environment.NewLine
         + "7.7\t8.8\t9.9";
     Assert.AreEqual(expected, text);
 }
开发者ID:rafaortega,项目名称:mathnet-numerics,代码行数:22,代码来源:DelimitedWriterTests.cs


示例8: CanSolveForRandomVector

        public void CanSolveForRandomVector(int row, int column)
        {
            var matrixA = new UserDefinedMatrix(Matrix<Complex>.Build.Random(row, column, 1).ToArray());
            var matrixACopy = matrixA.Clone();
            var factorSvd = matrixA.Svd();

            var vectorb = new UserDefinedVector(Vector<Complex>.Build.Random(row, 1).ToArray());
            var resultx = factorSvd.Solve(vectorb);

            Assert.AreEqual(matrixA.ColumnCount, resultx.Count);

            var matrixBReconstruct = matrixA*resultx;

            // Check the reconstruction.
            for (var i = 0; i < vectorb.Count; i++)
            {
                AssertHelpers.AlmostEqual(vectorb[i], matrixBReconstruct[i], 10);
            }

            // Make sure A didn't change.
            for (var i = 0; i < matrixA.RowCount; i++)
            {
                for (var j = 0; j < matrixA.ColumnCount; j++)
                {
                    Assert.AreEqual(matrixACopy[i, j], matrixA[i, j]);
                }
            }
        }
开发者ID:Jungwon,项目名称:mathnet-numerics,代码行数:28,代码来源:UserSvdTests.cs


示例9: LUFailsWithNonSquareMatrix

 public void LUFailsWithNonSquareMatrix()
 {
     var matrix = new UserDefinedMatrix(3, 2);
     Assert.Throws<ArgumentException>(() => matrix.LU());
 }
开发者ID:Amichai,项目名称:PhysicsPad,代码行数:5,代码来源:UserLUTests.cs


示例10: CanSolveForRandomMatrixWhenResultMatrixGiven

        public void CanSolveForRandomMatrixWhenResultMatrixGiven(int order)
        {
            var matrixA = new UserDefinedMatrix(Matrix<Complex>.Build.Random(order, order, 1).ToArray());
            var matrixACopy = matrixA.Clone();
            var factorGramSchmidt = matrixA.GramSchmidt();

            var matrixB = new UserDefinedMatrix(Matrix<Complex>.Build.Random(order, order, 1).ToArray());
            var matrixBCopy = matrixB.Clone();

            var matrixX = new UserDefinedMatrix(order, order);
            factorGramSchmidt.Solve(matrixB, matrixX);

            // The solution X row dimension is equal to the column dimension of A
            Assert.AreEqual(matrixA.ColumnCount, matrixX.RowCount);

            // The solution X has the same number of columns as B
            Assert.AreEqual(matrixB.ColumnCount, matrixX.ColumnCount);

            var matrixBReconstruct = matrixA * matrixX;

            // Check the reconstruction.
            for (var i = 0; i < matrixB.RowCount; i++)
            {
                for (var j = 0; j < matrixB.ColumnCount; j++)
                {
                    AssertHelpers.AlmostEqual(matrixB[i, j], matrixBReconstruct[i, j], 10);
                }
            }

            // Make sure A didn't change.
            for (var i = 0; i < matrixA.RowCount; i++)
            {
                for (var j = 0; j < matrixA.ColumnCount; j++)
                {
                    Assert.AreEqual(matrixACopy[i, j], matrixA[i, j]);
                }
            }

            // Make sure B didn't change.
            for (var i = 0; i < matrixB.RowCount; i++)
            {
                for (var j = 0; j < matrixB.ColumnCount; j++)
                {
                    Assert.AreEqual(matrixBCopy[i, j], matrixB[i, j]);
                }
            }
        }
开发者ID:kityandhero,项目名称:mathnet-numerics,代码行数:47,代码来源:UserGramSchmidtTests.cs


示例11: CanSolveForRandomMatrix

        public void CanSolveForRandomMatrix(int row, int col)
        {
            var matrixA = new UserDefinedMatrix(Matrix<Complex32>.Build.RandomPositiveDefinite(row, 1).ToArray());
            var matrixACopy = matrixA.Clone();
            var chol = matrixA.Cholesky();
            var matrixB = new UserDefinedMatrix(Matrix<Complex32>.Build.Random(row, col, 1).ToArray());
            var matrixX = chol.Solve(matrixB);

            Assert.AreEqual(matrixB.RowCount, matrixX.RowCount);
            Assert.AreEqual(matrixB.ColumnCount, matrixX.ColumnCount);

            var matrixBReconstruct = matrixA * matrixX;

            // Check the reconstruction.
            for (var i = 0; i < matrixB.RowCount; i++)
            {
                for (var j = 0; j < matrixB.ColumnCount; j++)
                {
                    Assert.AreEqual(matrixB[i, j].Real, matrixBReconstruct[i, j].Real, 0.01f);
                    Assert.AreEqual(matrixB[i, j].Imaginary, matrixBReconstruct[i, j].Imaginary, 0.01f);
                }
            }

            // Make sure A didn't change.
            for (var i = 0; i < matrixA.RowCount; i++)
            {
                for (var j = 0; j < matrixA.ColumnCount; j++)
                {
                    Assert.AreEqual(matrixACopy[i, j], matrixA[i, j]);
                }
            }
        }
开发者ID:rmundy,项目名称:mathnet-numerics,代码行数:32,代码来源:UserCholeskyTests.cs


示例12: CanSolveForRandomMatrixWhenResultMatrixGiven

        public void CanSolveForRandomMatrixWhenResultMatrixGiven(int row, int col)
        {
            var matrixA = new UserDefinedMatrix(Matrix<float>.Build.RandomPositiveDefinite(row, 1).ToArray());
            var matrixACopy = matrixA.Clone();
            var chol = matrixA.Cholesky();
            var matrixB = new UserDefinedMatrix(Matrix<float>.Build.Random(row, col, 1).ToArray());
            var matrixBCopy = matrixB.Clone();
            var matrixX = new UserDefinedMatrix(row, col);
            chol.Solve(matrixB, matrixX);

            Assert.AreEqual(matrixB.RowCount, matrixX.RowCount);
            Assert.AreEqual(matrixB.ColumnCount, matrixX.ColumnCount);

            var matrixBReconstruct = matrixA * matrixX;

            // Check the reconstruction.
            for (var i = 0; i < matrixB.RowCount; i++)
            {
                for (var j = 0; j < matrixB.ColumnCount; j++)
                {
                    Assert.AreEqual(matrixB[i, j], matrixBReconstruct[i, j], 1.0);
                }
            }

            // Make sure A didn't change.
            for (var i = 0; i < matrixA.RowCount; i++)
            {
                for (var j = 0; j < matrixA.ColumnCount; j++)
                {
                    Assert.AreEqual(matrixACopy[i, j], matrixA[i, j]);
                }
            }

            // Make sure B didn't change.
            for (var i = 0; i < matrixB.RowCount; i++)
            {
                for (var j = 0; j < matrixB.ColumnCount; j++)
                {
                    Assert.AreEqual(matrixBCopy[i, j], matrixB[i, j]);
                }
            }
        }
开发者ID:skair39,项目名称:mathnet-numerics,代码行数:42,代码来源:UserCholeskyTests.cs


示例13: CholeskyFailsWithNonSquareMatrix

 public void CholeskyFailsWithNonSquareMatrix()
 {
     var matrixI = new UserDefinedMatrix(3, 2);
     Assert.That(() => matrixI.Cholesky(), Throws.ArgumentException);
 }
开发者ID:skair39,项目名称:mathnet-numerics,代码行数:5,代码来源:UserCholeskyTests.cs


示例14: CanSolveForRandomVector

        public void CanSolveForRandomVector(int order)
        {
            var matrixA = new UserDefinedMatrix(Matrix<Complex32>.Build.Random(order, order, 1).ToArray());
            var matrixACopy = matrixA.Clone();
            var factorGramSchmidt = matrixA.GramSchmidt();

            var vectorb = new UserDefinedVector(Vector<Complex32>.Build.Random(order, 1).ToArray());
            var resultx = factorGramSchmidt.Solve(vectorb);

            Assert.AreEqual(matrixA.ColumnCount, resultx.Count);

            var matrixBReconstruct = matrixA * resultx;

            // Check the reconstruction.
            for (var i = 0; i < order; i++)
            {
                Assert.AreEqual(vectorb[i].Real, matrixBReconstruct[i].Real, 1e-3f);
                Assert.AreEqual(vectorb[i].Imaginary, matrixBReconstruct[i].Imaginary, 1e-3f);
            }

            // Make sure A didn't change.
            for (var i = 0; i < matrixA.RowCount; i++)
            {
                for (var j = 0; j < matrixA.ColumnCount; j++)
                {
                    Assert.AreEqual(matrixACopy[i, j], matrixA[i, j]);
                }
            }
        }
开发者ID:skair39,项目名称:mathnet-numerics,代码行数:29,代码来源:UserGramSchmidtTests.cs


示例15: CanSolveForRandomVectorWhenResultVectorGivenUsingThinQR

        public void CanSolveForRandomVectorWhenResultVectorGivenUsingThinQR(int order)
        {
            var matrixA = new UserDefinedMatrix(Matrix<double>.Build.Random(order, order, 1).ToArray());
            var matrixACopy = matrixA.Clone();
            var factorQR = matrixA.QR(QRMethod.Thin);
            var vectorb = new UserDefinedVector(Vector<double>.Build.Random(order, 1).ToArray());
            var vectorbCopy = vectorb.Clone();
            var resultx = new UserDefinedVector(order);
            factorQR.Solve(vectorb, resultx);

            Assert.AreEqual(vectorb.Count, resultx.Count);

            var matrixBReconstruct = matrixA * resultx;

            // Check the reconstruction.
            for (var i = 0; i < vectorb.Count; i++)
            {
                Assert.AreEqual(vectorb[i], matrixBReconstruct[i], 1.0e-11);
            }

            // Make sure A didn't change.
            for (var i = 0; i < matrixA.RowCount; i++)
            {
                for (var j = 0; j < matrixA.ColumnCount; j++)
                {
                    Assert.AreEqual(matrixACopy[i, j], matrixA[i, j]);
                }
            }

            // Make sure b didn't change.
            for (var i = 0; i < vectorb.Count; i++)
            {
                Assert.AreEqual(vectorbCopy[i], vectorb[i]);
            }
        }
开发者ID:Jungwon,项目名称:mathnet-numerics,代码行数:35,代码来源:UserQRTests.cs


示例16: CanSolveForRandomVectorAndSymmetricMatrixWhenResultVectorGiven

        public void CanSolveForRandomVectorAndSymmetricMatrixWhenResultVectorGiven([Values(1, 2, 5, 10, 50, 100)] int order)
        {
            var A = new UserDefinedMatrix(Matrix<Complex>.Build.RandomPositiveDefinite(order, 1).ToArray());
            MatrixHelpers.ForceHermitian(A);
            var ACopy = A.Clone();
            var evd = A.Evd(Symmetricity.Hermitian);

            var b = new UserDefinedVector(Vector<Complex>.Build.Random(order, 1).ToArray());
            var bCopy = b.Clone();

            var x = new UserDefinedVector(order);
            evd.Solve(b, x);

            var bReconstruct = A * x;

            // Check the reconstruction.
            AssertHelpers.AlmostEqual(b, bReconstruct, 9);

            // Make sure A/B didn't change.
            AssertHelpers.AlmostEqual(ACopy, A, 14);
            AssertHelpers.AlmostEqual(bCopy, b, 14);
        }
开发者ID:MaLiN2223,项目名称:mathnet-numerics,代码行数:22,代码来源:UserEvdTests.cs


示例17: CanSolveForRandomMatrixAndSymmetricMatrixWhenResultMatrixGiven

        public void CanSolveForRandomMatrixAndSymmetricMatrixWhenResultMatrixGiven([Values(1, 2, 5, 10, 50, 100)] int order)
        {
            var A = new UserDefinedMatrix(Matrix<Complex>.Build.RandomPositiveDefinite(order, 1).ToArray());
            MatrixHelpers.ForceHermitian(A);
            var ACopy = A.Clone();
            var evd = A.Evd(Symmetricity.Hermitian);

            var B = new UserDefinedMatrix(Matrix<Complex>.Build.Random(order, order, 1).ToArray());
            var BCopy = B.Clone();

            var X = new UserDefinedMatrix(order, order);
            evd.Solve(B, X);

            // The solution X row dimension is equal to the column dimension of A
            Assert.AreEqual(A.ColumnCount, X.RowCount);

            // The solution X has the same number of columns as B
            Assert.AreEqual(B.ColumnCount, X.ColumnCount);

            var BReconstruct = A * X;

            // Check the reconstruction.
            AssertHelpers.AlmostEqual(B, BReconstruct, 9);

            // Make sure A/B didn't change.
            AssertHelpers.AlmostEqual(ACopy, A, 14);
            AssertHelpers.AlmostEqual(BCopy, B, 14);
        }
开发者ID:MaLiN2223,项目名称:mathnet-numerics,代码行数:28,代码来源:UserEvdTests.cs


示例18: CanCheckRankSquare

        public void CanCheckRankSquare(int order)
        {
            var matrixA = new UserDefinedMatrix(Matrix<Complex>.Build.Random(order, order, 1).ToArray());
            var factorEvd = matrixA.Evd();

            Assert.AreEqual(factorEvd.Rank, order);
        }
开发者ID:MaLiN2223,项目名称:mathnet-numerics,代码行数:7,代码来源:UserEvdTests.cs


示例19: CanFactorizeRandomSymmetricMatrix

        public void CanFactorizeRandomSymmetricMatrix(int order)
        {
            var matrixA = new UserDefinedMatrix(Matrix<Complex>.Build.RandomPositiveDefinite(order, 1).ToArray());
            var factorEvd = matrixA.Evd(Symmetricity.Hermitian);
            var eigenVectors = factorEvd.EigenVectors;
            var d = factorEvd.D;

            Assert.AreEqual(order, eigenVectors.RowCount);
            Assert.AreEqual(order, eigenVectors.ColumnCount);

            Assert.AreEqual(order, d.RowCount);
            Assert.AreEqual(order, d.ColumnCount);

            // Make sure the A = V*λ*VT 
            var matrix = eigenVectors * d * eigenVectors.ConjugateTranspose();

            for (var i = 0; i < matrix.RowCount; i++)
            {
                for (var j = 0; j < matrix.ColumnCount; j++)
                {
                    AssertHelpers.AlmostEqualRelative(matrix[i, j], matrixA[i, j], 7);
                }
            }
        }
开发者ID:MaLiN2223,项目名称:mathnet-numerics,代码行数:24,代码来源:UserEvdTests.cs


示例20: CanSolveForRandomVectorWhenResultVectorGiven

        public void CanSolveForRandomVectorWhenResultVectorGiven(int order)
        {
            var matrixA = new UserDefinedMatrix(Matrix<Complex>.Build.Random(order, order, 1).ToArray());
            var matrixACopy = matrixA.Clone();
            var factorGramSchmidt = matrixA.GramSchmidt();
            var vectorb = new UserDefinedVector(Vector<Complex>.Build.Random(order, 1).ToArray());
            var vectorbCopy = vectorb.Clone();
            var resultx = new UserDefinedVector(order);
            factorGramSchmidt.Solve(vectorb, resultx);

            Assert.AreEqual(vectorb.Count, resultx.Count);

            var matrixBReconstruct = matrixA * resultx;

            // Check the reconstruction.
            for (var i = 0; i < vectorb.Count; i++)
            {
                AssertHelpers.AlmostEqual(vectorb[i], matrixBReconstruct[i], 10);
            }

            // Make sure A didn't change.
            for (var i = 0; i < matrixA.RowCount; i++)
            {
                for (var j = 0; j < matrixA.ColumnCount; j++)
                {
                    Assert.AreEqual(matrixACopy[i, j], matrixA[i, j]);
                }
            }

            // Make sure b didn't change.
            for (var i = 0; i < vectorb.Count; i++)
            {
                Assert.AreEqual(vectorbCopy[i], vectorb[i]);
            }
        }
开发者ID:kityandhero,项目名称:mathnet-numerics,代码行数:35,代码来源:UserGramSchmidtTests.cs



注:本文中的UserDefinedMatrix类示例整理自Github/MSDocs等源码及文档管理平台,相关代码片段筛选自各路编程大神贡献的开源项目,源码版权归原作者所有,传播和使用请参考对应项目的License;未经允许,请勿转载。


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C# UserDefinedVector类代码示例发布时间:2022-05-24
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