LA: Avoid cloning matrix factorization results at point of access

src/Examples/Interpolation/LinearBetweenPoints.cs

@@ -26,7 +26,6 @@
 
 using System;
 using MathNet.Numerics;
-using MathNet.Numerics.Interpolation;
 using MathNet.Numerics.Random;
 using MathNet.Numerics.Signals;
 

src/Examples/Interpolation/RationalWithPoles.cs

@@ -26,7 +26,6 @@
 
 using System;
 using MathNet.Numerics;
-using MathNet.Numerics.Interpolation;
 using MathNet.Numerics.Random;
 using MathNet.Numerics.Signals;
 

src/Examples/Interpolation/RationalWithoutPoles.cs

@@ -26,7 +26,6 @@
 
 using System;
 using MathNet.Numerics;
-using MathNet.Numerics.Interpolation;
 using MathNet.Numerics.Random;
 using MathNet.Numerics.Signals;
 

src/Examples/LinearAlgebra/Factorization/Evd.cs

@@ -87,27 +87,27 @@ namespace Examples.LinearAlgebra.FactorizationExamples
 
             // 1. Eigen vectors
             Console.WriteLine(@"1. Eigen vectors");
-            Console.WriteLine(evd.EigenVectors().ToString("#0.00\t", formatProvider));
+            Console.WriteLine(evd.EigenVectors.ToString("#0.00\t", formatProvider));
             Console.WriteLine();
 
             // 2. Eigen values as a complex vector
             Console.WriteLine(@"2. Eigen values as a complex vector");
-            Console.WriteLine(evd.EigenValues().ToString("N", formatProvider));
+            Console.WriteLine(evd.EigenValues.ToString("N", formatProvider));
             Console.WriteLine();
 
             // 3. Eigen values as the block diagonal matrix
             Console.WriteLine(@"3. Eigen values as the block diagonal matrix");
-            Console.WriteLine(evd.D().ToString("#0.00\t", formatProvider));
+            Console.WriteLine(evd.D.ToString("#0.00\t", formatProvider));
             Console.WriteLine();
 
             // 4. Multiply V by its transpose VT
-            var identity = evd.EigenVectors().TransposeAndMultiply(evd.EigenVectors());
+            var identity = evd.EigenVectors.TransposeAndMultiply(evd.EigenVectors);
             Console.WriteLine(@"4. Multiply V by its transpose VT: V*VT = I");
             Console.WriteLine(identity.ToString("#0.00\t", formatProvider));
             Console.WriteLine();
 
             // 5. Reconstruct initial matrix: A = V*D*V'
-            var reconstruct = evd.EigenVectors() * evd.D() * evd.EigenVectors().Transpose();
+            var reconstruct = evd.EigenVectors * evd.D * evd.EigenVectors.Transpose();
             Console.WriteLine(@"5. Reconstruct initial matrix: A = V*D*V'");
             Console.WriteLine(reconstruct.ToString("#0.00\t", formatProvider));
             Console.WriteLine();
@@ -142,33 +142,33 @@ namespace Examples.LinearAlgebra.FactorizationExamples
 
             // 8. Eigen vectors
             Console.WriteLine(@"8. Eigen vectors");
-            Console.WriteLine(evd.EigenVectors().ToString("#0.00\t", formatProvider));
+            Console.WriteLine(evd.EigenVectors.ToString("#0.00\t", formatProvider));
             Console.WriteLine();
 
             // 9. Eigen values as a complex vector
             Console.WriteLine(@"9. Eigen values as a complex vector");
-            Console.WriteLine(evd.EigenValues().ToString("N", formatProvider));
+            Console.WriteLine(evd.EigenValues.ToString("N", formatProvider));
             Console.WriteLine();
 
             // 10. Eigen values as the block diagonal matrix
             Console.WriteLine(@"10. Eigen values as the block diagonal matrix");
-            Console.WriteLine(evd.D().ToString("#0.00\t", formatProvider));
+            Console.WriteLine(evd.D.ToString("#0.00\t", formatProvider));
             Console.WriteLine();
 
             // 11. Multiply A * V
-            var av = matrix * evd.EigenVectors();
+            var av = matrix * evd.EigenVectors;
             Console.WriteLine(@"11. Multiply A * V");
             Console.WriteLine(av.ToString("#0.00\t", formatProvider));
             Console.WriteLine();
 
             // 12. Multiply V * D
-            var vd = evd.EigenVectors() * evd.D();
+            var vd = evd.EigenVectors * evd.D;
             Console.WriteLine(@"12. Multiply V * D");
             Console.WriteLine(vd.ToString("#0.00\t", formatProvider));
             Console.WriteLine();
 
             // 13. Reconstruct non-symmetriv matrix A = V * D * Vinverse
-            reconstruct = evd.EigenVectors() * evd.D() * evd.EigenVectors().Inverse();
+            reconstruct = evd.EigenVectors * evd.D * evd.EigenVectors.Inverse();
             Console.WriteLine(@"13. Reconstruct non-symmetriv matrix A = V * D * Vinverse");
             Console.WriteLine(reconstruct.ToString("#0.00\t", formatProvider));
             Console.WriteLine();

src/Examples/LinearAlgebra/Factorization/Svd.cs

@@ -87,12 +87,12 @@ namespace Examples.LinearAlgebra.FactorizationExamples
 
             // 1. Left singular vectors
             Console.WriteLine(@"1. Left singular vectors");
-            Console.WriteLine(svd.U().ToString("#0.00\t", formatProvider));
+            Console.WriteLine(svd.U.ToString("#0.00\t", formatProvider));
             Console.WriteLine();
 
             // 2. Singular values as vector
             Console.WriteLine(@"2. Singular values as vector");
-            Console.WriteLine(svd.S().ToString("#0.00\t", formatProvider));
+            Console.WriteLine(svd.S.ToString("#0.00\t", formatProvider));
             Console.WriteLine();
 
             // 3. Singular values as diagonal matrix
@@ -102,23 +102,23 @@ namespace Examples.LinearAlgebra.FactorizationExamples
 
             // 4. Right singular vectors
             Console.WriteLine(@"4. Right singular vectors");
-            Console.WriteLine(svd.VT().ToString("#0.00\t", formatProvider));
+            Console.WriteLine(svd.VT.ToString("#0.00\t", formatProvider));
             Console.WriteLine();
 
             // 5. Multiply U matrix by its transpose
-            var identinty = svd.U() * svd.U().Transpose();
+            var identinty = svd.U * svd.U.Transpose();
             Console.WriteLine(@"5. Multiply U matrix by its transpose");
             Console.WriteLine(identinty.ToString("#0.00\t", formatProvider));
             Console.WriteLine();
 
             // 6. Multiply V matrix by its transpose
-            identinty = svd.VT().TransposeAndMultiply(svd.VT());
+            identinty = svd.VT.TransposeAndMultiply(svd.VT);
             Console.WriteLine(@"6. Multiply V matrix by its transpose");
             Console.WriteLine(identinty.ToString("#0.00\t", formatProvider));
             Console.WriteLine();
 
             // 7. Reconstruct initial matrix: A = U*Σ*VT
-            var reconstruct = svd.U() * svd.W() * svd.VT();
+            var reconstruct = svd.U * svd.W() * svd.VT;
             Console.WriteLine(@"7. Reconstruct initial matrix: A = U*S*VT");
             Console.WriteLine(reconstruct.ToString("#0.00\t", formatProvider));
             Console.WriteLine();
@@ -149,7 +149,7 @@ namespace Examples.LinearAlgebra.FactorizationExamples
 
             // 12. Singular values as vector
             Console.WriteLine(@"12. Singular values as vector");
-            Console.WriteLine(svd.S().ToString("#0.00\t", formatProvider));
+            Console.WriteLine(svd.S.ToString("#0.00\t", formatProvider));
             Console.WriteLine();
 
             // 13. Singular values as diagonal matrix
@@ -161,7 +161,7 @@ namespace Examples.LinearAlgebra.FactorizationExamples
             try
             {
                 Console.WriteLine(@"14. Access to left singular vectors when partial SVD decomposition was performed");
-                Console.WriteLine(svd.U().ToString("#0.00\t", formatProvider));
+                Console.WriteLine(svd.U.ToString("#0.00\t", formatProvider));
             }
             catch (Exception ex)
             {
@@ -173,7 +173,7 @@ namespace Examples.LinearAlgebra.FactorizationExamples
             try
             {
                 Console.WriteLine(@"15. Access to right singular vectors when partial SVD decomposition was performed");
-                Console.WriteLine(svd.VT().ToString("#0.00\t", formatProvider));
+                Console.WriteLine(svd.VT.ToString("#0.00\t", formatProvider));
             }
             catch (Exception ex)
             {

src/Numerics/Distributions/MatrixNormal.cs

@@ -31,7 +31,6 @@
 using System;
 using MathNet.Numerics.LinearAlgebra;
 using MathNet.Numerics.LinearAlgebra.Double;
-using MathNet.Numerics.LinearAlgebra.Factorization;
 using MathNet.Numerics.Properties;
 
 namespace MathNet.Numerics.Distributions

src/Numerics/LinearAlgebra/Complex/Factorization/Cholesky.cs

@@ -57,9 +57,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             get
             {
                 var det = Complex.One;
-                for (var j = 0; j < CholeskyFactor.RowCount; j++)
+                for (var j = 0; j < Factor.RowCount; j++)
                 {
-                    var d = CholeskyFactor.At(j, j);
+                    var d = Factor.At(j, j);
                     det *= d * d;
                 }
 
@@ -75,9 +75,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             get
             {
                 var det = Complex.Zero;
-                for (var j = 0; j < CholeskyFactor.RowCount; j++)
+                for (var j = 0; j < Factor.RowCount; j++)
                 {
-                    det += 2.0 * CholeskyFactor.At(j, j).Ln();
+                    det += 2.0 * Factor.At(j, j).Ln();
                 }
 
                 return det;

src/Numerics/LinearAlgebra/Complex/Factorization/DenseCholesky.cs

@@ -74,7 +74,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             // Create a new matrix for the Cholesky factor, then perform factorization (while overwriting).
             var factor = (DenseMatrix)matrix.Clone();
             Control.LinearAlgebraProvider.CholeskyFactor(factor.Values, factor.RowCount);
-            CholeskyFactor = factor;
+            Factor = factor;
         }
 
         /// <summary>
@@ -106,9 +106,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
-            if (input.RowCount != CholeskyFactor.RowCount)
+            if (input.RowCount != Factor.RowCount)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(input, CholeskyFactor);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(input, Factor);
             }
 
             var dinput = input as DenseMatrix;
@@ -127,7 +127,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             Array.Copy(dinput.Values, dresult.Values, dinput.Values.Length);
 
             // Cholesky solve by overwriting result.
-            var dfactor = (DenseMatrix)CholeskyFactor;
+            var dfactor = (DenseMatrix)Factor;
             Control.LinearAlgebraProvider.CholeskySolveFactored(dfactor.Values, dfactor.RowCount, dresult.Values, dresult.ColumnCount);
         }
 
@@ -155,9 +155,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
-            if (input.Count != CholeskyFactor.RowCount)
+            if (input.Count != Factor.RowCount)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(input, CholeskyFactor);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(input, Factor);
             }
 
             var dinput = input as DenseVector;
@@ -176,7 +176,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             Array.Copy(dinput.Values, dresult.Values, dinput.Values.Length);
 
             // Cholesky solve by overwriting result.
-            var dfactor = (DenseMatrix)CholeskyFactor;
+            var dfactor = (DenseMatrix)Factor;
             Control.LinearAlgebraProvider.CholeskySolveFactored(dfactor.Values, dfactor.RowCount, dresult.Values, 1);
         }
     }

src/Numerics/LinearAlgebra/Complex/Factorization/DenseEvd.cs

@@ -79,9 +79,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             var order = matrix.RowCount;
 
             // Initialize matrices for eigenvalues and eigenvectors
-            MatrixEv = DenseMatrix.Identity(order);
-            MatrixD = matrix.CreateMatrix(order, order);
-            VectorEv = new DenseVector(order);
+            EigenVectors = DenseMatrix.Identity(order);
+            D = matrix.CreateMatrix(order, order);
+            EigenValues = new DenseVector(order);
 
             IsSymmetric = true;
 
@@ -93,8 +93,8 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 }
             }
 
-            Control.LinearAlgebraProvider.EigenDecomp(IsSymmetric, order, matrix.Values, ((DenseMatrix) MatrixEv).Values,
-                ((DenseVector) VectorEv).Values, ((DenseMatrix) MatrixD).Values);
+            Control.LinearAlgebraProvider.EigenDecomp(IsSymmetric, order, matrix.Values, ((DenseMatrix) EigenVectors).Values,
+                ((DenseVector) EigenValues).Values, ((DenseMatrix) D).Values);
         }
 
         /// <summary>
@@ -840,20 +840,20 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (VectorEv.Count != input.RowCount)
+            if (EigenValues.Count != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (VectorEv.Count != result.RowCount)
+            if (EigenValues.Count != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
             if (IsSymmetric)
             {
-                var order = VectorEv.Count;
+                var order = EigenValues.Count;
                 var tmp = new Complex[order];
 
                 for (var k = 0; k < order; k++)
@@ -865,10 +865,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                         {
                             for (var i = 0; i < order; i++)
                             {
-                                value += ((DenseMatrix) MatrixEv).Values[(j*order) + i].Conjugate()*input.At(i, k);
+                                value += ((DenseMatrix) EigenVectors).Values[(j*order) + i].Conjugate()*input.At(i, k);
                             }
 
-                            value /= VectorEv[j].Real;
+                            value /= EigenValues[j].Real;
                         }
 
                         tmp[j] = value;
@@ -879,7 +879,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                         Complex value = 0.0;
                         for (var i = 0; i < order; i++)
                         {
-                            value += ((DenseMatrix) MatrixEv).Values[(i*order) + j]*tmp[i];
+                            value += ((DenseMatrix) EigenVectors).Values[(i*order) + j]*tmp[i];
                         }
 
                         result.At(j, k, value);
@@ -911,21 +911,21 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
             // Ax=b where A is an m x m matrix
             // Check that b is a column vector with m entries
-            if (VectorEv.Count != input.Count)
+            if (EigenValues.Count != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (VectorEv.Count != result.Count)
+            if (EigenValues.Count != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(VectorEv, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(EigenValues, result);
             }
 
             if (IsSymmetric)
             {
                 // Symmetric case -> x = V * inv(λ) * VH * b;
-                var order = VectorEv.Count;
+                var order = EigenValues.Count;
                 var tmp = new Complex[order];
                 Complex value;
 
@@ -936,10 +936,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                     {
                         for (var i = 0; i < order; i++)
                         {
-                            value += ((DenseMatrix) MatrixEv).Values[(j*order) + i].Conjugate()*input[i];
+                            value += ((DenseMatrix) EigenVectors).Values[(j*order) + i].Conjugate()*input[i];
                         }
 
-                        value /= VectorEv[j].Real;
+                        value /= EigenValues[j].Real;
                     }
 
                     tmp[j] = value;
@@ -950,7 +950,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                     value = 0;
                     for (var i = 0; i < order; i++)
                     {
-                        value += ((DenseMatrix) MatrixEv).Values[(i*order) + j]*tmp[i];
+                        value += ((DenseMatrix) EigenVectors).Values[(i*order) + j]*tmp[i];
                     }
 
                     result[j] = value;

src/Numerics/LinearAlgebra/Complex/Factorization/DenseGramSchmidt.cs

@@ -76,9 +76,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 throw Matrix.DimensionsDontMatch<ArgumentException>(matrix);
             }
 
-            MatrixQ = matrix.Clone();
+            Q = matrix.Clone();
             MatrixR = matrix.CreateMatrix(matrix.ColumnCount, matrix.ColumnCount);
-            Factorize(((DenseMatrix)MatrixQ).Values, MatrixQ.RowCount, MatrixQ.ColumnCount, ((DenseMatrix)MatrixR).Values);
+            Factorize(((DenseMatrix)Q).Values, Q.RowCount, Q.ColumnCount, ((DenseMatrix)MatrixR).Values);
         }
 
         /// <summary>
@@ -156,13 +156,13 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixQ.RowCount != input.RowCount)
+            if (Q.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (MatrixQ.ColumnCount != result.RowCount)
+            if (Q.ColumnCount != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
@@ -179,7 +179,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 throw new NotSupportedException("Can only do GramSchmidt factorization for dense matrices at the moment.");
             }
 
-            _provider.QRSolveFactored(((DenseMatrix)MatrixQ).Values, ((DenseMatrix)MatrixR).Values, MatrixQ.RowCount, MatrixR.ColumnCount, null, dinput.Values, input.ColumnCount, dresult.Values, QRMethod.Thin);
+            _provider.QRSolveFactored(((DenseMatrix)Q).Values, ((DenseMatrix)MatrixR).Values, Q.RowCount, MatrixR.ColumnCount, null, dinput.Values, input.ColumnCount, dresult.Values, QRMethod.Thin);
         }
 
         /// <summary>
@@ -201,15 +201,15 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixQ.RowCount != input.Count)
+            if (Q.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (MatrixQ.ColumnCount != result.Count)
+            if (Q.ColumnCount != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(MatrixQ, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(Q, result);
             }
 
             var dinput = input as DenseVector;
@@ -224,7 +224,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 throw new NotSupportedException("Can only do GramSchmidt factorization for dense vectors at the moment.");
             }
 
-            _provider.QRSolveFactored(((DenseMatrix)MatrixQ).Values, ((DenseMatrix)MatrixR).Values, MatrixQ.RowCount, MatrixR.ColumnCount, null, dinput.Values, 1, dresult.Values, QRMethod.Thin);
+            _provider.QRSolveFactored(((DenseMatrix)Q).Values, ((DenseMatrix)MatrixR).Values, Q.RowCount, MatrixR.ColumnCount, null, dinput.Values, 1, dresult.Values, QRMethod.Thin);
         }
     }
 }

src/Numerics/LinearAlgebra/Complex/Factorization/DenseQR.cs

@@ -87,15 +87,15 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             if (method == QRMethod.Full)
             {
                 MatrixR = matrix.Clone();
-                MatrixQ = new DenseMatrix(matrix.RowCount);
+                Q = new DenseMatrix(matrix.RowCount);
                 Control.LinearAlgebraProvider.QRFactor(((DenseMatrix)MatrixR).Values, matrix.RowCount, matrix.ColumnCount,
-                                                       ((DenseMatrix)MatrixQ).Values, Tau);
+                                                       ((DenseMatrix)Q).Values, Tau);
             }
             else
             {
-                MatrixQ = matrix.Clone();
+                Q = matrix.Clone();
                 MatrixR = new DenseMatrix(matrix.ColumnCount);
-                Control.LinearAlgebraProvider.ThinQRFactor(((DenseMatrix)MatrixQ).Values, matrix.RowCount, matrix.ColumnCount,
+                Control.LinearAlgebraProvider.ThinQRFactor(((DenseMatrix)Q).Values, matrix.RowCount, matrix.ColumnCount,
                                                        ((DenseMatrix)MatrixR).Values, Tau);
             }
         }
@@ -125,7 +125,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixQ.RowCount != input.RowCount)
+            if (Q.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
@@ -148,7 +148,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 throw new NotSupportedException("Can only do QR factorization for dense matrices at the moment.");
             }
 
-            Control.LinearAlgebraProvider.QRSolveFactored(((DenseMatrix)MatrixQ).Values, ((DenseMatrix)MatrixR).Values, MatrixQ.RowCount, MatrixR.ColumnCount, Tau, dinput.Values, input.ColumnCount, dresult.Values, QrMethod);
+            Control.LinearAlgebraProvider.QRSolveFactored(((DenseMatrix)Q).Values, ((DenseMatrix)MatrixR).Values, Q.RowCount, MatrixR.ColumnCount, Tau, dinput.Values, input.ColumnCount, dresult.Values, QrMethod);
         }
 
         /// <summary>
@@ -170,7 +170,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixQ.RowCount != input.Count)
+            if (Q.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
@@ -193,7 +193,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 throw new NotSupportedException("Can only do QR factorization for dense vectors at the moment.");
             }
 
-            Control.LinearAlgebraProvider.QRSolveFactored(((DenseMatrix)MatrixQ).Values, ((DenseMatrix)MatrixR).Values, MatrixQ.RowCount, MatrixR.ColumnCount, Tau, dinput.Values, 1, dresult.Values, QrMethod);
+            Control.LinearAlgebraProvider.QRSolveFactored(((DenseMatrix)Q).Values, ((DenseMatrix)MatrixR).Values, Q.RowCount, MatrixR.ColumnCount, Tau, dinput.Values, 1, dresult.Values, QrMethod);
         }
     }
 }

src/Numerics/LinearAlgebra/Complex/Factorization/DenseSvd.cs

@@ -73,10 +73,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
             ComputeVectors = computeVectors;
             var nm = Math.Min(matrix.RowCount, matrix.ColumnCount);
-            VectorS = new DenseVector(nm);
-            MatrixU = new DenseMatrix(matrix.RowCount);
-            MatrixVT = new DenseMatrix(matrix.ColumnCount);
-            Control.LinearAlgebraProvider.SingularValueDecomposition(computeVectors, ((DenseMatrix)matrix.Clone()).Values, matrix.RowCount, matrix.ColumnCount, ((DenseVector)VectorS).Values, ((DenseMatrix)MatrixU).Values, ((DenseMatrix)MatrixVT).Values);
+            S = new DenseVector(nm);
+            U = new DenseMatrix(matrix.RowCount);
+            VT = new DenseMatrix(matrix.ColumnCount);
+            Control.LinearAlgebraProvider.SingularValueDecomposition(computeVectors, ((DenseMatrix)matrix.Clone()).Values, matrix.RowCount, matrix.ColumnCount, ((DenseVector)S).Values, ((DenseMatrix)U).Values, ((DenseMatrix)VT).Values);
         }
 
         /// <summary>
@@ -109,13 +109,13 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixU.RowCount != input.RowCount)
+            if (U.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (MatrixVT.ColumnCount != result.RowCount)
+            if (VT.ColumnCount != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
@@ -132,7 +132,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 throw new NotSupportedException("Can only do SVD factorization for dense matrices at the moment.");
             }
 
-            Control.LinearAlgebraProvider.SvdSolveFactored(MatrixU.RowCount, MatrixVT.ColumnCount, ((DenseVector)VectorS).Values, ((DenseMatrix)MatrixU).Values, ((DenseMatrix)MatrixVT).Values, dinput.Values, input.ColumnCount, dresult.Values);
+            Control.LinearAlgebraProvider.SvdSolveFactored(U.RowCount, VT.ColumnCount, ((DenseVector)S).Values, ((DenseMatrix)U).Values, ((DenseMatrix)VT).Values, dinput.Values, input.ColumnCount, dresult.Values);
         }
 
         /// <summary>
@@ -159,15 +159,15 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixU.RowCount != input.Count)
+            if (U.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (MatrixVT.ColumnCount != result.Count)
+            if (VT.ColumnCount != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(MatrixVT, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(VT, result);
             }
 
             var dinput = input as DenseVector;
@@ -182,7 +182,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 throw new NotSupportedException("Can only do SVD factorization for dense vectors at the moment.");
             }
 
-            Control.LinearAlgebraProvider.SvdSolveFactored(MatrixU.RowCount, MatrixVT.ColumnCount, ((DenseVector)VectorS).Values, ((DenseMatrix)MatrixU).Values, ((DenseMatrix)MatrixVT).Values, dinput.Values, 1, dresult.Values);
+            Control.LinearAlgebraProvider.SvdSolveFactored(U.RowCount, VT.ColumnCount, ((DenseVector)S).Values, ((DenseMatrix)U).Values, ((DenseMatrix)VT).Values, dinput.Values, 1, dresult.Values);
         }
     }
 }

src/Numerics/LinearAlgebra/Complex/Factorization/Evd.cs

@@ -59,11 +59,11 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             get
             {
                 var det = Complex.One;
-                for (var i = 0; i < VectorEv.Count; i++)
+                for (var i = 0; i < EigenValues.Count; i++)
                 {
-                    det *= VectorEv[i];
+                    det *= EigenValues[i];
 
-                    if (VectorEv[i].AlmostEqual(Complex.Zero))
+                    if (EigenValues[i].AlmostEqual(Complex.Zero))
                     {
                         return 0;
                     }
@@ -82,9 +82,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             get
             {
                 var rank = 0;
-                for (var i = 0; i < VectorEv.Count; i++)
+                for (var i = 0; i < EigenValues.Count; i++)
                 {
-                    if (VectorEv[i].AlmostEqual(Complex.Zero))
+                    if (EigenValues[i].AlmostEqual(Complex.Zero))
                     {
                         continue;
                     }
@@ -104,9 +104,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
         {
             get
             {
-                for (var i = 0; i < VectorEv.Count; i++)
+                for (var i = 0; i < EigenValues.Count; i++)
                 {
-                    if (VectorEv[i].AlmostEqual(Complex.Zero))
+                    if (EigenValues[i].AlmostEqual(Complex.Zero))
                     {
                         return false;
                     }

src/Numerics/LinearAlgebra/Complex/Factorization/Svd.cs

@@ -66,7 +66,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
         {
             get
             {
-                return VectorS.Count(t => !t.Magnitude.AlmostEqual(0.0));
+                return S.Count(t => !t.Magnitude.AlmostEqual(0.0));
             }
         }
 
@@ -78,7 +78,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
         {
             get
             {
-                return VectorS[0].Magnitude;
+                return S[0].Magnitude;
             }
         }
 
@@ -90,8 +90,8 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
         {
             get
             {
-                var tmp = Math.Min(MatrixU.RowCount, MatrixVT.ColumnCount) - 1;
-                return VectorS[0].Magnitude / VectorS[tmp].Magnitude;
+                var tmp = Math.Min(U.RowCount, VT.ColumnCount) - 1;
+                return S[0].Magnitude / S[tmp].Magnitude;
             }
         }
 
@@ -102,13 +102,13 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
         {
             get
             {
-                if (MatrixU.RowCount != MatrixVT.ColumnCount)
+                if (U.RowCount != VT.ColumnCount)
                 {
                     throw new ArgumentException(Resources.ArgumentMatrixSquare);
                 }
 
                 var det = Complex.One;
-                foreach (var value in VectorS)
+                foreach (var value in S)
                 {
                     det *= value;
                     if (value.Magnitude.AlmostEqual(0.0))

src/Numerics/LinearAlgebra/Complex/Factorization/UserCholesky.cs

@@ -73,40 +73,40 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             }
 
             // Create a new matrix for the Cholesky factor, then perform factorization (while overwriting).
-            CholeskyFactor = matrix.Clone();
-            var tmpColumn = new Complex[CholeskyFactor.RowCount];
+            Factor = matrix.Clone();
+            var tmpColumn = new Complex[Factor.RowCount];
 
             // Main loop - along the diagonal
-            for (var ij = 0; ij < CholeskyFactor.RowCount; ij++)
+            for (var ij = 0; ij < Factor.RowCount; ij++)
             {
                 // "Pivot" element
-                var tmpVal = CholeskyFactor.At(ij, ij);
+                var tmpVal = Factor.At(ij, ij);
 
                 if (tmpVal.Real > 0.0)
                 {
                     tmpVal = tmpVal.SquareRoot();
-                    CholeskyFactor.At(ij, ij, tmpVal);
+                    Factor.At(ij, ij, tmpVal);
                     tmpColumn[ij] = tmpVal;
 
                     // Calculate multipliers and copy to local column
                     // Current column, below the diagonal
-                    for (var i = ij + 1; i < CholeskyFactor.RowCount; i++)
+                    for (var i = ij + 1; i < Factor.RowCount; i++)
                     {
-                        CholeskyFactor.At(i, ij, CholeskyFactor.At(i, ij) / tmpVal);
-                        tmpColumn[i] = CholeskyFactor.At(i, ij);
+                        Factor.At(i, ij, Factor.At(i, ij) / tmpVal);
+                        tmpColumn[i] = Factor.At(i, ij);
                     }
 
                     // Remaining columns, below the diagonal
-                    DoCholeskyStep(CholeskyFactor, CholeskyFactor.RowCount, ij + 1, CholeskyFactor.RowCount, tmpColumn, Control.NumberOfParallelWorkerThreads);
+                    DoCholeskyStep(Factor, Factor.RowCount, ij + 1, Factor.RowCount, tmpColumn, Control.NumberOfParallelWorkerThreads);
                 }
                 else
                 {
                     throw new ArgumentException(Resources.ArgumentMatrixPositiveDefinite);
                 }
 
-                for (var i = ij + 1; i < CholeskyFactor.RowCount; i++)
+                for (var i = ij + 1; i < Factor.RowCount; i++)
                 {
-                    CholeskyFactor.At(ij, i, Complex.Zero);
+                    Factor.At(ij, i, Complex.Zero);
                 }
             }
         }
@@ -174,13 +174,13 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
-            if (input.RowCount != CholeskyFactor.RowCount)
+            if (input.RowCount != Factor.RowCount)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(input, CholeskyFactor);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(input, Factor);
             }
 
             input.CopyTo(result);
-            var order = CholeskyFactor.RowCount;
+            var order = Factor.RowCount;
 
             for (var c = 0; c < result.ColumnCount; c++)
             {
@@ -191,10 +191,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                     sum = result.At(i, c);
                     for (var k = i - 1; k >= 0; k--)
                     {
-                        sum -= CholeskyFactor.At(i, k) * result.At(k, c);
+                        sum -= Factor.At(i, k) * result.At(k, c);
                     }
 
-                    result.At(i, c, sum / CholeskyFactor.At(i, i));
+                    result.At(i, c, sum / Factor.At(i, i));
                 }
 
                 // Solve L'*X = Y;
@@ -203,10 +203,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                     sum = result.At(i, c);
                     for (var k = i + 1; k < order; k++)
                     {
-                        sum -= CholeskyFactor.At(k, i).Conjugate() * result.At(k, c);
+                        sum -= Factor.At(k, i).Conjugate() * result.At(k, c);
                     }
 
-                    result.At(i, c, sum / CholeskyFactor.At(i, i));
+                    result.At(i, c, sum / Factor.At(i, i));
                 }
             }
         }
@@ -235,13 +235,13 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
-            if (input.Count != CholeskyFactor.RowCount)
+            if (input.Count != Factor.RowCount)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(input, CholeskyFactor);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(input, Factor);
             }
 
             input.CopyTo(result);
-            var order = CholeskyFactor.RowCount;
+            var order = Factor.RowCount;
 
             // Solve L*Y = B;
             Complex sum;
@@ -250,10 +250,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 sum = result[i];
                 for (var k = i - 1; k >= 0; k--)
                 {
-                    sum -= CholeskyFactor.At(i, k) * result[k];
+                    sum -= Factor.At(i, k) * result[k];
                 }
 
-                result[i] = sum / CholeskyFactor.At(i, i);
+                result[i] = sum / Factor.At(i, i);
             }
 
             // Solve L'*X = Y;
@@ -262,10 +262,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 sum = result[i];
                 for (var k = i + 1; k < order; k++)
                 {
-                    sum -= CholeskyFactor.At(k, i).Conjugate() * result[k];
+                    sum -= Factor.At(k, i).Conjugate() * result[k];
                 }
 
-                result[i] = sum / CholeskyFactor.At(i, i);
+                result[i] = sum / Factor.At(i, i);
             }
         }
     }

src/Numerics/LinearAlgebra/Complex/Factorization/UserEvd.cs

@@ -79,9 +79,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             var order = matrix.RowCount;
 
             // Initialize matricies for eigenvalues and eigenvectors
-            MatrixEv = DenseMatrix.Identity(order);
-            MatrixD = matrix.CreateMatrix(order, order);
-            VectorEv = new DenseVector(order);
+            EigenVectors = DenseMatrix.Identity(order);
+            D = matrix.CreateMatrix(order, order);
+            EigenValues = new DenseVector(order);
            
             IsSymmetric = true;
 
@@ -106,7 +106,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
                 for (var i = 0; i < order; i++)
                 {
-                    VectorEv[i] = new Complex(d[i], e[i]);
+                    EigenValues[i] = new Complex(d[i], e[i]);
                 }
             }
             else
@@ -116,7 +116,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 NonsymmetricReduceHessenberToRealSchur(matrixH, order);
             }
 
-            MatrixD.SetDiagonal(VectorEv);
+            D.SetDiagonal(EigenValues);
         }
 
         /// <summary>
@@ -337,9 +337,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                             // Accumulate transformation.
                             for (var k = 0; k < order; k++)
                             {
-                                h = MatrixEv.At(k, i + 1).Real;
-                                MatrixEv.At(k, i + 1, (s * MatrixEv.At(k, i).Real) + (c * h));
-                                MatrixEv.At(k, i, (c * MatrixEv.At(k, i).Real) - (s * h));
+                                h = EigenVectors.At(k, i + 1).Real;
+                                EigenVectors.At(k, i + 1, (s * EigenVectors.At(k, i).Real) + (c * h));
+                                EigenVectors.At(k, i, (c * EigenVectors.At(k, i).Real) - (s * h));
                             }
                         }
 
@@ -381,9 +381,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                     d[i] = p;
                     for (var j = 0; j < order; j++)
                     {
-                        p = MatrixEv.At(j, i).Real;
-                        MatrixEv.At(j, i, MatrixEv.At(j, k));
-                        MatrixEv.At(j, k, p);
+                        p = EigenVectors.At(j, i).Real;
+                        EigenVectors.At(j, i, EigenVectors.At(j, k));
+                        EigenVectors.At(j, k, p);
                     }
                 }
             }
@@ -405,7 +405,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             {
                 for (var j = 0; j < order; j++)
                 {
-                    MatrixEv.At(i, j, MatrixEv.At(i, j).Real * tau[i].Conjugate());
+                    EigenVectors.At(i, j, EigenVectors.At(i, j).Real * tau[i].Conjugate());
                 }
             }
 
@@ -420,14 +420,14 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                         var s = Complex.Zero;
                         for (var k = 0; k < i; k++)
                         {
-                            s += MatrixEv.At(k, j) * matrixA[i, k];
+                            s += EigenVectors.At(k, j) * matrixA[i, k];
                         }
 
                         s = (s / h) / h;
 
                         for (var k = 0; k < i; k++)
                         {
-                            MatrixEv.At(k, j, MatrixEv.At(k, j) - s * matrixA[i, k].Conjugate());
+                            EigenVectors.At(k, j, EigenVectors.At(k, j) - s * matrixA[i, k].Conjugate());
                         }
                     }
                 }
@@ -521,7 +521,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             {
                 for (var j = 0; j < order; j++)
                 {
-                    MatrixEv.At(i, j, i == j ? Complex.One : Complex.Zero);
+                    EigenVectors.At(i, j, i == j ? Complex.One : Complex.Zero);
                 }
             }
 
@@ -541,14 +541,14 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                         var g = Complex.Zero;
                         for (var i = m; i < order; i++)
                         {
-                            g += ort[i].Conjugate() * MatrixEv.At(i, j);
+                            g += ort[i].Conjugate() * EigenVectors.At(i, j);
                         }
 
                         // Double division avoids possible underflow
                         g /= norm;
                         for (var i = m; i < order; i++)
                         {
-                            MatrixEv.At(i, j, MatrixEv.At(i, j) + g * ort[i]);
+                            EigenVectors.At(i, j, EigenVectors.At(i, j) + g * ort[i]);
                         }
                     }
                 }
@@ -573,7 +573,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
                     for (var j = 0; j < order; j++)
                     {
-                        MatrixEv.At(j, i, MatrixEv.At(j, i) * y);
+                        EigenVectors.At(j, i, EigenVectors.At(j, i) * y);
                     }
                 }
             }
@@ -619,7 +619,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 if (l == n)
                 {
                     matrixH[n, n] += exshift;
-                    VectorEv[n] = matrixH[n, n];
+                    EigenValues[n] = matrixH[n, n];
                     n--;
                     iter = 0;
                 }
@@ -665,7 +665,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                         s = matrixH[i, i - 1].Real;
                         norm = SpecialFunctions.Hypotenuse(matrixH[i - 1, i - 1].Magnitude, s.Real);
                         x = matrixH[i - 1, i - 1] / norm;
-                        VectorEv[i - 1] = x;
+                        EigenValues[i - 1] = x;
                         matrixH[i - 1, i - 1] = norm;
                         matrixH[i, i - 1] = new Complex(0.0, s.Real / norm);
 
@@ -693,7 +693,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                     // Inverse operation (columns).
                     for (var j = l + 1; j <= n; j++)
                     {
-                        x = VectorEv[j - 1];
+                        x = EigenValues[j - 1];
                         for (var i = 0; i <= j; i++)
                         {
                             z = matrixH[i, j];
@@ -713,10 +713,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
                         for (var i = 0; i < order; i++)
                         {
-                            y = MatrixEv.At(i, j - 1);
-                            z = MatrixEv.At(i, j);
-                            MatrixEv.At(i, j - 1, (x * y) + (matrixH[j, j - 1].Imaginary * z));
-                            MatrixEv.At(i, j, (x.Conjugate() * z) - (matrixH[j, j - 1].Imaginary * y));
+                            y = EigenVectors.At(i, j - 1);
+                            z = EigenVectors.At(i, j);
+                            EigenVectors.At(i, j - 1, (x * y) + (matrixH[j, j - 1].Imaginary * z));
+                            EigenVectors.At(i, j, (x.Conjugate() * z) - (matrixH[j, j - 1].Imaginary * y));
                         }
                     }
 
@@ -729,7 +729,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
                         for (var i = 0; i < order; i++)
                         {
-                            MatrixEv.At(i, n, MatrixEv.At(i, n) * s);
+                            EigenVectors.At(i, n, EigenVectors.At(i, n) * s);
                         }
                     }
                 }
@@ -758,7 +758,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
             for (n = order - 1; n > 0; n--)
             {
-                x = VectorEv[n];
+                x = EigenValues[n];
                 matrixH[n, n] = 1.0;
 
                 for (var i = n - 1; i >= 0; i--)
@@ -769,7 +769,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                         z += matrixH[i, j] * matrixH[j, n];
                     }
 
-                    y = x - VectorEv[i];
+                    y = x - EigenValues[i];
                     if (y.Real == 0.0 && y.Imaginary == 0.0)
                     {
                         y = eps * norm;
@@ -797,10 +797,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                     z = Complex.Zero;
                     for (var k = 0; k <= j; k++)
                     {
-                        z += MatrixEv.At(i, k) * matrixH[k, j];
+                        z += EigenVectors.At(i, k) * matrixH[k, j];
                     }
 
-                    MatrixEv.At(i, j, z);
+                    EigenVectors.At(i, j, z);
                 }
             }
         }
@@ -830,20 +830,20 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (VectorEv.Count != input.RowCount)
+            if (EigenValues.Count != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (VectorEv.Count != result.RowCount)
+            if (EigenValues.Count != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
             if (IsSymmetric)
             {
-                var order = VectorEv.Count;
+                var order = EigenValues.Count;
                 var tmp = new Complex[order];
 
                 for (var k = 0; k < order; k++)
@@ -855,10 +855,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                         {
                             for (var i = 0; i < order; i++)
                             {
-                                value += MatrixEv.At(i, j).Conjugate() * input.At(i, k);
+                                value += EigenVectors.At(i, j).Conjugate() * input.At(i, k);
                             }
 
-                            value /= VectorEv[j].Real;
+                            value /= EigenValues[j].Real;
                         }
 
                         tmp[j] = value;
@@ -869,7 +869,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                         Complex value = 0.0;
                         for (var i = 0; i < order; i++)
                         {
-                            value += MatrixEv.At(j, i) * tmp[i];
+                            value += EigenVectors.At(j, i) * tmp[i];
                         }
 
                         result.At(j, k, value);
@@ -901,21 +901,21 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
             // Ax=b where A is an m x m matrix
             // Check that b is a column vector with m entries
-            if (VectorEv.Count != input.Count)
+            if (EigenValues.Count != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (VectorEv.Count != result.Count)
+            if (EigenValues.Count != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(VectorEv, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(EigenValues, result);
             }
 
             if (IsSymmetric)
             {
                 // Symmetric case -> x = V * inv(λ) * VH * b;
-                var order = VectorEv.Count;
+                var order = EigenValues.Count;
                 var tmp = new Complex[order];
                 Complex value;
 
@@ -926,10 +926,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                     {
                         for (var i = 0; i < order; i++)
                         {
-                            value += MatrixEv.At(i, j).Conjugate() * input[i];
+                            value += EigenVectors.At(i, j).Conjugate() * input[i];
                         }
 
-                        value /= VectorEv[j].Real;
+                        value /= EigenValues[j].Real;
                     }
 
                     tmp[j] = value;
@@ -940,7 +940,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                     value = 0;
                     for (int i = 0; i < order; i++)
                     {
-                        value += MatrixEv.At(j, i) * tmp[i];
+                        value += EigenVectors.At(j, i) * tmp[i];
                     }
 
                     result[j] = value;

src/Numerics/LinearAlgebra/Complex/Factorization/UserGramSchmidt.cs

@@ -69,36 +69,36 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 throw Matrix.DimensionsDontMatch<ArgumentException>(matrix);
             }
 
-            MatrixQ = matrix.Clone();
+            Q = matrix.Clone();
             MatrixR = matrix.CreateMatrix(matrix.ColumnCount, matrix.ColumnCount);
 
-            for (var k = 0; k < MatrixQ.ColumnCount; k++)
+            for (var k = 0; k < Q.ColumnCount; k++)
             {
-                var norm = MatrixQ.Column(k).L2Norm();
+                var norm = Q.Column(k).L2Norm();
                 if (norm == 0.0)
                 {
                     throw new ArgumentException(Resources.ArgumentMatrixNotRankDeficient);
                 }
 
                 MatrixR.At(k, k, norm);
-                for (var i = 0; i < MatrixQ.RowCount; i++)
+                for (var i = 0; i < Q.RowCount; i++)
                 {
-                    MatrixQ.At(i, k, MatrixQ.At(i, k) / norm);
+                    Q.At(i, k, Q.At(i, k) / norm);
                 }
 
-                for (var j = k + 1; j < MatrixQ.ColumnCount; j++)
+                for (var j = k + 1; j < Q.ColumnCount; j++)
                 {
                     var dot = Complex.Zero;
-                    for (int i = 0; i < MatrixQ.RowCount; i++)
+                    for (int i = 0; i < Q.RowCount; i++)
                     {
-                        dot += MatrixQ.Column(k)[i].Conjugate() * MatrixQ.Column(j)[i];
+                        dot += Q.Column(k)[i].Conjugate() * Q.Column(j)[i];
                     }
                     
                     MatrixR.At(k, j, dot);
-                    for (var i = 0; i < MatrixQ.RowCount; i++)
+                    for (var i = 0; i < Q.RowCount; i++)
                     {
-                        var value = MatrixQ.At(i, j) - (MatrixQ.At(i, k) * dot);
-                        MatrixQ.At(i, j, value);
+                        var value = Q.At(i, j) - (Q.At(i, k) * dot);
+                        Q.At(i, j, value);
                     }
                 }
             }
@@ -129,13 +129,13 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixQ.RowCount != input.RowCount)
+            if (Q.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (MatrixQ.ColumnCount != result.RowCount)
+            if (Q.ColumnCount != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
@@ -143,20 +143,20 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             var inputCopy = input.Clone();
             
             // Compute Y = transpose(Q)*B
-            var column = new Complex[MatrixQ.RowCount];
+            var column = new Complex[Q.RowCount];
             for (var j = 0; j < input.ColumnCount; j++)
             {
-                for (var k = 0; k < MatrixQ.RowCount; k++)
+                for (var k = 0; k < Q.RowCount; k++)
                 {
                     column[k] = inputCopy.At(k, j);
                 }
 
-                for (var i = 0; i < MatrixQ.ColumnCount; i++)
+                for (var i = 0; i < Q.ColumnCount; i++)
                 {
                     var s = Complex.Zero;
-                    for (var k = 0; k < MatrixQ.RowCount; k++)
+                    for (var k = 0; k < Q.RowCount; k++)
                     {
-                        s += MatrixQ.At(k, i).Conjugate() * column[k];
+                        s += Q.At(k, i).Conjugate() * column[k];
                     }
 
                     inputCopy.At(i, j, s);
@@ -164,7 +164,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             }
 
             // Solve R*X = Y;
-            for (var k = MatrixQ.ColumnCount - 1; k >= 0; k--)
+            for (var k = Q.ColumnCount - 1; k >= 0; k--)
             {
                 for (var j = 0; j < input.ColumnCount; j++)
                 {
@@ -208,39 +208,39 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixQ.RowCount != input.Count)
+            if (Q.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (MatrixQ.ColumnCount != result.Count)
+            if (Q.ColumnCount != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(MatrixQ, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(Q, result);
             }
 
             var inputCopy = input.Clone();
 
             // Compute Y = transpose(Q)*B
-            var column = new Complex[MatrixQ.RowCount];
-            for (var k = 0; k < MatrixQ.RowCount; k++)
+            var column = new Complex[Q.RowCount];
+            for (var k = 0; k < Q.RowCount; k++)
             {
                 column[k] = inputCopy[k];
             }
 
-            for (var i = 0; i < MatrixQ.ColumnCount; i++)
+            for (var i = 0; i < Q.ColumnCount; i++)
             {
                 var s = Complex.Zero;
-                for (var k = 0; k < MatrixQ.RowCount; k++)
+                for (var k = 0; k < Q.RowCount; k++)
                 {
-                    s += MatrixQ.At(k, i).Conjugate() * column[k];
+                    s += Q.At(k, i).Conjugate() * column[k];
                 }
 
                 inputCopy[i] = s;
             }
 
             // Solve R*X = Y;
-            for (var k = MatrixQ.ColumnCount - 1; k >= 0; k--)
+            for (var k = Q.ColumnCount - 1; k >= 0; k--)
             {
                 inputCopy[k] /= MatrixR.At(k, k);
                 for (var i = 0; i < k; i++)

src/Numerics/LinearAlgebra/Complex/Factorization/UserQR.cs

@@ -80,11 +80,11 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             if (method == QRMethod.Full)
             {
                 MatrixR = matrix.Clone();
-                MatrixQ = matrix.CreateMatrix(matrix.RowCount, matrix.RowCount);
+                Q = matrix.CreateMatrix(matrix.RowCount, matrix.RowCount);
 
                 for (var i = 0; i < matrix.RowCount; i++)
                 {
-                    MatrixQ.At(i, i, 1.0f);
+                    Q.At(i, i, 1.0f);
                 }
 
                 for (var i = 0; i < minmn; i++)
@@ -96,33 +96,33 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
                 for (var i = minmn - 1; i >= 0; i--)
                 {
-                    ComputeQR(u[i], MatrixQ, i, matrix.RowCount, i, matrix.RowCount,
+                    ComputeQR(u[i], Q, i, matrix.RowCount, i, matrix.RowCount,
                               Control.NumberOfParallelWorkerThreads);
                 }
             }
             else
             {
                 MatrixR = matrix.CreateMatrix(matrix.ColumnCount, matrix.ColumnCount);
-                MatrixQ = matrix.Clone();
+                Q = matrix.Clone();
 
                 for (var i = 0; i < minmn; i++)
                 {
-                    u[i] = GenerateColumn(MatrixQ, i, i);
-                    ComputeQR(u[i], MatrixQ, i, matrix.RowCount, i + 1, matrix.ColumnCount,
+                    u[i] = GenerateColumn(Q, i, i);
+                    ComputeQR(u[i], Q, i, matrix.RowCount, i + 1, matrix.ColumnCount,
                               Control.NumberOfParallelWorkerThreads);
                 }
 
-                MatrixR = MatrixQ.SubMatrix(0, matrix.ColumnCount, 0, matrix.ColumnCount);
-                MatrixQ.Clear();
+                MatrixR = Q.SubMatrix(0, matrix.ColumnCount, 0, matrix.ColumnCount);
+                Q.Clear();
 
                 for (var i = 0; i < matrix.ColumnCount; i++)
                 {
-                    MatrixQ.At(i, i, 1.0f);
+                    Q.At(i, i, 1.0f);
                 }
 
                 for (var i = minmn - 1; i >= 0; i--)
                 {
-                    ComputeQR(u[i], MatrixQ, i, matrix.RowCount, i, matrix.ColumnCount,
+                    ComputeQR(u[i], Q, i, matrix.RowCount, i, matrix.ColumnCount,
                               Control.NumberOfParallelWorkerThreads);
                 }
             }
@@ -277,7 +277,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                     var s = Complex.Zero;
                     for (var k = 0; k < MatrixR.RowCount; k++)
                     {
-                        s += MatrixQ.At(k, i).Conjugate() * column[k];
+                        s += Q.At(k, i).Conjugate() * column[k];
                     }
 
                     inputCopy.At(i, j, s);
@@ -354,7 +354,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 var s = Complex.Zero;
                 for (var k = 0; k < MatrixR.RowCount; k++)
                 {
-                    s += MatrixQ.At(k, i).Conjugate() * column[k];
+                    s += Q.At(k, i).Conjugate() * column[k];
                 }
 
                 inputCopy[i] = s;

src/Numerics/LinearAlgebra/Complex/Factorization/UserSvd.cs

@@ -75,9 +75,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             var nm = Math.Min(matrix.RowCount + 1, matrix.ColumnCount);
             var matrixCopy = matrix.Clone();
 
-            VectorS = matrixCopy.CreateVector(nm);
-            MatrixU = matrixCopy.CreateMatrix(matrixCopy.RowCount, matrixCopy.RowCount);
-            MatrixVT = matrixCopy.CreateMatrix(matrixCopy.ColumnCount, matrixCopy.ColumnCount);
+            S = matrixCopy.CreateVector(nm);
+            U = matrixCopy.CreateMatrix(matrixCopy.RowCount, matrixCopy.RowCount);
+            VT = matrixCopy.CreateMatrix(matrixCopy.ColumnCount, matrixCopy.ColumnCount);
 
             const int maxiter = 1000;
             var e = new Complex[matrixCopy.ColumnCount];
@@ -100,26 +100,26 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 if (l < nct)
                 {
                     // Compute the transformation for the l-th column and place the l-th diagonal in VectorS[l].
-                    VectorS[l] = Cnrm2Column(matrixCopy, matrixCopy.RowCount, l, l);
-                    if (VectorS[l].Magnitude != 0.0)
+                    S[l] = Cnrm2Column(matrixCopy, matrixCopy.RowCount, l, l);
+                    if (S[l].Magnitude != 0.0)
                     {
                         if (matrixCopy.At(l, l).Magnitude != 0.0)
                         {
-                            VectorS[l] = Csign(VectorS[l], matrixCopy.At(l, l));
+                            S[l] = Csign(S[l], matrixCopy.At(l, l));
                         }
 
-                        CscalColumn(matrixCopy, matrixCopy.RowCount, l, l, 1.0 / VectorS[l]);
+                        CscalColumn(matrixCopy, matrixCopy.RowCount, l, l, 1.0 / S[l]);
                         matrixCopy.At(l, l, (Complex.One + matrixCopy.At(l, l)));
                     }
 
-                    VectorS[l] = -VectorS[l];
+                    S[l] = -S[l];
                 }
 
                 for (j = lp1; j < matrixCopy.ColumnCount; j++)
                 {
                     if (l < nct)
                     {
-                        if (VectorS[l].Magnitude != 0.0)
+                        if (S[l].Magnitude != 0.0)
                         {
                             // Apply the transformation.
                             t = -Cdotc(matrixCopy, matrixCopy.RowCount, l, j, l) / matrixCopy.At(l, l);
@@ -143,7 +143,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                     // Place the transformation in u for subsequent back multiplication.
                     for (i = l; i < matrixCopy.RowCount; i++)
                     {
-                        MatrixU.At(i, l, matrixCopy.At(i, l));
+                        U.At(i, l, matrixCopy.At(i, l));
                     }
                 }
 
@@ -204,7 +204,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                     // Place the transformation in v for subsequent back multiplication.
                     for (i = lp1; i < matrixCopy.ColumnCount; i++)
                     {
-                        MatrixVT.At(i, l, e[i]);
+                        VT.At(i, l, e[i]);
                     }
                 }
             }
@@ -215,12 +215,12 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             var nrtp1 = nrt + 1;
             if (nct < matrixCopy.ColumnCount)
             {
-                VectorS[nctp1 - 1] = matrixCopy.At((nctp1 - 1), (nctp1 - 1));
+                S[nctp1 - 1] = matrixCopy.At((nctp1 - 1), (nctp1 - 1));
             }
 
             if (matrixCopy.RowCount < m)
             {
-                VectorS[m - 1] = Complex.Zero;
+                S[m - 1] = Complex.Zero;
             }
 
             if (nrtp1 < m)
@@ -237,43 +237,43 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 {
                     for (i = 0; i < matrixCopy.RowCount; i++)
                     {
-                        MatrixU.At(i, j, Complex.Zero);
+                        U.At(i, j, Complex.Zero);
                     }
 
-                    MatrixU.At(j, j, Complex.One);
+                    U.At(j, j, Complex.One);
                 }
 
                 for (l = nct - 1; l >= 0; l--)
                 {
-                    if (VectorS[l].Magnitude != 0.0)
+                    if (S[l].Magnitude != 0.0)
                     {
                         for (j = l + 1; j < ncu; j++)
                         {
-                            t = -Cdotc(MatrixU, matrixCopy.RowCount, l, j, l) / MatrixU.At(l, l);
+                            t = -Cdotc(U, matrixCopy.RowCount, l, j, l) / U.At(l, l);
                             if (t != Complex.Zero)
                             {
                                 for (var ii = l; ii < matrixCopy.RowCount; ii++)
                                 {
-                                    MatrixU.At(ii, j, MatrixU.At(ii, j) + (t * MatrixU.At(ii, l)));
+                                    U.At(ii, j, U.At(ii, j) + (t * U.At(ii, l)));
                                 }
                             }
                         }
 
-                        CscalColumn(MatrixU, matrixCopy.RowCount, l, l, -1.0);
-                        MatrixU.At(l, l, Complex.One + MatrixU.At(l, l));
+                        CscalColumn(U, matrixCopy.RowCount, l, l, -1.0);
+                        U.At(l, l, Complex.One + U.At(l, l));
                         for (i = 0; i < l; i++)
                         {
-                            MatrixU.At(i, l, Complex.Zero);
+                            U.At(i, l, Complex.Zero);
                         }
                     }
                     else
                     {
                         for (i = 0; i < matrixCopy.RowCount; i++)
                         {
-                            MatrixU.At(i, l, Complex.Zero);
+                            U.At(i, l, Complex.Zero);
                         }
 
-                        MatrixU.At(l, l, Complex.One);
+                        U.At(l, l, Complex.One);
                     }
                 }
             }
@@ -290,12 +290,12 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                         {
                             for (j = lp1; j < matrixCopy.ColumnCount; j++)
                             {
-                                t = -Cdotc(MatrixVT, matrixCopy.ColumnCount, l, j, lp1) / MatrixVT.At(lp1, l);
+                                t = -Cdotc(VT, matrixCopy.ColumnCount, l, j, lp1) / VT.At(lp1, l);
                                 if (t != Complex.Zero)
                                 {
                                     for (var ii = l; ii < matrixCopy.ColumnCount; ii++)
                                     {
-                                        MatrixVT.At(ii, j, MatrixVT.At(ii, j) + (t * MatrixVT.At(ii, l)));
+                                        VT.At(ii, j, VT.At(ii, j) + (t * VT.At(ii, l)));
                                     }
                                 }
                             }
@@ -304,10 +304,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
                     for (i = 0; i < matrixCopy.ColumnCount; i++)
                     {
-                        MatrixVT.At(i, l, Complex.Zero);
+                        VT.At(i, l, Complex.Zero);
                     }
 
-                    MatrixVT.At(l, l, Complex.One);
+                    VT.At(l, l, Complex.One);
                 }
             }
 
@@ -315,11 +315,11 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             for (i = 0; i < m; i++)
             {
                 Complex r;
-                if (VectorS[i].Magnitude != 0.0)
+                if (S[i].Magnitude != 0.0)
                 {
-                    t = VectorS[i].Magnitude;
-                    r = VectorS[i] / t;
-                    VectorS[i] = t;
+                    t = S[i].Magnitude;
+                    r = S[i] / t;
+                    S[i] = t;
                     if (i < m - 1)
                     {
                         e[i] = e[i] / r;
@@ -327,7 +327,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
                     if (ComputeVectors)
                     {
-                        CscalColumn(MatrixU, matrixCopy.RowCount, i, 0, r);
+                        CscalColumn(U, matrixCopy.RowCount, i, 0, r);
                     }
                 }
 
@@ -342,10 +342,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                     t = e[i].Magnitude;
                     r = t / e[i];
                     e[i] = t;
-                    VectorS[i + 1] = VectorS[i + 1] * r;
+                    S[i + 1] = S[i + 1] * r;
                     if (ComputeVectors)
                     {
-                        CscalColumn(MatrixVT, matrixCopy.ColumnCount, i + 1, 0, r);
+                        CscalColumn(VT, matrixCopy.ColumnCount, i + 1, 0, r);
                     }
                 }
             }
@@ -373,7 +373,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 double test;
                 for (l = m - 2; l >= 0; l--)
                 {
-                    test = VectorS[l].Magnitude + VectorS[l + 1].Magnitude;
+                    test = S[l].Magnitude + S[l + 1].Magnitude;
                     ztest = test + e[l].Magnitude;
                     if (ztest.AlmostEqualInDecimalPlaces(test, 15))
                     {
@@ -403,10 +403,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                             test = test + e[ls - 1].Magnitude;
                         }
 
-                        ztest = test + VectorS[ls].Magnitude;
+                        ztest = test + S[ls].Magnitude;
                         if (ztest.AlmostEqualInDecimalPlaces(test, 15))
                         {
-                            VectorS[ls] = Complex.Zero;
+                            S[ls] = Complex.Zero;
                             break;
                         }
                     }
@@ -443,9 +443,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                         for (var kk = l; kk < m - 1; kk++)
                         {
                             k = m - 2 - kk + l;
-                            t1 = VectorS[k].Real;
+                            t1 = S[k].Real;
                             Srotg(ref t1, ref f, out cs, out sn);
-                            VectorS[k] = t1;
+                            S[k] = t1;
                             if (k != l)
                             {
                                 f = -sn * e[k - 1].Real;
@@ -454,7 +454,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
                             if (ComputeVectors)
                             {
-                                Csrot(MatrixVT, matrixCopy.ColumnCount, k, m - 1, cs, sn);
+                                Csrot(VT, matrixCopy.ColumnCount, k, m - 1, cs, sn);
                             }
                         }
 
@@ -466,14 +466,14 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                         e[l - 1] = Complex.Zero;
                         for (k = l; k < m; k++)
                         {
-                            t1 = VectorS[k].Real;
+                            t1 = S[k].Real;
                             Srotg(ref t1, ref f, out cs, out sn);
-                            VectorS[k] = t1;
+                            S[k] = t1;
                             f = -sn * e[k].Real;
                             e[k] = cs * e[k];
                             if (ComputeVectors)
                             {
-                                Csrot(MatrixU, matrixCopy.RowCount, k, l - 1, cs, sn);
+                                Csrot(U, matrixCopy.RowCount, k, l - 1, cs, sn);
                             }
                         }
 
@@ -483,15 +483,15 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                     case 3:
                         // Calculate the shift.
                         var scale = 0.0;
-                        scale = Math.Max(scale, VectorS[m - 1].Magnitude);
-                        scale = Math.Max(scale, VectorS[m - 2].Magnitude);
+                        scale = Math.Max(scale, S[m - 1].Magnitude);
+                        scale = Math.Max(scale, S[m - 2].Magnitude);
                         scale = Math.Max(scale, e[m - 2].Magnitude);
-                        scale = Math.Max(scale, VectorS[l].Magnitude);
+                        scale = Math.Max(scale, S[l].Magnitude);
                         scale = Math.Max(scale, e[l].Magnitude);
-                        var sm = VectorS[m - 1].Real / scale;
-                        var smm1 = VectorS[m - 2].Real / scale;
+                        var sm = S[m - 1].Real / scale;
+                        var smm1 = S[m - 2].Real / scale;
                         var emm1 = e[m - 2].Real / scale;
-                        var sl = VectorS[l].Real / scale;
+                        var sl = S[l].Real / scale;
                         var el = e[l].Real / scale;
                         var b = (((smm1 + sm) * (smm1 - sm)) + (emm1 * emm1)) / 2.0;
                         var c = (sm * emm1) * (sm * emm1);
@@ -520,24 +520,24 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                                 e[k - 1] = f;
                             }
 
-                            f = (cs * VectorS[k].Real) + (sn * e[k].Real);
-                            e[k] = (cs * e[k]) - (sn * VectorS[k]);
-                            g = sn * VectorS[k + 1].Real;
-                            VectorS[k + 1] = cs * VectorS[k + 1];
+                            f = (cs * S[k].Real) + (sn * e[k].Real);
+                            e[k] = (cs * e[k]) - (sn * S[k]);
+                            g = sn * S[k + 1].Real;
+                            S[k + 1] = cs * S[k + 1];
                             if (ComputeVectors)
                             {
-                                Csrot(MatrixVT, matrixCopy.ColumnCount, k, k + 1, cs, sn);
+                                Csrot(VT, matrixCopy.ColumnCount, k, k + 1, cs, sn);
                             }
 
                             Srotg(ref f, ref g, out cs, out sn);
-                            VectorS[k] = f;
-                            f = (cs * e[k].Real) + (sn * VectorS[k + 1].Real);
-                            VectorS[k + 1] = (-sn * e[k]) + (cs * VectorS[k + 1]);
+                            S[k] = f;
+                            f = (cs * e[k].Real) + (sn * S[k + 1].Real);
+                            S[k + 1] = (-sn * e[k]) + (cs * S[k + 1]);
                             g = sn * e[k + 1].Real;
                             e[k + 1] = cs * e[k + 1];
                             if (ComputeVectors && k < matrixCopy.RowCount)
                             {
-                                Csrot(MatrixU, matrixCopy.RowCount, k, k + 1, cs, sn);
+                                Csrot(U, matrixCopy.RowCount, k, k + 1, cs, sn);
                             }
                         }
 
@@ -548,34 +548,34 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                     // Convergence.
                     case 4:
                         // Make the singular value  positive
-                        if (VectorS[l].Real < 0.0)
+                        if (S[l].Real < 0.0)
                         {
-                            VectorS[l] = -VectorS[l];
+                            S[l] = -S[l];
                             if (ComputeVectors)
                             {
-                                CscalColumn(MatrixVT, matrixCopy.ColumnCount, l, 0, -1.0);
+                                CscalColumn(VT, matrixCopy.ColumnCount, l, 0, -1.0);
                             }
                         }
 
                         // Order the singular value.
                         while (l != mn - 1)
                         {
-                            if (VectorS[l].Real >= VectorS[l + 1].Real)
+                            if (S[l].Real >= S[l + 1].Real)
                             {
                                 break;
                             }
 
-                            t = VectorS[l];
-                            VectorS[l] = VectorS[l + 1];
-                            VectorS[l + 1] = t;
+                            t = S[l];
+                            S[l] = S[l + 1];
+                            S[l + 1] = t;
                             if (ComputeVectors && l < matrixCopy.ColumnCount)
                             {
-                                Swap(MatrixVT, matrixCopy.ColumnCount, l, l + 1);
+                                Swap(VT, matrixCopy.ColumnCount, l, l + 1);
                             }
 
                             if (ComputeVectors && l < matrixCopy.RowCount)
                             {
-                                Swap(MatrixU, matrixCopy.RowCount, l, l + 1);
+                                Swap(U, matrixCopy.RowCount, l, l + 1);
                             }
 
                             l = l + 1;
@@ -589,7 +589,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
             if (ComputeVectors)
             {
-                MatrixVT = MatrixVT.ConjugateTranspose();
+                VT = VT.ConjugateTranspose();
             }
 
             // Adjust the size of s if rows < columns. We are using ported copy of linpack's svd code and it uses
@@ -601,10 +601,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
                 var tmp = matrixCopy.CreateVector(nm);
                 for (i = 0; i < nm; i++)
                 {
-                    tmp[i] = VectorS[i];
+                    tmp[i] = S[i];
                 }
 
-                VectorS = tmp;
+                S = tmp;
             }
         }
 
@@ -830,46 +830,46 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixU.RowCount != input.RowCount)
+            if (U.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (MatrixVT.ColumnCount != result.RowCount)
+            if (VT.ColumnCount != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
-            var mn = Math.Min(MatrixU.RowCount, MatrixVT.ColumnCount);
+            var mn = Math.Min(U.RowCount, VT.ColumnCount);
             var bn = input.ColumnCount;
 
-            var tmp = new Complex[MatrixVT.ColumnCount];
+            var tmp = new Complex[VT.ColumnCount];
 
             for (var k = 0; k < bn; k++)
             {
-                for (var j = 0; j < MatrixVT.ColumnCount; j++)
+                for (var j = 0; j < VT.ColumnCount; j++)
                 {
                     var value = Complex.Zero;
                     if (j < mn)
                     {
-                        for (var i = 0; i < MatrixU.RowCount; i++)
+                        for (var i = 0; i < U.RowCount; i++)
                         {
-                            value += MatrixU.At(i, j).Conjugate() * input.At(i, k);
+                            value += U.At(i, j).Conjugate() * input.At(i, k);
                         }
 
-                        value /= VectorS[j];
+                        value /= S[j];
                     }
 
                     tmp[j] = value;
                 }
 
-                for (var j = 0; j < MatrixVT.ColumnCount; j++)
+                for (var j = 0; j < VT.ColumnCount; j++)
                 {
                     var value = Complex.Zero;
-                    for (var i = 0; i < MatrixVT.ColumnCount; i++)
+                    for (var i = 0; i < VT.ColumnCount; i++)
                     {
-                        value += MatrixVT.At(i, j).Conjugate() * tmp[i];
+                        value += VT.At(i, j).Conjugate() * tmp[i];
                     }
 
                     result.At(j, k, value);
@@ -901,41 +901,41 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixU.RowCount != input.Count)
+            if (U.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (MatrixVT.ColumnCount != result.Count)
+            if (VT.ColumnCount != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(MatrixVT, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(VT, result);
             }
 
-            var mn = Math.Min(MatrixU.RowCount, MatrixVT.ColumnCount);
-            var tmp = new Complex[MatrixVT.ColumnCount];
-            for (var j = 0; j < MatrixVT.ColumnCount; j++)
+            var mn = Math.Min(U.RowCount, VT.ColumnCount);
+            var tmp = new Complex[VT.ColumnCount];
+            for (var j = 0; j < VT.ColumnCount; j++)
             {
                 var value = Complex.Zero;
                 if (j < mn)
                 {
-                    for (var i = 0; i < MatrixU.RowCount; i++)
+                    for (var i = 0; i < U.RowCount; i++)
                     {
-                        value += MatrixU.At(i, j).Conjugate() * input[i];
+                        value += U.At(i, j).Conjugate() * input[i];
                     }
 
-                    value /= VectorS[j];
+                    value /= S[j];
                 }
 
                 tmp[j] = value;
             }
 
-            for (var j = 0; j < MatrixVT.ColumnCount; j++)
+            for (var j = 0; j < VT.ColumnCount; j++)
             {
                 var value = Complex.Zero;
-                for (var i = 0; i < MatrixVT.ColumnCount; i++)
+                for (var i = 0; i < VT.ColumnCount; i++)
                 {
-                    value += MatrixVT.At(i, j).Conjugate() * tmp[i];
+                    value += VT.At(i, j).Conjugate() * tmp[i];
                 }
 
                 result[j] = value;

src/Numerics/LinearAlgebra/Complex32/Factorization/Cholesky.cs

@@ -53,9 +53,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             get
             {
                 var det = Complex32.One;
-                for (var j = 0; j < CholeskyFactor.RowCount; j++)
+                for (var j = 0; j < Factor.RowCount; j++)
                 {
-                    var d = CholeskyFactor.At(j, j);
+                    var d = Factor.At(j, j);
                     det *= d * d;
                 }
 
@@ -71,9 +71,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             get
             {
                 var det = Complex32.Zero;
-                for (var j = 0; j < CholeskyFactor.RowCount; j++)
+                for (var j = 0; j < Factor.RowCount; j++)
                 {
-                    det += 2.0f * CholeskyFactor.At(j, j).NaturalLogarithm();
+                    det += 2.0f * Factor.At(j, j).NaturalLogarithm();
                 }
 
                 return det;

src/Numerics/LinearAlgebra/Complex32/Factorization/DenseCholesky.cs

@@ -68,7 +68,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             // Create a new matrix for the Cholesky factor, then perform factorization (while overwriting).
             var factor = (DenseMatrix)matrix.Clone();
             Control.LinearAlgebraProvider.CholeskyFactor(factor.Values, factor.RowCount);
-            CholeskyFactor = factor;
+            Factor = factor;
         }
 
         /// <summary>
@@ -100,9 +100,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
-            if (input.RowCount != CholeskyFactor.RowCount)
+            if (input.RowCount != Factor.RowCount)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(input, CholeskyFactor);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(input, Factor);
             }
 
             var dinput = input as DenseMatrix;
@@ -121,7 +121,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             Array.Copy(dinput.Values, dresult.Values, dinput.Values.Length);
 
             // Cholesky solve by overwriting result.
-            var dfactor = (DenseMatrix)CholeskyFactor;
+            var dfactor = (DenseMatrix)Factor;
             Control.LinearAlgebraProvider.CholeskySolveFactored(dfactor.Values, dfactor.RowCount, dresult.Values, dresult.ColumnCount);
         }
 
@@ -149,9 +149,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
-            if (input.Count != CholeskyFactor.RowCount)
+            if (input.Count != Factor.RowCount)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(input, CholeskyFactor);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(input, Factor);
             }
 
             var dinput = input as DenseVector;
@@ -170,7 +170,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             Array.Copy(dinput.Values, dresult.Values, dinput.Values.Length);
 
             // Cholesky solve by overwriting result.
-            var dfactor = (DenseMatrix)CholeskyFactor;
+            var dfactor = (DenseMatrix)Factor;
             Control.LinearAlgebraProvider.CholeskySolveFactored(dfactor.Values, dfactor.RowCount, dresult.Values, 1);
         }
     }

src/Numerics/LinearAlgebra/Complex32/Factorization/DenseEvd.cs

@@ -72,9 +72,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             var order = matrix.RowCount;
 
             // Initialize matrices for eigenvalues and eigenvectors
-            MatrixEv = DenseMatrix.Identity(order);
-            MatrixD = matrix.CreateMatrix(order, order);
-            VectorEv = new Complex.DenseVector(order);
+            EigenVectors = DenseMatrix.Identity(order);
+            D = matrix.CreateMatrix(order, order);
+            EigenValues = new Complex.DenseVector(order);
 
             IsSymmetric = true;
 
@@ -86,8 +86,8 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 }
             }
 
-            Control.LinearAlgebraProvider.EigenDecomp(IsSymmetric, order, matrix.Values, ((DenseMatrix) MatrixEv).Values,
-                ((Complex.DenseVector) VectorEv).Values, ((DenseMatrix) MatrixD).Values);
+            Control.LinearAlgebraProvider.EigenDecomp(IsSymmetric, order, matrix.Values, ((DenseMatrix) EigenVectors).Values,
+                ((Complex.DenseVector)EigenValues).Values, ((DenseMatrix)D).Values);
         }
 
         /// <summary>
@@ -833,20 +833,20 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (VectorEv.Count != input.RowCount)
+            if (EigenValues.Count != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (VectorEv.Count != result.RowCount)
+            if (EigenValues.Count != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
             if (IsSymmetric)
             {
-                var order = VectorEv.Count;
+                var order = EigenValues.Count;
                 var tmp = new Numerics.Complex32[order];
 
                 for (var k = 0; k < order; k++)
@@ -858,10 +858,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                         {
                             for (var i = 0; i < order; i++)
                             {
-                                value += ((DenseMatrix) MatrixEv).Values[(j*order) + i].Conjugate()*input.At(i, k);
+                                value += ((DenseMatrix) EigenVectors).Values[(j*order) + i].Conjugate()*input.At(i, k);
                             }
 
-                            value /= (float) VectorEv[j].Real;
+                            value /= (float)EigenValues[j].Real;
                         }
 
                         tmp[j] = value;
@@ -872,7 +872,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                         Numerics.Complex32 value = 0.0f;
                         for (var i = 0; i < order; i++)
                         {
-                            value += ((DenseMatrix) MatrixEv).Values[(i*order) + j]*tmp[i];
+                            value += ((DenseMatrix) EigenVectors).Values[(i*order) + j]*tmp[i];
                         }
 
                         result.At(j, k, value);
@@ -904,13 +904,13 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
             // Ax=b where A is an m x m matrix
             // Check that b is a column vector with m entries
-            if (VectorEv.Count != input.Count)
+            if (EigenValues.Count != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (VectorEv.Count != result.Count)
+            if (EigenValues.Count != result.Count)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixDimensions);
             }
@@ -918,7 +918,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             if (IsSymmetric)
             {
                 // Symmetric case -> x = V * inv(λ) * VH * b;
-                var order = VectorEv.Count;
+                var order = EigenValues.Count;
                 var tmp = new Numerics.Complex32[order];
                 Numerics.Complex32 value;
 
@@ -929,10 +929,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                     {
                         for (var i = 0; i < order; i++)
                         {
-                            value += ((DenseMatrix) MatrixEv).Values[(j*order) + i].Conjugate()*input[i];
+                            value += ((DenseMatrix) EigenVectors).Values[(j*order) + i].Conjugate()*input[i];
                         }
 
-                        value /= (float) VectorEv[j].Real;
+                        value /= (float)EigenValues[j].Real;
                     }
 
                     tmp[j] = value;
@@ -943,7 +943,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                     value = 0;
                     for (var i = 0; i < order; i++)
                     {
-                        value += ((DenseMatrix) MatrixEv).Values[(i*order) + j]*tmp[i];
+                        value += ((DenseMatrix) EigenVectors).Values[(i*order) + j]*tmp[i];
                     }
 
                     result[j] = value;

src/Numerics/LinearAlgebra/Complex32/Factorization/DenseGramSchmidt.cs

@@ -71,9 +71,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 throw Matrix.DimensionsDontMatch<ArgumentException>(matrix);
             }
 
-            MatrixQ = matrix.Clone();
+            Q = matrix.Clone();
             MatrixR = matrix.CreateMatrix(matrix.ColumnCount, matrix.ColumnCount);
-            Factorize(((DenseMatrix)MatrixQ).Values, MatrixQ.RowCount, MatrixQ.ColumnCount, ((DenseMatrix)MatrixR).Values);
+            Factorize(((DenseMatrix)Q).Values, Q.RowCount, Q.ColumnCount, ((DenseMatrix)MatrixR).Values);
         }
 
         /// <summary>
@@ -151,13 +151,13 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixQ.RowCount != input.RowCount)
+            if (Q.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (MatrixQ.ColumnCount != result.RowCount)
+            if (Q.ColumnCount != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
@@ -174,7 +174,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 throw new NotSupportedException("Can only do GramSchmidt factorization for dense matrices at the moment.");
             }
 
-            _provider.QRSolveFactored(((DenseMatrix)MatrixQ).Values, ((DenseMatrix)MatrixR).Values, MatrixQ.RowCount, MatrixR.ColumnCount, null, dinput.Values, input.ColumnCount, dresult.Values, QRMethod.Thin);
+            _provider.QRSolveFactored(((DenseMatrix)Q).Values, ((DenseMatrix)MatrixR).Values, Q.RowCount, MatrixR.ColumnCount, null, dinput.Values, input.ColumnCount, dresult.Values, QRMethod.Thin);
         }
 
         /// <summary>
@@ -196,15 +196,15 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixQ.RowCount != input.Count)
+            if (Q.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (MatrixQ.ColumnCount != result.Count)
+            if (Q.ColumnCount != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(MatrixQ, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(Q, result);
             }
 
             var dinput = input as DenseVector;
@@ -219,7 +219,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 throw new NotSupportedException("Can only do GramSchmidt factorization for dense vectors at the moment.");
             }
 
-            _provider.QRSolveFactored(((DenseMatrix)MatrixQ).Values, ((DenseMatrix)MatrixR).Values, MatrixQ.RowCount, MatrixR.ColumnCount, null, dinput.Values, 1, dresult.Values, QRMethod.Thin);
+            _provider.QRSolveFactored(((DenseMatrix)Q).Values, ((DenseMatrix)MatrixR).Values, Q.RowCount, MatrixR.ColumnCount, null, dinput.Values, 1, dresult.Values, QRMethod.Thin);
         }
     }
 }

src/Numerics/LinearAlgebra/Complex32/Factorization/DenseQR.cs

@@ -82,15 +82,15 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             if (method == QRMethod.Full)
             {
                 MatrixR = matrix.Clone();
-                MatrixQ = new DenseMatrix(matrix.RowCount);
+                Q = new DenseMatrix(matrix.RowCount);
                 Control.LinearAlgebraProvider.QRFactor(((DenseMatrix)MatrixR).Values, matrix.RowCount, matrix.ColumnCount,
-                                                       ((DenseMatrix)MatrixQ).Values, Tau);
+                                                       ((DenseMatrix)Q).Values, Tau);
             }
             else
             {
-                MatrixQ = matrix.Clone();
+                Q = matrix.Clone();
                 MatrixR = new DenseMatrix(matrix.ColumnCount);
-                Control.LinearAlgebraProvider.ThinQRFactor(((DenseMatrix)MatrixQ).Values, matrix.RowCount, matrix.ColumnCount,
+                Control.LinearAlgebraProvider.ThinQRFactor(((DenseMatrix)Q).Values, matrix.RowCount, matrix.ColumnCount,
                                                        ((DenseMatrix)MatrixR).Values, Tau);
             }
         }
@@ -120,7 +120,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixQ.RowCount != input.RowCount)
+            if (Q.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
@@ -143,7 +143,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 throw new NotSupportedException("Can only do QR factorization for dense matrices at the moment.");
             }
 
-            Control.LinearAlgebraProvider.QRSolveFactored(((DenseMatrix)MatrixQ).Values, ((DenseMatrix)MatrixR).Values, MatrixQ.RowCount, MatrixR.ColumnCount, Tau, dinput.Values, input.ColumnCount, dresult.Values, QrMethod);
+            Control.LinearAlgebraProvider.QRSolveFactored(((DenseMatrix)Q).Values, ((DenseMatrix)MatrixR).Values, Q.RowCount, MatrixR.ColumnCount, Tau, dinput.Values, input.ColumnCount, dresult.Values, QrMethod);
         }
 
         /// <summary>
@@ -165,7 +165,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixQ.RowCount != input.Count)
+            if (Q.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
@@ -188,7 +188,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 throw new NotSupportedException("Can only do QR factorization for dense vectors at the moment.");
             }
 
-            Control.LinearAlgebraProvider.QRSolveFactored(((DenseMatrix)MatrixQ).Values, ((DenseMatrix)MatrixR).Values, MatrixQ.RowCount, MatrixR.ColumnCount, Tau, dinput.Values, 1, dresult.Values, QrMethod);
+            Control.LinearAlgebraProvider.QRSolveFactored(((DenseMatrix)Q).Values, ((DenseMatrix)MatrixR).Values, Q.RowCount, MatrixR.ColumnCount, Tau, dinput.Values, 1, dresult.Values, QrMethod);
         }
     }
 }

src/Numerics/LinearAlgebra/Complex32/Factorization/DenseSvd.cs

@@ -68,10 +68,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
             ComputeVectors = computeVectors;
             var nm = Math.Min(matrix.RowCount, matrix.ColumnCount);
-            VectorS = new DenseVector(nm);
-            MatrixU = new DenseMatrix(matrix.RowCount);
-            MatrixVT = new DenseMatrix(matrix.ColumnCount);
-            Control.LinearAlgebraProvider.SingularValueDecomposition(computeVectors, ((DenseMatrix)matrix.Clone()).Values, matrix.RowCount, matrix.ColumnCount, ((DenseVector)VectorS).Values, ((DenseMatrix)MatrixU).Values, ((DenseMatrix)MatrixVT).Values);
+            S = new DenseVector(nm);
+            U = new DenseMatrix(matrix.RowCount);
+            VT = new DenseMatrix(matrix.ColumnCount);
+            Control.LinearAlgebraProvider.SingularValueDecomposition(computeVectors, ((DenseMatrix)matrix.Clone()).Values, matrix.RowCount, matrix.ColumnCount, ((DenseVector)S).Values, ((DenseMatrix)U).Values, ((DenseMatrix)VT).Values);
         }
 
         /// <summary>
@@ -104,13 +104,13 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixU.RowCount != input.RowCount)
+            if (U.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (MatrixVT.ColumnCount != result.RowCount)
+            if (VT.ColumnCount != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
@@ -127,7 +127,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 throw new NotSupportedException("Can only do SVD factorization for dense matrices at the moment.");
             }
 
-            Control.LinearAlgebraProvider.SvdSolveFactored(MatrixU.RowCount, MatrixVT.ColumnCount, ((DenseVector)VectorS).Values, ((DenseMatrix)MatrixU).Values, ((DenseMatrix)MatrixVT).Values, dinput.Values, input.ColumnCount, dresult.Values);
+            Control.LinearAlgebraProvider.SvdSolveFactored(U.RowCount, VT.ColumnCount, ((DenseVector)S).Values, ((DenseMatrix)U).Values, ((DenseMatrix)VT).Values, dinput.Values, input.ColumnCount, dresult.Values);
         }
 
         /// <summary>
@@ -154,15 +154,15 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixU.RowCount != input.Count)
+            if (U.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (MatrixVT.ColumnCount != result.Count)
+            if (VT.ColumnCount != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(MatrixVT, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(VT, result);
             }
 
             var dinput = input as DenseVector;
@@ -177,7 +177,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 throw new NotSupportedException("Can only do SVD factorization for dense vectors at the moment.");
             }
 
-            Control.LinearAlgebraProvider.SvdSolveFactored(MatrixU.RowCount, MatrixVT.ColumnCount, ((DenseVector)VectorS).Values, ((DenseMatrix)MatrixU).Values, ((DenseMatrix)MatrixVT).Values, dinput.Values, 1, dresult.Values);
+            Control.LinearAlgebraProvider.SvdSolveFactored(U.RowCount, VT.ColumnCount, ((DenseVector)S).Values, ((DenseMatrix)U).Values, ((DenseMatrix)VT).Values, dinput.Values, 1, dresult.Values);
         }
     }
 }

src/Numerics/LinearAlgebra/Complex32/Factorization/Evd.cs

@@ -62,11 +62,11 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             get
             {
                 var det = Complex.One;
-                for (var i = 0; i < VectorEv.Count; i++)
+                for (var i = 0; i < EigenValues.Count; i++)
                 {
-                    det *= VectorEv[i];
+                    det *= EigenValues[i];
 
-                    if (((Complex32)VectorEv[i]).AlmostEqual(Complex32.Zero))
+                    if (((Complex32)EigenValues[i]).AlmostEqual(Complex32.Zero))
                     {
                         return 0;
                     }
@@ -85,9 +85,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             get
             {
                 var rank = 0;
-                for (var i = 0; i < VectorEv.Count; i++)
+                for (var i = 0; i < EigenValues.Count; i++)
                 {
-                    if (((Complex32)VectorEv[i]).AlmostEqual(Complex32.Zero))
+                    if (((Complex32)EigenValues[i]).AlmostEqual(Complex32.Zero))
                     {
                         continue;
                     }
@@ -107,9 +107,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
         {
             get
             {
-                for (var i = 0; i < VectorEv.Count; i++)
+                for (var i = 0; i < EigenValues.Count; i++)
                 {
-                    if (VectorEv[i].AlmostEqual(Complex.Zero))
+                    if (EigenValues[i].AlmostEqual(Complex.Zero))
                     {
                         return false;
                     }

src/Numerics/LinearAlgebra/Complex32/Factorization/Svd.cs

@@ -61,7 +61,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
         {
             get
             {
-                return VectorS.Count(t => !t.Magnitude.AlmostEqual(0.0f));
+                return S.Count(t => !t.Magnitude.AlmostEqual(0.0f));
             }
         }
 
@@ -73,7 +73,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
         {
             get
             {
-                return VectorS[0].Magnitude;
+                return S[0].Magnitude;
             }
         }
 
@@ -85,8 +85,8 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
         {
             get
             {
-                var tmp = Math.Min(MatrixU.RowCount, MatrixVT.ColumnCount) - 1;
-                return VectorS[0].Magnitude / VectorS[tmp].Magnitude;
+                var tmp = Math.Min(U.RowCount, VT.ColumnCount) - 1;
+                return S[0].Magnitude / S[tmp].Magnitude;
             }
         }
 
@@ -97,13 +97,13 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
         {
             get
             {
-                if (MatrixU.RowCount != MatrixVT.ColumnCount)
+                if (U.RowCount != VT.ColumnCount)
                 {
                     throw new ArgumentException(Resources.ArgumentMatrixSquare);
                 }
 
                 var det = Complex32.One;
-                foreach (var value in VectorS)
+                foreach (var value in S)
                 {
                     det *= value;
                     if (value.Magnitude.AlmostEqual(0.0f))

src/Numerics/LinearAlgebra/Complex32/Factorization/UserCholesky.cs

@@ -68,40 +68,40 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             }
 
             // Create a new matrix for the Cholesky factor, then perform factorization (while overwriting).
-            CholeskyFactor = matrix.Clone();
-            var tmpColumn = new Complex32[CholeskyFactor.RowCount];
+            Factor = matrix.Clone();
+            var tmpColumn = new Complex32[Factor.RowCount];
 
             // Main loop - along the diagonal
-            for (var ij = 0; ij < CholeskyFactor.RowCount; ij++)
+            for (var ij = 0; ij < Factor.RowCount; ij++)
             {
                 // "Pivot" element
-                var tmpVal = CholeskyFactor.At(ij, ij);
+                var tmpVal = Factor.At(ij, ij);
 
                 if (tmpVal.Real > 0.0)
                 {
                     tmpVal = tmpVal.SquareRoot();
-                    CholeskyFactor.At(ij, ij, tmpVal);
+                    Factor.At(ij, ij, tmpVal);
                     tmpColumn[ij] = tmpVal;
 
                     // Calculate multipliers and copy to local column
                     // Current column, below the diagonal
-                    for (var i = ij + 1; i < CholeskyFactor.RowCount; i++)
+                    for (var i = ij + 1; i < Factor.RowCount; i++)
                     {
-                        CholeskyFactor.At(i, ij, CholeskyFactor.At(i, ij) / tmpVal);
-                        tmpColumn[i] = CholeskyFactor.At(i, ij);
+                        Factor.At(i, ij, Factor.At(i, ij) / tmpVal);
+                        tmpColumn[i] = Factor.At(i, ij);
                     }
 
                     // Remaining columns, below the diagonal
-                    DoCholeskyStep(CholeskyFactor, CholeskyFactor.RowCount, ij + 1, CholeskyFactor.RowCount, tmpColumn, Control.NumberOfParallelWorkerThreads);
+                    DoCholeskyStep(Factor, Factor.RowCount, ij + 1, Factor.RowCount, tmpColumn, Control.NumberOfParallelWorkerThreads);
                 }
                 else
                 {
                     throw new ArgumentException(Resources.ArgumentMatrixPositiveDefinite);
                 }
 
-                for (var i = ij + 1; i < CholeskyFactor.RowCount; i++)
+                for (var i = ij + 1; i < Factor.RowCount; i++)
                 {
-                    CholeskyFactor.At(ij, i, Complex32.Zero);
+                    Factor.At(ij, i, Complex32.Zero);
                 }
             }
         }
@@ -169,13 +169,13 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
-            if (input.RowCount != CholeskyFactor.RowCount)
+            if (input.RowCount != Factor.RowCount)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(input, CholeskyFactor);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(input, Factor);
             }
 
             input.CopyTo(result);
-            var order = CholeskyFactor.RowCount;
+            var order = Factor.RowCount;
 
             for (var c = 0; c < result.ColumnCount; c++)
             {
@@ -186,10 +186,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                     sum = result.At(i, c);
                     for (var k = i - 1; k >= 0; k--)
                     {
-                        sum -= CholeskyFactor.At(i, k) * result.At(k, c);
+                        sum -= Factor.At(i, k) * result.At(k, c);
                     }
 
-                    result.At(i, c, sum / CholeskyFactor.At(i, i));
+                    result.At(i, c, sum / Factor.At(i, i));
                 }
 
                 // Solve L'*X = Y;
@@ -198,10 +198,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                     sum = result.At(i, c);
                     for (var k = i + 1; k < order; k++)
                     {
-                        sum -= CholeskyFactor.At(k, i).Conjugate() * result.At(k, c);
+                        sum -= Factor.At(k, i).Conjugate() * result.At(k, c);
                     }
 
-                    result.At(i, c, sum / CholeskyFactor.At(i, i));
+                    result.At(i, c, sum / Factor.At(i, i));
                 }
             }
         }
@@ -230,13 +230,13 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
-            if (input.Count != CholeskyFactor.RowCount)
+            if (input.Count != Factor.RowCount)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(input, CholeskyFactor);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(input, Factor);
             }
 
             input.CopyTo(result);
-            var order = CholeskyFactor.RowCount;
+            var order = Factor.RowCount;
 
             // Solve L*Y = B;
             Complex32 sum;
@@ -245,10 +245,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 sum = result[i];
                 for (var k = i - 1; k >= 0; k--)
                 {
-                    sum -= CholeskyFactor.At(i, k) * result[k];
+                    sum -= Factor.At(i, k) * result[k];
                 }
 
-                result[i] = sum / CholeskyFactor.At(i, i);
+                result[i] = sum / Factor.At(i, i);
             }
 
             // Solve L'*X = Y;
@@ -257,10 +257,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 sum = result[i];
                 for (var k = i + 1; k < order; k++)
                 {
-                    sum -= CholeskyFactor.At(k, i).Conjugate() * result[k];
+                    sum -= Factor.At(k, i).Conjugate() * result[k];
                 }
 
-                result[i] = sum / CholeskyFactor.At(i, i);
+                result[i] = sum / Factor.At(i, i);
             }
         }
     }

src/Numerics/LinearAlgebra/Complex32/Factorization/UserEvd.cs

@@ -78,9 +78,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             var order = matrix.RowCount;
 
             // Initialize matricies for eigenvalues and eigenvectors
-            MatrixEv = DenseMatrix.Identity(order);
-            MatrixD = matrix.CreateMatrix(order, order);
-            VectorEv = new LinearAlgebra.Complex.DenseVector(order);
+            EigenVectors = DenseMatrix.Identity(order);
+            D = matrix.CreateMatrix(order, order);
+            EigenValues = new LinearAlgebra.Complex.DenseVector(order);
            
             IsSymmetric = true;
 
@@ -105,7 +105,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
                 for (var i = 0; i < order; i++)
                 {
-                    VectorEv[i] = new Complex(d[i], e[i]);
+                    EigenValues[i] = new Complex(d[i], e[i]);
                 }
             }
             else
@@ -115,9 +115,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 NonsymmetricReduceHessenberToRealSchur(matrixH, order);
             }
 
-            for (var i = 0; i < VectorEv.Count; i++)
+            for (var i = 0; i < EigenValues.Count; i++)
             {
-                MatrixD.At(i, i, (Complex32)VectorEv[i]);
+                D.At(i, i, (Complex32)EigenValues[i]);
             }
         }
 
@@ -339,9 +339,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                             // Accumulate transformation.
                             for (var k = 0; k < order; k++)
                             {
-                                h = MatrixEv.At(k, i + 1).Real;
-                                MatrixEv.At(k, i + 1, (s * MatrixEv.At(k, i).Real) + (c * h));
-                                MatrixEv.At(k, i, (c * MatrixEv.At(k, i).Real) - (s * h));
+                                h = EigenVectors.At(k, i + 1).Real;
+                                EigenVectors.At(k, i + 1, (s * EigenVectors.At(k, i).Real) + (c * h));
+                                EigenVectors.At(k, i, (c * EigenVectors.At(k, i).Real) - (s * h));
                             }
                         }
 
@@ -383,9 +383,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                     d[i] = p;
                     for (var j = 0; j < order; j++)
                     {
-                        p = MatrixEv.At(j, i).Real;
-                        MatrixEv.At(j, i, MatrixEv.At(j, k));
-                        MatrixEv.At(j, k, p);
+                        p = EigenVectors.At(j, i).Real;
+                        EigenVectors.At(j, i, EigenVectors.At(j, k));
+                        EigenVectors.At(j, k, p);
                     }
                 }
             }
@@ -407,7 +407,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             {
                 for (var j = 0; j < order; j++)
                 {
-                    MatrixEv.At(i, j, MatrixEv.At(i, j).Real * tau[i].Conjugate());
+                    EigenVectors.At(i, j, EigenVectors.At(i, j).Real * tau[i].Conjugate());
                 }
             }
 
@@ -422,14 +422,14 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                         var s = Complex32.Zero;
                         for (var k = 0; k < i; k++)
                         {
-                            s += MatrixEv.At(k, j) * matrixA[i, k];
+                            s += EigenVectors.At(k, j) * matrixA[i, k];
                         }
 
                         s = (s / h) / h;
 
                         for (var k = 0; k < i; k++)
                         {
-                            MatrixEv.At(k, j, MatrixEv.At(k, j) - s * matrixA[i, k].Conjugate());
+                            EigenVectors.At(k, j, EigenVectors.At(k, j) - s * matrixA[i, k].Conjugate());
                         }
                     }
                 }
@@ -523,7 +523,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             {
                 for (var j = 0; j < order; j++)
                 {
-                    MatrixEv.At(i, j, i == j ? Complex32.One : Complex32.Zero);
+                    EigenVectors.At(i, j, i == j ? Complex32.One : Complex32.Zero);
                 }
             }
 
@@ -543,14 +543,14 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                         var g = Complex32.Zero;
                         for (var i = m; i < order; i++)
                         {
-                            g += ort[i].Conjugate() * MatrixEv.At(i, j);
+                            g += ort[i].Conjugate() * EigenVectors.At(i, j);
                         }
 
                         // Double division avoids possible underflow
                         g /= norm;
                         for (var i = m; i < order; i++)
                         {
-                            MatrixEv.At(i, j, MatrixEv.At(i, j) + g * ort[i]);
+                            EigenVectors.At(i, j, EigenVectors.At(i, j) + g * ort[i]);
                         }
                     }
                 }
@@ -575,7 +575,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
                     for (var j = 0; j < order; j++)
                     {
-                        MatrixEv.At(j, i, MatrixEv.At(j, i) * y);
+                        EigenVectors.At(j, i, EigenVectors.At(j, i) * y);
                     }
                 }
             }
@@ -621,7 +621,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 if (l == n)
                 {
                     matrixH[n, n] += exshift;
-                    VectorEv[n] = matrixH[n, n].ToComplex();
+                    EigenValues[n] = matrixH[n, n].ToComplex();
                     n--;
                     iter = 0;
                 }
@@ -667,7 +667,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                         s = matrixH[i, i - 1].Real;
                         norm = SpecialFunctions.Hypotenuse(matrixH[i - 1, i - 1].Magnitude, s.Real);
                         x = matrixH[i - 1, i - 1] / norm;
-                        VectorEv[i - 1] = x.ToComplex();
+                        EigenValues[i - 1] = x.ToComplex();
                         matrixH[i - 1, i - 1] = norm;
                         matrixH[i, i - 1] = new Complex32(0.0f, s.Real / norm);
 
@@ -695,7 +695,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                     // Inverse operation (columns).
                     for (var j = l + 1; j <= n; j++)
                     {
-                        x = (Complex32)VectorEv[j - 1];
+                        x = (Complex32)EigenValues[j - 1];
                         for (var i = 0; i <= j; i++)
                         {
                             z = matrixH[i, j];
@@ -715,10 +715,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
                         for (var i = 0; i < order; i++)
                         {
-                            y = MatrixEv.At(i, j - 1);
-                            z = MatrixEv.At(i, j);
-                            MatrixEv.At(i, j - 1, (x * y) + (matrixH[j, j - 1].Imaginary * z));
-                            MatrixEv.At(i, j, (x.Conjugate() * z) - (matrixH[j, j - 1].Imaginary * y));
+                            y = EigenVectors.At(i, j - 1);
+                            z = EigenVectors.At(i, j);
+                            EigenVectors.At(i, j - 1, (x * y) + (matrixH[j, j - 1].Imaginary * z));
+                            EigenVectors.At(i, j, (x.Conjugate() * z) - (matrixH[j, j - 1].Imaginary * y));
                         }
                     }
 
@@ -731,7 +731,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
                         for (var i = 0; i < order; i++)
                         {
-                            MatrixEv.At(i, n, MatrixEv.At(i, n) * s);
+                            EigenVectors.At(i, n, EigenVectors.At(i, n) * s);
                         }
                     }
                 }
@@ -760,7 +760,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
             for (n = order - 1; n > 0; n--)
             {
-                x = (Complex32)VectorEv[n];
+                x = (Complex32)EigenValues[n];
                 matrixH[n, n] = 1.0f;
 
                 for (var i = n - 1; i >= 0; i--)
@@ -771,7 +771,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                         z += matrixH[i, j] * matrixH[j, n];
                     }
 
-                    y = x - (Complex32)VectorEv[i];
+                    y = x - (Complex32)EigenValues[i];
                     if (y.Real == 0.0f && y.Imaginary == 0.0f)
                     {
                         y = eps * norm;
@@ -799,10 +799,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                     z = Complex32.Zero;
                     for (var k = 0; k <= j; k++)
                     {
-                        z += MatrixEv.At(i, k) * matrixH[k, j];
+                        z += EigenVectors.At(i, k) * matrixH[k, j];
                     }
 
-                    MatrixEv.At(i, j, z);
+                    EigenVectors.At(i, j, z);
                 }
             }
         }
@@ -832,20 +832,20 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (VectorEv.Count != input.RowCount)
+            if (EigenValues.Count != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (VectorEv.Count != result.RowCount)
+            if (EigenValues.Count != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
             if (IsSymmetric)
             {
-                var order = VectorEv.Count;
+                var order = EigenValues.Count;
                 var tmp = new Complex32[order];
 
                 for (var k = 0; k < order; k++)
@@ -857,10 +857,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                         {
                             for (var i = 0; i < order; i++)
                             {
-                                value += MatrixEv.At(i, j).Conjugate() * input.At(i, k);
+                                value += EigenVectors.At(i, j).Conjugate() * input.At(i, k);
                             }
 
-                            value /= (float)VectorEv[j].Real;
+                            value /= (float)EigenValues[j].Real;
                         }
 
                         tmp[j] = value;
@@ -871,7 +871,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                         Complex32 value = 0.0f;
                         for (var i = 0; i < order; i++)
                         {
-                            value += MatrixEv.At(j, i) * tmp[i];
+                            value += EigenVectors.At(j, i) * tmp[i];
                         }
 
                         result.At(j, k, value);
@@ -903,13 +903,13 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
             // Ax=b where A is an m x m matrix
             // Check that b is a column vector with m entries
-            if (VectorEv.Count != input.Count)
+            if (EigenValues.Count != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (VectorEv.Count != result.Count)
+            if (EigenValues.Count != result.Count)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixDimensions);
             }
@@ -917,7 +917,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             if (IsSymmetric)
             {
                 // Symmetric case -> x = V * inv(λ) * VH * b;
-                var order = VectorEv.Count;
+                var order = EigenValues.Count;
                 var tmp = new Complex32[order];
                 Complex32 value;
 
@@ -928,10 +928,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                     {
                         for (var i = 0; i < order; i++)
                         {
-                            value += MatrixEv.At(i, j).Conjugate() * input[i];
+                            value += EigenVectors.At(i, j).Conjugate() * input[i];
                         }
 
-                        value /= (float)VectorEv[j].Real;
+                        value /= (float)EigenValues[j].Real;
                     }
 
                     tmp[j] = value;
@@ -942,7 +942,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                     value = 0;
                     for (int i = 0; i < order; i++)
                     {
-                        value += MatrixEv.At(j, i) * tmp[i];
+                        value += EigenVectors.At(j, i) * tmp[i];
                     }
 
                     result[j] = value;

src/Numerics/LinearAlgebra/Complex32/Factorization/UserGramSchmidt.cs

@@ -64,36 +64,36 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 throw Matrix.DimensionsDontMatch<ArgumentException>(matrix);
             }
 
-            MatrixQ = matrix.Clone();
+            Q = matrix.Clone();
             MatrixR = matrix.CreateMatrix(matrix.ColumnCount, matrix.ColumnCount);
 
-            for (var k = 0; k < MatrixQ.ColumnCount; k++)
+            for (var k = 0; k < Q.ColumnCount; k++)
             {
-                var norm = MatrixQ.Column(k).L2Norm().Real;
+                var norm = Q.Column(k).L2Norm().Real;
                 if (norm == 0.0f)
                 {
                     throw new ArgumentException(Resources.ArgumentMatrixNotRankDeficient);
                 }
 
                 MatrixR.At(k, k, norm);
-                for (var i = 0; i < MatrixQ.RowCount; i++)
+                for (var i = 0; i < Q.RowCount; i++)
                 {
-                    MatrixQ.At(i, k, MatrixQ.At(i, k) / norm);
+                    Q.At(i, k, Q.At(i, k) / norm);
                 }
 
-                for (var j = k + 1; j < MatrixQ.ColumnCount; j++)
+                for (var j = k + 1; j < Q.ColumnCount; j++)
                 {
                     var dot = Complex32.Zero;
-                    for (int i = 0; i < MatrixQ.RowCount; i++)
+                    for (int i = 0; i < Q.RowCount; i++)
                     {
-                        dot += MatrixQ.Column(k)[i].Conjugate() * MatrixQ.Column(j)[i];
+                        dot += Q.Column(k)[i].Conjugate() * Q.Column(j)[i];
                     }
                     
                     MatrixR.At(k, j, dot);
-                    for (var i = 0; i < MatrixQ.RowCount; i++)
+                    for (var i = 0; i < Q.RowCount; i++)
                     {
-                        var value = MatrixQ.At(i, j) - (MatrixQ.At(i, k) * dot);
-                        MatrixQ.At(i, j, value);
+                        var value = Q.At(i, j) - (Q.At(i, k) * dot);
+                        Q.At(i, j, value);
                     }
                 }
             }
@@ -124,13 +124,13 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixQ.RowCount != input.RowCount)
+            if (Q.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (MatrixQ.ColumnCount != result.RowCount)
+            if (Q.ColumnCount != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
@@ -138,20 +138,20 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             var inputCopy = input.Clone();
             
             // Compute Y = transpose(Q)*B
-            var column = new Complex32[MatrixQ.RowCount];
+            var column = new Complex32[Q.RowCount];
             for (var j = 0; j < input.ColumnCount; j++)
             {
-                for (var k = 0; k < MatrixQ.RowCount; k++)
+                for (var k = 0; k < Q.RowCount; k++)
                 {
                     column[k] = inputCopy.At(k, j);
                 }
 
-                for (var i = 0; i < MatrixQ.ColumnCount; i++)
+                for (var i = 0; i < Q.ColumnCount; i++)
                 {
                     var s = Complex32.Zero;
-                    for (var k = 0; k < MatrixQ.RowCount; k++)
+                    for (var k = 0; k < Q.RowCount; k++)
                     {
-                        s += MatrixQ.At(k, i).Conjugate() * column[k];
+                        s += Q.At(k, i).Conjugate() * column[k];
                     }
 
                     inputCopy.At(i, j, s);
@@ -159,7 +159,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             }
 
             // Solve R*X = Y;
-            for (var k = MatrixQ.ColumnCount - 1; k >= 0; k--)
+            for (var k = Q.ColumnCount - 1; k >= 0; k--)
             {
                 for (var j = 0; j < input.ColumnCount; j++)
                 {
@@ -203,39 +203,39 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixQ.RowCount != input.Count)
+            if (Q.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (MatrixQ.ColumnCount != result.Count)
+            if (Q.ColumnCount != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(MatrixQ, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(Q, result);
             }
 
             var inputCopy = input.Clone();
 
             // Compute Y = transpose(Q)*B
-            var column = new Complex32[MatrixQ.RowCount];
-            for (var k = 0; k < MatrixQ.RowCount; k++)
+            var column = new Complex32[Q.RowCount];
+            for (var k = 0; k < Q.RowCount; k++)
             {
                 column[k] = inputCopy[k];
             }
 
-            for (var i = 0; i < MatrixQ.ColumnCount; i++)
+            for (var i = 0; i < Q.ColumnCount; i++)
             {
                 var s = Complex32.Zero;
-                for (var k = 0; k < MatrixQ.RowCount; k++)
+                for (var k = 0; k < Q.RowCount; k++)
                 {
-                    s += MatrixQ.At(k, i).Conjugate() * column[k];
+                    s += Q.At(k, i).Conjugate() * column[k];
                 }
 
                 inputCopy[i] = s;
             }
 
             // Solve R*X = Y;
-            for (var k = MatrixQ.ColumnCount - 1; k >= 0; k--)
+            for (var k = Q.ColumnCount - 1; k >= 0; k--)
             {
                 inputCopy[k] /= MatrixR.At(k, k);
                 for (var i = 0; i < k; i++)

src/Numerics/LinearAlgebra/Complex32/Factorization/UserQR.cs

@@ -75,11 +75,11 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             if (method == QRMethod.Full)
             {
                 MatrixR = matrix.Clone();
-                MatrixQ = matrix.CreateMatrix(matrix.RowCount, matrix.RowCount);
+                Q = matrix.CreateMatrix(matrix.RowCount, matrix.RowCount);
 
                 for (var i = 0; i < matrix.RowCount; i++)
                 {
-                    MatrixQ.At(i, i, 1.0f);
+                    Q.At(i, i, 1.0f);
                 }
 
                 for (var i = 0; i < minmn; i++)
@@ -91,33 +91,33 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
                 for (var i = minmn - 1; i >= 0; i--)
                 {
-                    ComputeQR(u[i], MatrixQ, i, matrix.RowCount, i, matrix.RowCount,
+                    ComputeQR(u[i], Q, i, matrix.RowCount, i, matrix.RowCount,
                               Control.NumberOfParallelWorkerThreads);
                 }
             }
             else
             {
                 MatrixR = matrix.CreateMatrix(matrix.ColumnCount, matrix.ColumnCount);
-                MatrixQ = matrix.Clone();
+                Q = matrix.Clone();
 
                 for (var i = 0; i < minmn; i++)
                 {
-                    u[i] = GenerateColumn(MatrixQ, i, i);
-                    ComputeQR(u[i], MatrixQ, i, matrix.RowCount, i + 1, matrix.ColumnCount,
+                    u[i] = GenerateColumn(Q, i, i);
+                    ComputeQR(u[i], Q, i, matrix.RowCount, i + 1, matrix.ColumnCount,
                               Control.NumberOfParallelWorkerThreads);
                 }
 
-                MatrixR = MatrixQ.SubMatrix(0, matrix.ColumnCount, 0, matrix.ColumnCount);
-                MatrixQ.Clear();
+                MatrixR = Q.SubMatrix(0, matrix.ColumnCount, 0, matrix.ColumnCount);
+                Q.Clear();
 
                 for (var i = 0; i < matrix.ColumnCount; i++)
                 {
-                    MatrixQ.At(i, i, 1.0f);
+                    Q.At(i, i, 1.0f);
                 }
 
                 for (var i = minmn - 1; i >= 0; i--)
                 {
-                    ComputeQR(u[i], MatrixQ, i, matrix.RowCount, i, matrix.ColumnCount,
+                    ComputeQR(u[i], Q, i, matrix.RowCount, i, matrix.ColumnCount,
                               Control.NumberOfParallelWorkerThreads);
                 }
             }
@@ -272,7 +272,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                     var s = Complex32.Zero;
                     for (var k = 0; k < MatrixR.RowCount; k++)
                     {
-                        s += MatrixQ.At(k, i).Conjugate() * column[k];
+                        s += Q.At(k, i).Conjugate() * column[k];
                     }
 
                     inputCopy.At(i, j, s);
@@ -349,7 +349,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 var s = Complex32.Zero;
                 for (var k = 0; k < MatrixR.RowCount; k++)
                 {
-                    s += MatrixQ.At(k, i).Conjugate() * column[k];
+                    s += Q.At(k, i).Conjugate() * column[k];
                 }
 
                 inputCopy[i] = s;

src/Numerics/LinearAlgebra/Complex32/Factorization/UserSvd.cs

@@ -70,9 +70,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             var nm = Math.Min(matrix.RowCount + 1, matrix.ColumnCount);
             var matrixCopy = matrix.Clone();
 
-            VectorS = matrixCopy.CreateVector(nm);
-            MatrixU = matrixCopy.CreateMatrix(matrixCopy.RowCount, matrixCopy.RowCount);
-            MatrixVT = matrixCopy.CreateMatrix(matrixCopy.ColumnCount, matrixCopy.ColumnCount);
+            S = matrixCopy.CreateVector(nm);
+            U = matrixCopy.CreateMatrix(matrixCopy.RowCount, matrixCopy.RowCount);
+            VT = matrixCopy.CreateMatrix(matrixCopy.ColumnCount, matrixCopy.ColumnCount);
 
             const int maxiter = 1000;
             var e = new Complex32[matrixCopy.ColumnCount];
@@ -95,26 +95,26 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 if (l < nct)
                 {
                     // Compute the transformation for the l-th column and place the l-th diagonal in VectorS[l].
-                    VectorS[l] = Cnrm2Column(matrixCopy, matrixCopy.RowCount, l, l);
-                    if (VectorS[l].Magnitude != 0.0f)
+                    S[l] = Cnrm2Column(matrixCopy, matrixCopy.RowCount, l, l);
+                    if (S[l].Magnitude != 0.0f)
                     {
                         if (matrixCopy.At(l, l).Magnitude != 0.0f)
                         {
-                            VectorS[l] = Csign(VectorS[l], matrixCopy.At(l, l));
+                            S[l] = Csign(S[l], matrixCopy.At(l, l));
                         }
 
-                        CscalColumn(matrixCopy, matrixCopy.RowCount, l, l, 1.0f / VectorS[l]);
+                        CscalColumn(matrixCopy, matrixCopy.RowCount, l, l, 1.0f / S[l]);
                         matrixCopy.At(l, l, (Complex32.One + matrixCopy.At(l, l)));
                     }
 
-                    VectorS[l] = -VectorS[l];
+                    S[l] = -S[l];
                 }
 
                 for (j = lp1; j < matrixCopy.ColumnCount; j++)
                 {
                     if (l < nct)
                     {
-                        if (VectorS[l].Magnitude != 0.0f)
+                        if (S[l].Magnitude != 0.0f)
                         {
                             // Apply the transformation.
                             t = -Cdotc(matrixCopy, matrixCopy.RowCount, l, j, l) / matrixCopy.At(l, l);
@@ -138,7 +138,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                     // Place the transformation in u for subsequent back multiplication.
                     for (i = l; i < matrixCopy.RowCount; i++)
                     {
-                        MatrixU.At(i, l, matrixCopy.At(i, l));
+                        U.At(i, l, matrixCopy.At(i, l));
                     }
                 }
 
@@ -199,7 +199,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                     // Place the transformation in v for subsequent back multiplication.
                     for (i = lp1; i < matrixCopy.ColumnCount; i++)
                     {
-                        MatrixVT.At(i, l, e[i]);
+                        VT.At(i, l, e[i]);
                     }
                 }
             }
@@ -210,12 +210,12 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             var nrtp1 = nrt + 1;
             if (nct < matrixCopy.ColumnCount)
             {
-                VectorS[nctp1 - 1] = matrixCopy.At((nctp1 - 1), (nctp1 - 1));
+                S[nctp1 - 1] = matrixCopy.At((nctp1 - 1), (nctp1 - 1));
             }
 
             if (matrixCopy.RowCount < m)
             {
-                VectorS[m - 1] = Complex32.Zero;
+                S[m - 1] = Complex32.Zero;
             }
 
             if (nrtp1 < m)
@@ -232,43 +232,43 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 {
                     for (i = 0; i < matrixCopy.RowCount; i++)
                     {
-                        MatrixU.At(i, j, Complex32.Zero);
+                        U.At(i, j, Complex32.Zero);
                     }
 
-                    MatrixU.At(j, j, Complex32.One);
+                    U.At(j, j, Complex32.One);
                 }
 
                 for (l = nct - 1; l >= 0; l--)
                 {
-                    if (VectorS[l].Magnitude != 0.0f)
+                    if (S[l].Magnitude != 0.0f)
                     {
                         for (j = l + 1; j < ncu; j++)
                         {
-                            t = -Cdotc(MatrixU, matrixCopy.RowCount, l, j, l) / MatrixU.At(l, l);
+                            t = -Cdotc(U, matrixCopy.RowCount, l, j, l) / U.At(l, l);
                             if (t != Complex32.Zero)
                             {
                                 for (var ii = l; ii < matrixCopy.RowCount; ii++)
                                 {
-                                    MatrixU.At(ii, j, MatrixU.At(ii, j) + (t * MatrixU.At(ii, l)));
+                                    U.At(ii, j, U.At(ii, j) + (t * U.At(ii, l)));
                                 }
                             }
                         }
 
-                        CscalColumn(MatrixU, matrixCopy.RowCount, l, l, -1.0f);
-                        MatrixU.At(l, l, Complex32.One + MatrixU.At(l, l));
+                        CscalColumn(U, matrixCopy.RowCount, l, l, -1.0f);
+                        U.At(l, l, Complex32.One + U.At(l, l));
                         for (i = 0; i < l; i++)
                         {
-                            MatrixU.At(i, l, Complex32.Zero);
+                            U.At(i, l, Complex32.Zero);
                         }
                     }
                     else
                     {
                         for (i = 0; i < matrixCopy.RowCount; i++)
                         {
-                            MatrixU.At(i, l, Complex32.Zero);
+                            U.At(i, l, Complex32.Zero);
                         }
 
-                        MatrixU.At(l, l, Complex32.One);
+                        U.At(l, l, Complex32.One);
                     }
                 }
             }
@@ -285,12 +285,12 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                         {
                             for (j = lp1; j < matrixCopy.ColumnCount; j++)
                             {
-                                t = -Cdotc(MatrixVT, matrixCopy.ColumnCount, l, j, lp1) / MatrixVT.At(lp1, l);
+                                t = -Cdotc(VT, matrixCopy.ColumnCount, l, j, lp1) / VT.At(lp1, l);
                                 if (t != Complex32.Zero)
                                 {
                                     for (var ii = l; ii < matrixCopy.ColumnCount; ii++)
                                     {
-                                        MatrixVT.At(ii, j, MatrixVT.At(ii, j) + (t * MatrixVT.At(ii, l)));
+                                        VT.At(ii, j, VT.At(ii, j) + (t * VT.At(ii, l)));
                                     }
                                 }
                             }
@@ -299,10 +299,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
                     for (i = 0; i < matrixCopy.ColumnCount; i++)
                     {
-                        MatrixVT.At(i, l, Complex32.Zero);
+                        VT.At(i, l, Complex32.Zero);
                     }
 
-                    MatrixVT.At(l, l, Complex32.One);
+                    VT.At(l, l, Complex32.One);
                 }
             }
 
@@ -310,11 +310,11 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             for (i = 0; i < m; i++)
             {
                 Complex32 r;
-                if (VectorS[i].Magnitude != 0.0f)
+                if (S[i].Magnitude != 0.0f)
                 {
-                    t = VectorS[i].Magnitude;
-                    r = VectorS[i] / t;
-                    VectorS[i] = t;
+                    t = S[i].Magnitude;
+                    r = S[i] / t;
+                    S[i] = t;
                     if (i < m - 1)
                     {
                         e[i] = e[i] / r;
@@ -322,7 +322,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
                     if (ComputeVectors)
                     {
-                        CscalColumn(MatrixU, matrixCopy.RowCount, i, 0, r);
+                        CscalColumn(U, matrixCopy.RowCount, i, 0, r);
                     }
                 }
 
@@ -337,10 +337,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                     t = e[i].Magnitude;
                     r = t / e[i];
                     e[i] = t;
-                    VectorS[i + 1] = VectorS[i + 1] * r;
+                    S[i + 1] = S[i + 1] * r;
                     if (ComputeVectors)
                     {
-                        CscalColumn(MatrixVT, matrixCopy.ColumnCount, i + 1, 0, r);
+                        CscalColumn(VT, matrixCopy.ColumnCount, i + 1, 0, r);
                     }
                 }
             }
@@ -368,7 +368,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 float test;
                 for (l = m - 2; l >= 0; l--)
                 {
-                    test = VectorS[l].Magnitude + VectorS[l + 1].Magnitude;
+                    test = S[l].Magnitude + S[l + 1].Magnitude;
                     ztest = test + e[l].Magnitude;
                     if (ztest.AlmostEqualInDecimalPlaces(test, 7))
                     {
@@ -398,10 +398,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                             test = test + e[ls - 1].Magnitude;
                         }
 
-                        ztest = test + VectorS[ls].Magnitude;
+                        ztest = test + S[ls].Magnitude;
                         if (ztest.AlmostEqualInDecimalPlaces(test, 7))
                         {
-                            VectorS[ls] = Complex32.Zero;
+                            S[ls] = Complex32.Zero;
                             break;
                         }
                     }
@@ -438,9 +438,9 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                         for (var kk = l; kk < m - 1; kk++)
                         {
                             k = m - 2 - kk + l;
-                            t1 = VectorS[k].Real;
+                            t1 = S[k].Real;
                             Srotg(ref t1, ref f, out cs, out sn);
-                            VectorS[k] = t1;
+                            S[k] = t1;
                             if (k != l)
                             {
                                 f = -sn * e[k - 1].Real;
@@ -449,7 +449,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
                             if (ComputeVectors)
                             {
-                                Csrot(MatrixVT, matrixCopy.ColumnCount, k, m - 1, cs, sn);
+                                Csrot(VT, matrixCopy.ColumnCount, k, m - 1, cs, sn);
                             }
                         }
 
@@ -461,14 +461,14 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                         e[l - 1] = Complex32.Zero;
                         for (k = l; k < m; k++)
                         {
-                            t1 = VectorS[k].Real;
+                            t1 = S[k].Real;
                             Srotg(ref t1, ref f, out cs, out sn);
-                            VectorS[k] = t1;
+                            S[k] = t1;
                             f = -sn * e[k].Real;
                             e[k] = cs * e[k];
                             if (ComputeVectors)
                             {
-                                Csrot(MatrixU, matrixCopy.RowCount, k, l - 1, cs, sn);
+                                Csrot(U, matrixCopy.RowCount, k, l - 1, cs, sn);
                             }
                         }
 
@@ -478,15 +478,15 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                     case 3:
                         // Calculate the shift.
                         var scale = 0.0f;
-                        scale = Math.Max(scale, VectorS[m - 1].Magnitude);
-                        scale = Math.Max(scale, VectorS[m - 2].Magnitude);
+                        scale = Math.Max(scale, S[m - 1].Magnitude);
+                        scale = Math.Max(scale, S[m - 2].Magnitude);
                         scale = Math.Max(scale, e[m - 2].Magnitude);
-                        scale = Math.Max(scale, VectorS[l].Magnitude);
+                        scale = Math.Max(scale, S[l].Magnitude);
                         scale = Math.Max(scale, e[l].Magnitude);
-                        var sm = VectorS[m - 1].Real / scale;
-                        var smm1 = VectorS[m - 2].Real / scale;
+                        var sm = S[m - 1].Real / scale;
+                        var smm1 = S[m - 2].Real / scale;
                         var emm1 = e[m - 2].Real / scale;
-                        var sl = VectorS[l].Real / scale;
+                        var sl = S[l].Real / scale;
                         var el = e[l].Real / scale;
                         var b = (((smm1 + sm) * (smm1 - sm)) + (emm1 * emm1)) / 2.0f;
                         var c = (sm * emm1) * (sm * emm1);
@@ -515,24 +515,24 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                                 e[k - 1] = f;
                             }
 
-                            f = (cs * VectorS[k].Real) + (sn * e[k].Real);
-                            e[k] = (cs * e[k]) - (sn * VectorS[k]);
-                            g = sn * VectorS[k + 1].Real;
-                            VectorS[k + 1] = cs * VectorS[k + 1];
+                            f = (cs * S[k].Real) + (sn * e[k].Real);
+                            e[k] = (cs * e[k]) - (sn * S[k]);
+                            g = sn * S[k + 1].Real;
+                            S[k + 1] = cs * S[k + 1];
                             if (ComputeVectors)
                             {
-                                Csrot(MatrixVT, matrixCopy.ColumnCount, k, k + 1, cs, sn);
+                                Csrot(VT, matrixCopy.ColumnCount, k, k + 1, cs, sn);
                             }
 
                             Srotg(ref f, ref g, out cs, out sn);
-                            VectorS[k] = f;
-                            f = (cs * e[k].Real) + (sn * VectorS[k + 1].Real);
-                            VectorS[k + 1] = (-sn * e[k]) + (cs * VectorS[k + 1]);
+                            S[k] = f;
+                            f = (cs * e[k].Real) + (sn * S[k + 1].Real);
+                            S[k + 1] = (-sn * e[k]) + (cs * S[k + 1]);
                             g = sn * e[k + 1].Real;
                             e[k + 1] = cs * e[k + 1];
                             if (ComputeVectors && k < matrixCopy.RowCount)
                             {
-                                Csrot(MatrixU, matrixCopy.RowCount, k, k + 1, cs, sn);
+                                Csrot(U, matrixCopy.RowCount, k, k + 1, cs, sn);
                             }
                         }
 
@@ -543,34 +543,34 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                     // Convergence.
                     case 4:
                         // Make the singular value  positive
-                        if (VectorS[l].Real < 0.0f)
+                        if (S[l].Real < 0.0f)
                         {
-                            VectorS[l] = -VectorS[l];
+                            S[l] = -S[l];
                             if (ComputeVectors)
                             {
-                                CscalColumn(MatrixVT, matrixCopy.ColumnCount, l, 0, -1.0f);
+                                CscalColumn(VT, matrixCopy.ColumnCount, l, 0, -1.0f);
                             }
                         }
 
                         // Order the singular value.
                         while (l != mn - 1)
                         {
-                            if (VectorS[l].Real >= VectorS[l + 1].Real)
+                            if (S[l].Real >= S[l + 1].Real)
                             {
                                 break;
                             }
 
-                            t = VectorS[l];
-                            VectorS[l] = VectorS[l + 1];
-                            VectorS[l + 1] = t;
+                            t = S[l];
+                            S[l] = S[l + 1];
+                            S[l + 1] = t;
                             if (ComputeVectors && l < matrixCopy.ColumnCount)
                             {
-                                Swap(MatrixVT, matrixCopy.ColumnCount, l, l + 1);
+                                Swap(VT, matrixCopy.ColumnCount, l, l + 1);
                             }
 
                             if (ComputeVectors && l < matrixCopy.RowCount)
                             {
-                                Swap(MatrixU, matrixCopy.RowCount, l, l + 1);
+                                Swap(U, matrixCopy.RowCount, l, l + 1);
                             }
 
                             l = l + 1;
@@ -584,7 +584,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
             if (ComputeVectors)
             {
-                MatrixVT = MatrixVT.ConjugateTranspose();
+                VT = VT.ConjugateTranspose();
             }
 
             // Adjust the size of s if rows < columns. We are using ported copy of linpack's svd code and it uses
@@ -596,10 +596,10 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
                 var tmp = matrixCopy.CreateVector(nm);
                 for (i = 0; i < nm; i++)
                 {
-                    tmp[i] = VectorS[i];
+                    tmp[i] = S[i];
                 }
 
-                VectorS = tmp;
+                S = tmp;
             }
         }
 
@@ -825,46 +825,46 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixU.RowCount != input.RowCount)
+            if (U.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (MatrixVT.ColumnCount != result.RowCount)
+            if (VT.ColumnCount != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
-            var mn = Math.Min(MatrixU.RowCount, MatrixVT.ColumnCount);
+            var mn = Math.Min(U.RowCount, VT.ColumnCount);
             var bn = input.ColumnCount;
 
-            var tmp = new Complex32[MatrixVT.ColumnCount];
+            var tmp = new Complex32[VT.ColumnCount];
 
             for (var k = 0; k < bn; k++)
             {
-                for (var j = 0; j < MatrixVT.ColumnCount; j++)
+                for (var j = 0; j < VT.ColumnCount; j++)
                 {
                     var value = Complex32.Zero;
                     if (j < mn)
                     {
-                        for (var i = 0; i < MatrixU.RowCount; i++)
+                        for (var i = 0; i < U.RowCount; i++)
                         {
-                            value += MatrixU.At(i, j).Conjugate() * input.At(i, k);
+                            value += U.At(i, j).Conjugate() * input.At(i, k);
                         }
 
-                        value /= VectorS[j];
+                        value /= S[j];
                     }
 
                     tmp[j] = value;
                 }
 
-                for (var j = 0; j < MatrixVT.ColumnCount; j++)
+                for (var j = 0; j < VT.ColumnCount; j++)
                 {
                     var value = Complex32.Zero;
-                    for (var i = 0; i < MatrixVT.ColumnCount; i++)
+                    for (var i = 0; i < VT.ColumnCount; i++)
                     {
-                        value += MatrixVT.At(i, j).Conjugate() * tmp[i];
+                        value += VT.At(i, j).Conjugate() * tmp[i];
                     }
 
                     result.At(j, k, value);
@@ -896,41 +896,41 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixU.RowCount != input.Count)
+            if (U.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (MatrixVT.ColumnCount != result.Count)
+            if (VT.ColumnCount != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(MatrixVT, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(VT, result);
             }
 
-            var mn = Math.Min(MatrixU.RowCount, MatrixVT.ColumnCount);
-            var tmp = new Complex32[MatrixVT.ColumnCount];
-            for (var j = 0; j < MatrixVT.ColumnCount; j++)
+            var mn = Math.Min(U.RowCount, VT.ColumnCount);
+            var tmp = new Complex32[VT.ColumnCount];
+            for (var j = 0; j < VT.ColumnCount; j++)
             {
                 var value = Complex32.Zero;
                 if (j < mn)
                 {
-                    for (var i = 0; i < MatrixU.RowCount; i++)
+                    for (var i = 0; i < U.RowCount; i++)
                     {
-                        value += MatrixU.At(i, j).Conjugate() * input[i];
+                        value += U.At(i, j).Conjugate() * input[i];
                     }
 
-                    value /= VectorS[j];
+                    value /= S[j];
                 }
 
                 tmp[j] = value;
             }
 
-            for (var j = 0; j < MatrixVT.ColumnCount; j++)
+            for (var j = 0; j < VT.ColumnCount; j++)
             {
                 var value = Complex32.Zero;
-                for (var i = 0; i < MatrixVT.ColumnCount; i++)
+                for (var i = 0; i < VT.ColumnCount; i++)
                 {
-                    value += MatrixVT.At(i, j).Conjugate() * tmp[i];
+                    value += VT.At(i, j).Conjugate() * tmp[i];
                 }
 
                 result[j] = value;

src/Numerics/LinearAlgebra/Double/Factorization/Cholesky.cs

@@ -53,9 +53,9 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             get
             {
                 var det = 1.0;
-                for (var j = 0; j < CholeskyFactor.RowCount; j++)
+                for (var j = 0; j < Factor.RowCount; j++)
                 {
-                    var d = CholeskyFactor.At(j, j);
+                    var d = Factor.At(j, j);
                     det *= d * d;
                 }
 
@@ -71,9 +71,9 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             get
             {
                 var det = 0.0;
-                for (var j = 0; j < CholeskyFactor.RowCount; j++)
+                for (var j = 0; j < Factor.RowCount; j++)
                 {
-                    det += 2 * Math.Log(CholeskyFactor.At(j, j));
+                    det += 2 * Math.Log(Factor.At(j, j));
                 }
 
                 return det;

src/Numerics/LinearAlgebra/Double/Factorization/DenseCholesky.cs

@@ -67,7 +67,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             // Create a new matrix for the Cholesky factor, then perform factorization (while overwriting).
             var factor = (DenseMatrix)matrix.Clone();
             Control.LinearAlgebraProvider.CholeskyFactor(factor.Values, factor.RowCount);
-            CholeskyFactor = factor;
+            Factor = factor;
         }
 
         /// <summary>
@@ -99,9 +99,9 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
-            if (input.RowCount != CholeskyFactor.RowCount)
+            if (input.RowCount != Factor.RowCount)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(input, CholeskyFactor);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(input, Factor);
             }
 
             var dinput = input as DenseMatrix;
@@ -120,7 +120,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             Buffer.BlockCopy(dinput.Values, 0, dresult.Values, 0, dinput.Values.Length * Constants.SizeOfDouble);
 
             // Cholesky solve by overwriting result.
-            var dfactor = (DenseMatrix)CholeskyFactor;
+            var dfactor = (DenseMatrix)Factor;
             Control.LinearAlgebraProvider.CholeskySolveFactored(dfactor.Values, dfactor.RowCount, dresult.Values, dresult.ColumnCount);
         }
 
@@ -148,9 +148,9 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
-            if (input.Count != CholeskyFactor.RowCount)
+            if (input.Count != Factor.RowCount)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(input, CholeskyFactor);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(input, Factor);
             }
 
             var dinput = input as DenseVector;
@@ -169,7 +169,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             Buffer.BlockCopy(dinput.Values, 0, dresult.Values, 0, dinput.Values.Length * Constants.SizeOfDouble);
 
             // Cholesky solve by overwriting result.
-            var dfactor = (DenseMatrix)CholeskyFactor;
+            var dfactor = (DenseMatrix)Factor;
             Control.LinearAlgebraProvider.CholeskySolveFactored(dfactor.Values, dfactor.RowCount, dresult.Values, 1);
         }
     }

src/Numerics/LinearAlgebra/Double/Factorization/DenseEvd.cs

@@ -79,9 +79,9 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             var order = matrix.RowCount;
 
             // Initialize matrices for eigenvalues and eigenvectors
-            MatrixEv = matrix.CreateMatrix(order, order);
-            MatrixD = matrix.CreateMatrix(order, order);
-            VectorEv = new LinearAlgebra.Complex.DenseVector(order);
+            EigenVectors = matrix.CreateMatrix(order, order);
+            D = matrix.CreateMatrix(order, order);
+            EigenValues = new LinearAlgebra.Complex.DenseVector(order);
 
             IsSymmetric = true;
 
@@ -93,8 +93,8 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 }
             }
 
-            Control.LinearAlgebraProvider.EigenDecomp(IsSymmetric, order, matrix.Values, ((DenseMatrix) MatrixEv).Values,
-                ((LinearAlgebra.Complex.DenseVector)VectorEv).Values, ((DenseMatrix)MatrixD).Values);
+            Control.LinearAlgebraProvider.EigenDecomp(IsSymmetric, order, matrix.Values, ((DenseMatrix) EigenVectors).Values,
+                ((LinearAlgebra.Complex.DenseVector)EigenValues).Values, ((DenseMatrix)D).Values);
         }
 
         /// <summary>
@@ -1132,20 +1132,20 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (VectorEv.Count != input.RowCount)
+            if (EigenValues.Count != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (VectorEv.Count != result.RowCount)
+            if (EigenValues.Count != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
             if (IsSymmetric)
             {
-                var order = VectorEv.Count;
+                var order = EigenValues.Count;
                 var tmp = new double[order];
 
                 for (var k = 0; k < order; k++)
@@ -1157,10 +1157,10 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                         {
                             for (var i = 0; i < order; i++)
                             {
-                                value += ((DenseMatrix) MatrixEv).Values[(j*order) + i]*input.At(i, k);
+                                value += ((DenseMatrix) EigenVectors).Values[(j*order) + i]*input.At(i, k);
                             }
 
-                            value /= VectorEv[j].Real;
+                            value /= EigenValues[j].Real;
                         }
 
                         tmp[j] = value;
@@ -1171,7 +1171,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                         double value = 0;
                         for (var i = 0; i < order; i++)
                         {
-                            value += ((DenseMatrix) MatrixEv).Values[(i*order) + j]*tmp[i];
+                            value += ((DenseMatrix) EigenVectors).Values[(i*order) + j]*tmp[i];
                         }
 
                         result.At(j, k, value);
@@ -1203,13 +1203,13 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
 
             // Ax=b where A is an m x m matrix
             // Check that b is a column vector with m entries
-            if (VectorEv.Count != input.Count)
+            if (EigenValues.Count != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (VectorEv.Count != result.Count)
+            if (EigenValues.Count != result.Count)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixDimensions);
             }
@@ -1217,7 +1217,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             if (IsSymmetric)
             {
                 // Symmetric case -> x = V * inv(λ) * VT * b;
-                var order = VectorEv.Count;
+                var order = EigenValues.Count;
                 var tmp = new double[order];
                 double value;
 
@@ -1228,10 +1228,10 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                     {
                         for (var i = 0; i < order; i++)
                         {
-                            value += ((DenseMatrix) MatrixEv).Values[(j*order) + i]*input[i];
+                            value += ((DenseMatrix) EigenVectors).Values[(j*order) + i]*input[i];
                         }
 
-                        value /= VectorEv[j].Real;
+                        value /= EigenValues[j].Real;
                     }
 
                     tmp[j] = value;
@@ -1242,7 +1242,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                     value = 0;
                     for (var i = 0; i < order; i++)
                     {
-                        value += ((DenseMatrix) MatrixEv).Values[(i*order) + j]*tmp[i];
+                        value += ((DenseMatrix) EigenVectors).Values[(i*order) + j]*tmp[i];
                     }
 
                     result[j] = value;

src/Numerics/LinearAlgebra/Double/Factorization/DenseGramSchmidt.cs

@@ -69,9 +69,9 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 throw Matrix.DimensionsDontMatch<ArgumentException>(matrix);
             }
 
-            MatrixQ = matrix.Clone();
+            Q = matrix.Clone();
             MatrixR = matrix.CreateMatrix(matrix.ColumnCount, matrix.ColumnCount);
-            Factorize(((DenseMatrix)MatrixQ).Values, MatrixQ.RowCount, MatrixQ.ColumnCount, ((DenseMatrix)MatrixR).Values);
+            Factorize(((DenseMatrix)Q).Values, Q.RowCount, Q.ColumnCount, ((DenseMatrix)MatrixR).Values);
         }
 
         /// <summary>
@@ -149,13 +149,13 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixQ.RowCount != input.RowCount)
+            if (Q.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (MatrixQ.ColumnCount != result.RowCount)
+            if (Q.ColumnCount != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
@@ -172,7 +172,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 throw new NotSupportedException("Can only do GramSchmidt factorization for dense matrices at the moment.");
             }
 
-            _provider.QRSolveFactored(((DenseMatrix)MatrixQ).Values, ((DenseMatrix)MatrixR).Values, MatrixQ.RowCount, MatrixR.ColumnCount, null, dinput.Values, input.ColumnCount, dresult.Values, QRMethod.Thin);
+            _provider.QRSolveFactored(((DenseMatrix)Q).Values, ((DenseMatrix)MatrixR).Values, Q.RowCount, MatrixR.ColumnCount, null, dinput.Values, input.ColumnCount, dresult.Values, QRMethod.Thin);
         }
 
         /// <summary>
@@ -194,15 +194,15 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixQ.RowCount != input.Count)
+            if (Q.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (MatrixQ.ColumnCount != result.Count)
+            if (Q.ColumnCount != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(MatrixQ, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(Q, result);
             }
 
             var dinput = input as DenseVector;
@@ -217,7 +217,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 throw new NotSupportedException("Can only do GramSchmidt factorization for dense vectors at the moment.");
             }
 
-            _provider.QRSolveFactored(((DenseMatrix)MatrixQ).Values, ((DenseMatrix)MatrixR).Values, MatrixQ.RowCount, MatrixR.ColumnCount, null, dinput.Values, 1, dresult.Values, QRMethod.Thin);
+            _provider.QRSolveFactored(((DenseMatrix)Q).Values, ((DenseMatrix)MatrixR).Values, Q.RowCount, MatrixR.ColumnCount, null, dinput.Values, 1, dresult.Values, QRMethod.Thin);
         }
     }
 }

src/Numerics/LinearAlgebra/Double/Factorization/DenseQR.cs

@@ -80,15 +80,15 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             if (method == QRMethod.Full)
             {
                 MatrixR = matrix.Clone();
-                MatrixQ = new DenseMatrix(matrix.RowCount);
+                Q = new DenseMatrix(matrix.RowCount);
                 Control.LinearAlgebraProvider.QRFactor(((DenseMatrix)MatrixR).Values, matrix.RowCount, matrix.ColumnCount,
-                                                       ((DenseMatrix)MatrixQ).Values, Tau);
+                                                       ((DenseMatrix)Q).Values, Tau);
             }
             else
             {
-                MatrixQ = matrix.Clone();
+                Q = matrix.Clone();
                 MatrixR = new DenseMatrix(matrix.ColumnCount);
-                Control.LinearAlgebraProvider.ThinQRFactor(((DenseMatrix) MatrixQ).Values, matrix.RowCount,
+                Control.LinearAlgebraProvider.ThinQRFactor(((DenseMatrix) Q).Values, matrix.RowCount,
                                                            matrix.ColumnCount,
                                                            ((DenseMatrix) MatrixR).Values, Tau);
             }
@@ -119,7 +119,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixQ.RowCount != input.RowCount)
+            if (Q.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
@@ -142,7 +142,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 throw new NotSupportedException("Can only do QR factorization for dense matrices at the moment.");
             }
 
-            Control.LinearAlgebraProvider.QRSolveFactored(((DenseMatrix)MatrixQ).Values, ((DenseMatrix)MatrixR).Values, MatrixQ.RowCount, MatrixR.ColumnCount, Tau, dinput.Values, input.ColumnCount, dresult.Values, QrMethod);
+            Control.LinearAlgebraProvider.QRSolveFactored(((DenseMatrix)Q).Values, ((DenseMatrix)MatrixR).Values, Q.RowCount, MatrixR.ColumnCount, Tau, dinput.Values, input.ColumnCount, dresult.Values, QrMethod);
         }
 
         /// <summary>
@@ -164,7 +164,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixQ.RowCount != input.Count)
+            if (Q.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
@@ -187,7 +187,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 throw new NotSupportedException("Can only do QR factorization for dense vectors at the moment.");
             }
 
-            Control.LinearAlgebraProvider.QRSolveFactored(((DenseMatrix)MatrixQ).Values, ((DenseMatrix)MatrixR).Values, MatrixQ.RowCount, MatrixR.ColumnCount, Tau, dinput.Values, 1, dresult.Values, QrMethod);
+            Control.LinearAlgebraProvider.QRSolveFactored(((DenseMatrix)Q).Values, ((DenseMatrix)MatrixR).Values, Q.RowCount, MatrixR.ColumnCount, Tau, dinput.Values, 1, dresult.Values, QrMethod);
         }
     }
 }

src/Numerics/LinearAlgebra/Double/Factorization/DenseSvd.cs

@@ -66,10 +66,10 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
 
             ComputeVectors = computeVectors;
             var nm = Math.Min(matrix.RowCount, matrix.ColumnCount);
-            VectorS = new DenseVector(nm);
-            MatrixU = new DenseMatrix(matrix.RowCount);
-            MatrixVT = new DenseMatrix(matrix.ColumnCount);
-            Control.LinearAlgebraProvider.SingularValueDecomposition(computeVectors, ((DenseMatrix)matrix.Clone()).Values, matrix.RowCount, matrix.ColumnCount, ((DenseVector)VectorS).Values, ((DenseMatrix)MatrixU).Values, ((DenseMatrix)MatrixVT).Values);
+            S = new DenseVector(nm);
+            U = new DenseMatrix(matrix.RowCount);
+            VT = new DenseMatrix(matrix.ColumnCount);
+            Control.LinearAlgebraProvider.SingularValueDecomposition(computeVectors, ((DenseMatrix)matrix.Clone()).Values, matrix.RowCount, matrix.ColumnCount, ((DenseVector)S).Values, ((DenseMatrix)U).Values, ((DenseMatrix)VT).Values);
         }
 
         /// <summary>
@@ -102,13 +102,13 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixU.RowCount != input.RowCount)
+            if (U.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (MatrixVT.ColumnCount != result.RowCount)
+            if (VT.ColumnCount != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
@@ -125,7 +125,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 throw new NotSupportedException("Can only do SVD factorization for dense matrices at the moment.");
             }
 
-            Control.LinearAlgebraProvider.SvdSolveFactored(MatrixU.RowCount, MatrixVT.ColumnCount, ((DenseVector)VectorS).Values, ((DenseMatrix)MatrixU).Values, ((DenseMatrix)MatrixVT).Values, dinput.Values, input.ColumnCount, dresult.Values);
+            Control.LinearAlgebraProvider.SvdSolveFactored(U.RowCount, VT.ColumnCount, ((DenseVector)S).Values, ((DenseMatrix)U).Values, ((DenseMatrix)VT).Values, dinput.Values, input.ColumnCount, dresult.Values);
         }
 
         /// <summary>
@@ -152,15 +152,15 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixU.RowCount != input.Count)
+            if (U.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (MatrixVT.ColumnCount != result.Count)
+            if (VT.ColumnCount != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(MatrixVT, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(VT, result);
             }
 
             var dinput = input as DenseVector;
@@ -175,7 +175,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 throw new NotSupportedException("Can only do SVD factorization for dense vectors at the moment.");
             }
 
-            Control.LinearAlgebraProvider.SvdSolveFactored(MatrixU.RowCount, MatrixVT.ColumnCount, ((DenseVector)VectorS).Values, ((DenseMatrix)MatrixU).Values, ((DenseMatrix)MatrixVT).Values, dinput.Values, 1, dresult.Values);
+            Control.LinearAlgebraProvider.SvdSolveFactored(U.RowCount, VT.ColumnCount, ((DenseVector)S).Values, ((DenseMatrix)U).Values, ((DenseMatrix)VT).Values, dinput.Values, 1, dresult.Values);
         }
     }
 }

src/Numerics/LinearAlgebra/Double/Factorization/Evd.cs

@@ -59,11 +59,11 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             get
             {
                 var det = Complex.One;
-                for (var i = 0; i < VectorEv.Count; i++)
+                for (var i = 0; i < EigenValues.Count; i++)
                 {
-                    det *= VectorEv[i];
+                    det *= EigenValues[i];
 
-                    if (VectorEv[i].AlmostEqual(Complex.Zero))
+                    if (EigenValues[i].AlmostEqual(Complex.Zero))
                     {
                         return 0;
                     }
@@ -82,9 +82,9 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             get
             {
                 var rank = 0;
-                for (var i = 0; i < VectorEv.Count; i++)
+                for (var i = 0; i < EigenValues.Count; i++)
                 {
-                    if (VectorEv[i].AlmostEqual(Complex.Zero))
+                    if (EigenValues[i].AlmostEqual(Complex.Zero))
                     {
                         continue;
                     }
@@ -104,9 +104,9 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
         {
             get
             {
-                for (var i = 0; i < VectorEv.Count; i++)
+                for (var i = 0; i < EigenValues.Count; i++)
                 {
-                    if (VectorEv[i].AlmostEqual(Complex.Zero))
+                    if (EigenValues[i].AlmostEqual(Complex.Zero))
                     {
                         return false;
                     }

src/Numerics/LinearAlgebra/Double/Factorization/Svd.cs

@@ -59,7 +59,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
         {
             get
             {
-                return VectorS.Count(t => !Math.Abs(t).AlmostEqual(0.0));
+                return S.Count(t => !Math.Abs(t).AlmostEqual(0.0));
             }
         }
 
@@ -71,7 +71,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
         {
             get
             {
-                return Math.Abs(VectorS[0]);
+                return Math.Abs(S[0]);
             }
         }
 
@@ -83,8 +83,8 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
         {
             get
             {
-                var tmp = Math.Min(MatrixU.RowCount, MatrixVT.ColumnCount) - 1;
-                return Math.Abs(VectorS[0]) / Math.Abs(VectorS[tmp]);
+                var tmp = Math.Min(U.RowCount, VT.ColumnCount) - 1;
+                return Math.Abs(S[0]) / Math.Abs(S[tmp]);
             }
         }
 
@@ -95,13 +95,13 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
         {
             get
             {
-                if (MatrixU.RowCount != MatrixVT.ColumnCount)
+                if (U.RowCount != VT.ColumnCount)
                 {
                     throw new ArgumentException(Resources.ArgumentMatrixSquare);
                 }
 
                 var det = 1.0;
-                foreach (var value in VectorS)
+                foreach (var value in S)
                 {
                     det *= value;
                     if (Math.Abs(value).AlmostEqual(0.0))

src/Numerics/LinearAlgebra/Double/Factorization/UserCholesky.cs

@@ -66,40 +66,40 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             }
 
             // Create a new matrix for the Cholesky factor, then perform factorization (while overwriting).
-            CholeskyFactor = matrix.Clone();
-            var tmpColumn = new double[CholeskyFactor.RowCount];
+            Factor = matrix.Clone();
+            var tmpColumn = new double[Factor.RowCount];
 
             // Main loop - along the diagonal
-            for (var ij = 0; ij < CholeskyFactor.RowCount; ij++)
+            for (var ij = 0; ij < Factor.RowCount; ij++)
             {
                 // "Pivot" element
-                var tmpVal = CholeskyFactor.At(ij, ij);
+                var tmpVal = Factor.At(ij, ij);
 
                 if (tmpVal > 0.0)
                 {
                     tmpVal = Math.Sqrt(tmpVal);
-                    CholeskyFactor.At(ij, ij, tmpVal);
+                    Factor.At(ij, ij, tmpVal);
                     tmpColumn[ij] = tmpVal;
 
                     // Calculate multipliers and copy to local column
                     // Current column, below the diagonal
-                    for (var i = ij + 1; i < CholeskyFactor.RowCount; i++)
+                    for (var i = ij + 1; i < Factor.RowCount; i++)
                     {
-                        CholeskyFactor.At(i, ij, CholeskyFactor.At(i, ij) / tmpVal);
-                        tmpColumn[i] = CholeskyFactor.At(i, ij);
+                        Factor.At(i, ij, Factor.At(i, ij) / tmpVal);
+                        tmpColumn[i] = Factor.At(i, ij);
                     }
 
                     // Remaining columns, below the diagonal
-                    DoCholeskyStep(CholeskyFactor, CholeskyFactor.RowCount, ij + 1, CholeskyFactor.RowCount, tmpColumn, Control.NumberOfParallelWorkerThreads);
+                    DoCholeskyStep(Factor, Factor.RowCount, ij + 1, Factor.RowCount, tmpColumn, Control.NumberOfParallelWorkerThreads);
                 }
                 else
                 {
                     throw new ArgumentException(Resources.ArgumentMatrixPositiveDefinite);
                 }
 
-                for (var i = ij + 1; i < CholeskyFactor.RowCount; i++)
+                for (var i = ij + 1; i < Factor.RowCount; i++)
                 {
-                    CholeskyFactor.At(ij, i, 0.0);
+                    Factor.At(ij, i, 0.0);
                 }
             }
         }
@@ -167,13 +167,13 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
-            if (input.RowCount != CholeskyFactor.RowCount)
+            if (input.RowCount != Factor.RowCount)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(input, CholeskyFactor);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(input, Factor);
             }
 
             input.CopyTo(result);
-            var order = CholeskyFactor.RowCount;
+            var order = Factor.RowCount;
 
             for (var c = 0; c < result.ColumnCount; c++)
             {
@@ -184,10 +184,10 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                     sum = result.At(i, c);
                     for (var k = i - 1; k >= 0; k--)
                     {
-                        sum -= CholeskyFactor.At(i, k) * result.At(k, c);
+                        sum -= Factor.At(i, k) * result.At(k, c);
                     }
 
-                    result.At(i, c, sum / CholeskyFactor.At(i, i));
+                    result.At(i, c, sum / Factor.At(i, i));
                 }
 
                 // Solve L'*X = Y;
@@ -196,10 +196,10 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                     sum = result.At(i, c);
                     for (var k = i + 1; k < order; k++)
                     {
-                        sum -= CholeskyFactor.At(k, i) * result.At(k, c);
+                        sum -= Factor.At(k, i) * result.At(k, c);
                     }
 
-                    result.At(i, c, sum / CholeskyFactor.At(i, i));
+                    result.At(i, c, sum / Factor.At(i, i));
                 }
             }
         }
@@ -228,13 +228,13 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
-            if (input.Count != CholeskyFactor.RowCount)
+            if (input.Count != Factor.RowCount)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(input, CholeskyFactor);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(input, Factor);
             }
 
             input.CopyTo(result);
-            var order = CholeskyFactor.RowCount;
+            var order = Factor.RowCount;
 
             // Solve L*Y = B;
             double sum;
@@ -243,10 +243,10 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 sum = result[i];
                 for (var k = i - 1; k >= 0; k--)
                 {
-                    sum -= CholeskyFactor.At(i, k) * result[k];
+                    sum -= Factor.At(i, k) * result[k];
                 }
 
-                result[i] = sum / CholeskyFactor.At(i, i);
+                result[i] = sum / Factor.At(i, i);
             }
 
             // Solve L'*X = Y;
@@ -255,10 +255,10 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 sum = result[i];
                 for (var k = i + 1; k < order; k++)
                 {
-                    sum -= CholeskyFactor.At(k, i) * result[k];
+                    sum -= Factor.At(k, i) * result[k];
                 }
 
-                result[i] = sum / CholeskyFactor.At(i, i);
+                result[i] = sum / Factor.At(i, i);
             }
         }
     }

src/Numerics/LinearAlgebra/Double/Factorization/UserEvd.cs

@@ -79,9 +79,9 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             var order = matrix.RowCount;
 
             // Initialize matricies for eigenvalues and eigenvectors
-            MatrixEv = matrix.CreateMatrix(order, order);
-            MatrixD = matrix.CreateMatrix(order, order);
-            VectorEv = new LinearAlgebra.Complex.DenseVector(order);
+            EigenVectors = matrix.CreateMatrix(order, order);
+            D = matrix.CreateMatrix(order, order);
+            EigenValues = new LinearAlgebra.Complex.DenseVector(order);
            
             IsSymmetric = true;
 
@@ -98,8 +98,8 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
 
             if (IsSymmetric)
             {
-                matrix.CopyTo(MatrixEv);
-                d = MatrixEv.Row(order - 1).ToArray();
+                matrix.CopyTo(EigenVectors);
+                d = EigenVectors.Row(order - 1).ToArray();
 
                 SymmetricTridiagonalize(d, e, order);
                 SymmetricDiagonalize(d, e, order);
@@ -114,21 +114,21 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
 
             for (var i = 0; i < order; i++)
             {
-                MatrixD.At(i, i, d[i]);
+                D.At(i, i, d[i]);
 
                 if (e[i] > 0)
                 {
-                    MatrixD.At(i, i + 1, e[i]);
+                    D.At(i, i + 1, e[i]);
                 }
                 else if (e[i] < 0)
                 {
-                    MatrixD.At(i, i - 1, e[i]);
+                    D.At(i, i - 1, e[i]);
                 }
             }
 
             for (var i = 0; i < order; i++)
             {
-                VectorEv[i] = new Complex(d[i], e[i]);
+                EigenValues[i] = new Complex(d[i], e[i]);
             }
         }
 
@@ -161,9 +161,9 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                     e[i] = d[i - 1];
                     for (var j = 0; j < i; j++)
                     {
-                        d[j] = MatrixEv.At(i - 1, j);
-                        MatrixEv.At(i, j, 0.0);
-                        MatrixEv.At(j, i, 0.0);
+                        d[j] = EigenVectors.At(i - 1, j);
+                        EigenVectors.At(i, j, 0.0);
+                        EigenVectors.At(j, i, 0.0);
                     }
                 }
                 else
@@ -195,13 +195,13 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                     for (var j = 0; j < i; j++)
                     {
                         f = d[j];
-                        MatrixEv.At(j, i, f);
-                        g = e[j] + (MatrixEv.At(j, j) * f);
+                        EigenVectors.At(j, i, f);
+                        g = e[j] + (EigenVectors.At(j, j) * f);
 
                         for (var k = j + 1; k <= i - 1; k++)
                         {
-                            g += MatrixEv.At(k, j) * d[k];
-                            e[k] += MatrixEv.At(k, j) * f;
+                            g += EigenVectors.At(k, j) * d[k];
+                            e[k] += EigenVectors.At(k, j) * f;
                         }
 
                         e[j] = g;
@@ -229,11 +229,11 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
 
                         for (var k = j; k <= i - 1; k++)
                         {
-                            MatrixEv.At(k, j, MatrixEv.At(k, j) - (f * e[k]) - (g * d[k]));
+                            EigenVectors.At(k, j, EigenVectors.At(k, j) - (f * e[k]) - (g * d[k]));
                         }
 
-                        d[j] = MatrixEv.At(i - 1, j);
-                        MatrixEv.At(i, j, 0.0);
+                        d[j] = EigenVectors.At(i - 1, j);
+                        EigenVectors.At(i, j, 0.0);
                     }
                 }
 
@@ -243,14 +243,14 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             // Accumulate transformations.
             for (var i = 0; i < order - 1; i++)
             {
-                MatrixEv.At(order - 1, i, MatrixEv.At(i, i));
-                MatrixEv.At(i, i, 1.0);
+                EigenVectors.At(order - 1, i, EigenVectors.At(i, i));
+                EigenVectors.At(i, i, 1.0);
                 var h = d[i + 1];
                 if (h != 0.0)
                 {
                     for (var k = 0; k <= i; k++)
                     {
-                        d[k] = MatrixEv.At(k, i + 1) / h;
+                        d[k] = EigenVectors.At(k, i + 1) / h;
                     }
 
                     for (var j = 0; j <= i; j++)
@@ -258,29 +258,29 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                         var g = 0.0;
                         for (var k = 0; k <= i; k++)
                         {
-                            g += MatrixEv.At(k, i + 1) * MatrixEv.At(k, j);
+                            g += EigenVectors.At(k, i + 1) * EigenVectors.At(k, j);
                         }
 
                         for (var k = 0; k <= i; k++)
                         {
-                            MatrixEv.At(k, j, MatrixEv.At(k, j) - g * d[k]);
+                            EigenVectors.At(k, j, EigenVectors.At(k, j) - g * d[k]);
                         }
                     }
                 }
 
                 for (var k = 0; k <= i; k++)
                 {
-                    MatrixEv.At(k, i + 1, 0.0);
+                    EigenVectors.At(k, i + 1, 0.0);
                 }
             }
 
             for (var j = 0; j < order; j++)
             {
-                d[j] = MatrixEv.At(order - 1, j);
-                MatrixEv.At(order - 1, j, 0.0);
+                d[j] = EigenVectors.At(order - 1, j);
+                EigenVectors.At(order - 1, j, 0.0);
             }
 
-            MatrixEv.At(order - 1, order - 1, 1.0);
+            EigenVectors.At(order - 1, order - 1, 1.0);
             e[0] = 0.0;
         }
 
@@ -379,9 +379,9 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                             // Accumulate transformation.
                             for (var k = 0; k < order; k++)
                             {
-                                h = MatrixEv.At(k, i + 1);
-                                MatrixEv.At(k, i + 1, (s * MatrixEv.At(k, i)) + (c * h));
-                                MatrixEv.At(k, i, (c * MatrixEv.At(k, i)) - (s * h));
+                                h = EigenVectors.At(k, i + 1);
+                                EigenVectors.At(k, i + 1, (s * EigenVectors.At(k, i)) + (c * h));
+                                EigenVectors.At(k, i, (c * EigenVectors.At(k, i)) - (s * h));
                             }
                         }
 
@@ -423,9 +423,9 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                     d[i] = p;
                     for (var j = 0; j < order; j++)
                     {
-                        p = MatrixEv.At(j, i);
-                        MatrixEv.At(j, i, MatrixEv.At(j, k));
-                        MatrixEv.At(j, k, p);
+                        p = EigenVectors.At(j, i);
+                        EigenVectors.At(j, i, EigenVectors.At(j, k));
+                        EigenVectors.At(j, k, p);
                     }
                 }
             }
@@ -514,7 +514,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             {
                 for (var j = 0; j < order; j++)
                 {
-                    MatrixEv.At(i, j, i == j ? 1.0 : 0.0);
+                    EigenVectors.At(i, j, i == j ? 1.0 : 0.0);
                 }
             }
 
@@ -532,14 +532,14 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                         var g = 0.0;
                         for (var i = m; i < order; i++)
                         {
-                            g += ort[i] * MatrixEv.At(i, j);
+                            g += ort[i] * EigenVectors.At(i, j);
                         }
 
                         // Double division avoids possible underflow
                         g = (g / ort[m]) / matrixH[m, m - 1];
                         for (var i = m; i < order; i++)
                         {
-                            MatrixEv.At(i, j, MatrixEv.At(i, j) + g * ort[i]);
+                            EigenVectors.At(i, j, EigenVectors.At(i, j) + g * ort[i]);
                         }
                     }
                 }
@@ -669,9 +669,9 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                         // Accumulate transformations
                         for (var i = 0; i < order; i++)
                         {
-                            z = MatrixEv.At(i, n - 1);
-                            MatrixEv.At(i, n - 1, (q * z) + (p * MatrixEv.At(i, n)));
-                            MatrixEv.At(i, n, (q * MatrixEv.At(i, n)) - (p * z));
+                            z = EigenVectors.At(i, n - 1);
+                            EigenVectors.At(i, n - 1, (q * z) + (p * EigenVectors.At(i, n)));
+                            EigenVectors.At(i, n, (q * EigenVectors.At(i, n)) - (p * z));
                         }
 
                         // Complex pair
@@ -859,16 +859,16 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                             // Accumulate transformations
                             for (var i = 0; i < order; i++)
                             {
-                                p = (x * MatrixEv.At(i, k)) + (y * MatrixEv.At(i, k + 1));
+                                p = (x * EigenVectors.At(i, k)) + (y * EigenVectors.At(i, k + 1));
 
                                 if (notlast)
                                 {
-                                    p = p + (z * MatrixEv.At(i, k + 2));
-                                    MatrixEv.At(i, k + 2, MatrixEv.At(i, k + 2) - (p * r));
+                                    p = p + (z * EigenVectors.At(i, k + 2));
+                                    EigenVectors.At(i, k + 2, EigenVectors.At(i, k + 2) - (p * r));
                                 }
 
-                                MatrixEv.At(i, k, MatrixEv.At(i, k) - p);
-                                MatrixEv.At(i, k + 1, MatrixEv.At(i, k + 1) - (p * q));
+                                EigenVectors.At(i, k, EigenVectors.At(i, k) - p);
+                                EigenVectors.At(i, k + 1, EigenVectors.At(i, k + 1) - (p * q));
                             }
                         } // (s != 0)
                     } // k loop
@@ -1052,10 +1052,10 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                     z = 0.0;
                     for (var k = 0; k <= j; k++)
                     {
-                        z = z + (MatrixEv.At(i, k) * matrixH[k, j]);
+                        z = z + (EigenVectors.At(i, k) * matrixH[k, j]);
                     }
 
-                    MatrixEv.At(i, j, z);
+                    EigenVectors.At(i, j, z);
                 }
             }
         }
@@ -1103,20 +1103,20 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (VectorEv.Count != input.RowCount)
+            if (EigenValues.Count != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (VectorEv.Count != result.RowCount)
+            if (EigenValues.Count != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
             if (IsSymmetric)
             {
-                var order = VectorEv.Count;
+                var order = EigenValues.Count;
                 var tmp = new double[order];
 
                 for (var k = 0; k < order; k++)
@@ -1128,10 +1128,10 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                         {
                             for (var i = 0; i < order; i++)
                             {
-                                value += MatrixEv.At(i, j) * input.At(i, k);
+                                value += EigenVectors.At(i, j) * input.At(i, k);
                             }
 
-                            value /= VectorEv[j].Real;
+                            value /= EigenValues[j].Real;
                         }
 
                         tmp[j] = value;
@@ -1142,7 +1142,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                         double value = 0;
                         for (var i = 0; i < order; i++)
                         {
-                            value += MatrixEv.At(j, i) * tmp[i];
+                            value += EigenVectors.At(j, i) * tmp[i];
                         }
 
                         result.At(j, k, value);
@@ -1174,13 +1174,13 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
 
             // Ax=b where A is an m x m matrix
             // Check that b is a column vector with m entries
-            if (VectorEv.Count != input.Count)
+            if (EigenValues.Count != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (VectorEv.Count != result.Count)
+            if (EigenValues.Count != result.Count)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixDimensions);
             }
@@ -1188,7 +1188,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             if (IsSymmetric)
             {
                 // Symmetric case -> x = V * inv(λ) * VT * b;
-                var order = VectorEv.Count;
+                var order = EigenValues.Count;
                 var tmp = new double[order];
                 double value;
 
@@ -1199,10 +1199,10 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                     {
                         for (var i = 0; i < order; i++)
                         {
-                            value += MatrixEv.At(i, j) * input[i];
+                            value += EigenVectors.At(i, j) * input[i];
                         }
 
-                        value /= VectorEv[j].Real;
+                        value /= EigenValues[j].Real;
                     }
 
                     tmp[j] = value;
@@ -1213,7 +1213,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                     value = 0;
                     for (int i = 0; i < order; i++)
                     {
-                        value += MatrixEv.At(j, i) * tmp[i];
+                        value += EigenVectors.At(j, i) * tmp[i];
                     }
 
                     result[j] = value;

src/Numerics/LinearAlgebra/Double/Factorization/UserGramSchmidt.cs

@@ -62,31 +62,31 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 throw Matrix.DimensionsDontMatch<ArgumentException>(matrix);
             }
 
-            MatrixQ = matrix.Clone();
+            Q = matrix.Clone();
             MatrixR = matrix.CreateMatrix(matrix.ColumnCount, matrix.ColumnCount);
 
-            for (var k = 0; k < MatrixQ.ColumnCount; k++)
+            for (var k = 0; k < Q.ColumnCount; k++)
             {
-                var norm = MatrixQ.Column(k).L2Norm();
+                var norm = Q.Column(k).L2Norm();
                 if (norm == 0.0)
                 {
                     throw new ArgumentException(Resources.ArgumentMatrixNotRankDeficient);
                 }
 
                 MatrixR.At(k, k, norm);
-                for (var i = 0; i < MatrixQ.RowCount; i++)
+                for (var i = 0; i < Q.RowCount; i++)
                 {
-                    MatrixQ.At(i, k, MatrixQ.At(i, k) / norm);
+                    Q.At(i, k, Q.At(i, k) / norm);
                 }
 
-                for (var j = k + 1; j < MatrixQ.ColumnCount; j++)
+                for (var j = k + 1; j < Q.ColumnCount; j++)
                 {
-                    var dot = MatrixQ.Column(k).DotProduct(MatrixQ.Column(j));
+                    var dot = Q.Column(k).DotProduct(Q.Column(j));
                     MatrixR.At(k, j, dot);
-                    for (var i = 0; i < MatrixQ.RowCount; i++)
+                    for (var i = 0; i < Q.RowCount; i++)
                     {
-                        var value = MatrixQ.At(i, j) - (MatrixQ.At(i, k) * dot);
-                        MatrixQ.At(i, j, value);
+                        var value = Q.At(i, j) - (Q.At(i, k) * dot);
+                        Q.At(i, j, value);
                     }
                 }
             }
@@ -117,13 +117,13 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixQ.RowCount != input.RowCount)
+            if (Q.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (MatrixQ.ColumnCount != result.RowCount)
+            if (Q.ColumnCount != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
@@ -131,20 +131,20 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             var inputCopy = input.Clone();
             
             // Compute Y = transpose(Q)*B
-            var column = new double[MatrixQ.RowCount];
+            var column = new double[Q.RowCount];
             for (var j = 0; j < input.ColumnCount; j++)
             {
-                for (var k = 0; k < MatrixQ.RowCount; k++)
+                for (var k = 0; k < Q.RowCount; k++)
                 {
                     column[k] = inputCopy.At(k, j);
                 }
 
-                for (var i = 0; i < MatrixQ.ColumnCount; i++)
+                for (var i = 0; i < Q.ColumnCount; i++)
                 {
                     double s = 0;
-                    for (var k = 0; k < MatrixQ.RowCount; k++)
+                    for (var k = 0; k < Q.RowCount; k++)
                     {
-                        s += MatrixQ.At(k, i) * column[k];
+                        s += Q.At(k, i) * column[k];
                     }
 
                     inputCopy.At(i, j, s);
@@ -152,7 +152,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             }
 
             // Solve R*X = Y;
-            for (var k = MatrixQ.ColumnCount - 1; k >= 0; k--)
+            for (var k = Q.ColumnCount - 1; k >= 0; k--)
             {
                 for (var j = 0; j < input.ColumnCount; j++)
                 {
@@ -196,39 +196,39 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixQ.RowCount != input.Count)
+            if (Q.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (MatrixQ.ColumnCount != result.Count)
+            if (Q.ColumnCount != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(MatrixQ, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(Q, result);
             }
 
             var inputCopy = input.Clone();
 
             // Compute Y = transpose(Q)*B
-            var column = new double[MatrixQ.RowCount];
-            for (var k = 0; k < MatrixQ.RowCount; k++)
+            var column = new double[Q.RowCount];
+            for (var k = 0; k < Q.RowCount; k++)
             {
                 column[k] = inputCopy[k];
             }
 
-            for (var i = 0; i < MatrixQ.ColumnCount; i++)
+            for (var i = 0; i < Q.ColumnCount; i++)
             {
                 double s = 0;
-                for (var k = 0; k < MatrixQ.RowCount; k++)
+                for (var k = 0; k < Q.RowCount; k++)
                 {
-                    s += MatrixQ.At(k, i) * column[k];
+                    s += Q.At(k, i) * column[k];
                 }
 
                 inputCopy[i] = s;
             }
 
             // Solve R*X = Y;
-            for (var k = MatrixQ.ColumnCount - 1; k >= 0; k--)
+            for (var k = Q.ColumnCount - 1; k >= 0; k--)
             {
                 inputCopy[k] /= MatrixR.At(k, k);
                 for (var i = 0; i < k; i++)

src/Numerics/LinearAlgebra/Double/Factorization/UserQR.cs

@@ -73,11 +73,11 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             if (method == QRMethod.Full)
             {
                 MatrixR = matrix.Clone();
-                MatrixQ = matrix.CreateMatrix(matrix.RowCount, matrix.RowCount);
+                Q = matrix.CreateMatrix(matrix.RowCount, matrix.RowCount);
 
                 for (var i = 0; i < matrix.RowCount; i++)
                 {
-                    MatrixQ.At(i, i, 1.0);
+                    Q.At(i, i, 1.0);
                 }
 
                 for (var i = 0; i < minmn; i++)
@@ -89,33 +89,33 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
 
                 for (var i = minmn - 1; i >= 0; i--)
                 {
-                    ComputeQR(u[i], MatrixQ, i, matrix.RowCount, i, matrix.RowCount,
+                    ComputeQR(u[i], Q, i, matrix.RowCount, i, matrix.RowCount,
                               Control.NumberOfParallelWorkerThreads);
                 }
             }
             else
             {
                 MatrixR = matrix.CreateMatrix(matrix.ColumnCount, matrix.ColumnCount);
-                MatrixQ = matrix.Clone();
+                Q = matrix.Clone();
 
                 for (var i = 0; i < minmn; i++)
                 {
-                    u[i] = GenerateColumn(MatrixQ, i, i);
-                    ComputeQR(u[i], MatrixQ, i, matrix.RowCount, i + 1, matrix.ColumnCount,
+                    u[i] = GenerateColumn(Q, i, i);
+                    ComputeQR(u[i], Q, i, matrix.RowCount, i + 1, matrix.ColumnCount,
                               Control.NumberOfParallelWorkerThreads);
                 }
 
-                MatrixR = MatrixQ.SubMatrix(0, matrix.ColumnCount, 0, matrix.ColumnCount);
-                MatrixQ.Clear();
+                MatrixR = Q.SubMatrix(0, matrix.ColumnCount, 0, matrix.ColumnCount);
+                Q.Clear();
                 
                 for (var i = 0; i < matrix.ColumnCount; i++)
                 {
-                    MatrixQ.At(i, i, 1.0);
+                    Q.At(i, i, 1.0);
                 }
                 
                 for (var i = minmn - 1; i >= 0; i--)
                 {
-                    ComputeQR(u[i], MatrixQ, i, matrix.RowCount, i, matrix.ColumnCount,
+                    ComputeQR(u[i], Q, i, matrix.RowCount, i, matrix.ColumnCount,
                               Control.NumberOfParallelWorkerThreads);
                 }
 
@@ -272,7 +272,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                     double s = 0;
                     for (var k = 0; k < MatrixR.RowCount; k++)
                     {
-                        s += MatrixQ.At(k, i) * column[k];
+                        s += Q.At(k, i) * column[k];
                     }
 
                     inputCopy.At(i, j, s);
@@ -349,7 +349,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 double s = 0;
                 for (var k = 0; k < MatrixR.RowCount; k++)
                 {
-                    s += MatrixQ.At(k, i) * column[k];
+                    s += Q.At(k, i) * column[k];
                 }
 
                 inputCopy[i] = s;

src/Numerics/LinearAlgebra/Double/Factorization/UserSvd.cs

@@ -68,9 +68,9 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             var nm = Math.Min(matrix.RowCount + 1, matrix.ColumnCount);
             var matrixCopy = matrix.Clone();
 
-            VectorS = matrixCopy.CreateVector(nm);
-            MatrixU = matrixCopy.CreateMatrix(matrixCopy.RowCount, matrixCopy.RowCount);
-            MatrixVT = matrixCopy.CreateMatrix(matrixCopy.ColumnCount, matrixCopy.ColumnCount);
+            S = matrixCopy.CreateVector(nm);
+            U = matrixCopy.CreateMatrix(matrixCopy.RowCount, matrixCopy.RowCount);
+            VT = matrixCopy.CreateMatrix(matrixCopy.ColumnCount, matrixCopy.ColumnCount);
 
             const int maxiter = 1000;
             var e = new double[matrixCopy.ColumnCount];
@@ -94,26 +94,26 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 {
                     // Compute the transformation for the l-th column and place the l-th diagonal in VectorS[l].
                     var xnorm = Dnrm2Column(matrixCopy, matrixCopy.RowCount, l, l);
-                    VectorS[l] = xnorm;
-                    if (VectorS[l] != 0.0)
+                    S[l] = xnorm;
+                    if (S[l] != 0.0)
                     {
                         if (matrixCopy.At(l, l) != 0.0)
                         {
-                            VectorS[l] = Dsign(VectorS[l], matrixCopy.At(l, l));
+                            S[l] = Dsign(S[l], matrixCopy.At(l, l));
                         }
 
-                        DscalColumn(matrixCopy, matrixCopy.RowCount, l, l, 1.0 / VectorS[l]);
+                        DscalColumn(matrixCopy, matrixCopy.RowCount, l, l, 1.0 / S[l]);
                         matrixCopy.At(l, l, (1.0 + matrixCopy.At(l, l)));
                     }
 
-                    VectorS[l] = -VectorS[l];
+                    S[l] = -S[l];
                 }
 
                 for (j = lp1; j < matrixCopy.ColumnCount; j++)
                 {
                     if (l < nct)
                     {
-                        if (VectorS[l] != 0.0)
+                        if (S[l] != 0.0)
                         {
                             // Apply the transformation.
                             t = -Ddot(matrixCopy, matrixCopy.RowCount, l, j, l) / matrixCopy.At(l, l);
@@ -134,7 +134,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                     // Place the transformation in u for subsequent back multiplication.
                     for (i = l; i < matrixCopy.RowCount; i++)
                     {
-                        MatrixU.At(i, l, matrixCopy.At(i, l));
+                        U.At(i, l, matrixCopy.At(i, l));
                     }
                 }
 
@@ -189,7 +189,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                     // Place the transformation in v for subsequent back multiplication.
                     for (i = lp1; i < matrixCopy.ColumnCount; i++)
                     {
-                        MatrixVT.At(i, l, e[i]);
+                        VT.At(i, l, e[i]);
                     }
                 }
             }
@@ -200,12 +200,12 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             var nrtp1 = nrt + 1;
             if (nct < matrixCopy.ColumnCount)
             {
-                VectorS[nctp1 - 1] = matrixCopy.At((nctp1 - 1), (nctp1 - 1));
+                S[nctp1 - 1] = matrixCopy.At((nctp1 - 1), (nctp1 - 1));
             }
 
             if (matrixCopy.RowCount < m)
             {
-                VectorS[m - 1] = 0.0;
+                S[m - 1] = 0.0;
             }
 
             if (nrtp1 < m)
@@ -222,40 +222,40 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 {
                     for (i = 0; i < matrixCopy.RowCount; i++)
                     {
-                        MatrixU.At(i, j, 0.0);
+                        U.At(i, j, 0.0);
                     }
 
-                    MatrixU.At(j, j, 1.0);
+                    U.At(j, j, 1.0);
                 }
 
                 for (l = nct - 1; l >= 0; l--)
                 {
-                    if (VectorS[l] != 0.0)
+                    if (S[l] != 0.0)
                     {
                         for (j = l + 1; j < ncu; j++)
                         {
-                            t = -Ddot(MatrixU, matrixCopy.RowCount, l, j, l) / MatrixU.At(l, l);
+                            t = -Ddot(U, matrixCopy.RowCount, l, j, l) / U.At(l, l);
                             for (var ii = l; ii < matrixCopy.RowCount; ii++)
                             {
-                                MatrixU.At(ii, j, MatrixU.At(ii, j) + (t * MatrixU.At(ii, l)));
+                                U.At(ii, j, U.At(ii, j) + (t * U.At(ii, l)));
                             }
                         }
 
-                        DscalColumn(MatrixU, matrixCopy.RowCount, l, l, -1.0);
-                        MatrixU.At(l, l, 1.0 + MatrixU.At(l, l));
+                        DscalColumn(U, matrixCopy.RowCount, l, l, -1.0);
+                        U.At(l, l, 1.0 + U.At(l, l));
                         for (i = 0; i < l; i++)
                         {
-                            MatrixU.At(i, l, 0.0);
+                            U.At(i, l, 0.0);
                         }
                     }
                     else
                     {
                         for (i = 0; i < matrixCopy.RowCount; i++)
                         {
-                            MatrixU.At(i, l, 0.0);
+                            U.At(i, l, 0.0);
                         }
 
-                        MatrixU.At(l, l, 1.0);
+                        U.At(l, l, 1.0);
                     }
                 }
             }
@@ -272,10 +272,10 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                         {
                             for (j = lp1; j < matrixCopy.ColumnCount; j++)
                             {
-                                t = -Ddot(MatrixVT, matrixCopy.ColumnCount, l, j, lp1) / MatrixVT.At(lp1, l);
+                                t = -Ddot(VT, matrixCopy.ColumnCount, l, j, lp1) / VT.At(lp1, l);
                                 for (var ii = l; ii < matrixCopy.ColumnCount; ii++)
                                 {
-                                    MatrixVT.At(ii, j, MatrixVT.At(ii, j) + (t * MatrixVT.At(ii, l)));
+                                    VT.At(ii, j, VT.At(ii, j) + (t * VT.At(ii, l)));
                                 }
                             }
                         }
@@ -283,10 +283,10 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
 
                     for (i = 0; i < matrixCopy.ColumnCount; i++)
                     {
-                        MatrixVT.At(i, l, 0.0);
+                        VT.At(i, l, 0.0);
                     }
 
-                    MatrixVT.At(l, l, 1.0);
+                    VT.At(l, l, 1.0);
                 }
             }
 
@@ -294,11 +294,11 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             for (i = 0; i < m; i++)
             {
                 double r;
-                if (VectorS[i] != 0.0)
+                if (S[i] != 0.0)
                 {
-                    t = VectorS[i];
-                    r = VectorS[i] / t;
-                    VectorS[i] = t;
+                    t = S[i];
+                    r = S[i] / t;
+                    S[i] = t;
                     if (i < m - 1)
                     {
                         e[i] = e[i] / r;
@@ -306,7 +306,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
 
                     if (ComputeVectors)
                     {
-                        DscalColumn(MatrixU, matrixCopy.RowCount, i, 0, r);
+                        DscalColumn(U, matrixCopy.RowCount, i, 0, r);
                     }
                 }
 
@@ -321,10 +321,10 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                     t = e[i];
                     r = t / e[i];
                     e[i] = t;
-                    VectorS[i + 1] = VectorS[i + 1] * r;
+                    S[i + 1] = S[i + 1] * r;
                     if (ComputeVectors)
                     {
-                        DscalColumn(MatrixVT, matrixCopy.ColumnCount, i + 1, 0, r);
+                        DscalColumn(VT, matrixCopy.ColumnCount, i + 1, 0, r);
                     }
                 }
             }
@@ -352,7 +352,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 double test;
                 for (l = m - 2; l >= 0; l--)
                 {
-                    test = Math.Abs(VectorS[l]) + Math.Abs(VectorS[l + 1]);
+                    test = Math.Abs(S[l]) + Math.Abs(S[l + 1]);
                     ztest = test + Math.Abs(e[l]);
                     if (ztest.AlmostEqualInDecimalPlaces(test, 15))
                     {
@@ -382,10 +382,10 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                             test = test + Math.Abs(e[ls - 1]);
                         }
 
-                        ztest = test + Math.Abs(VectorS[ls]);
+                        ztest = test + Math.Abs(S[ls]);
                         if (ztest.AlmostEqualInDecimalPlaces(test, 15))
                         {
-                            VectorS[ls] = 0.0;
+                            S[ls] = 0.0;
                             break;
                         }
                     }
@@ -422,9 +422,9 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                         for (var kk = l; kk < m - 1; kk++)
                         {
                             k = m - 2 - kk + l;
-                            t1 = VectorS[k];
+                            t1 = S[k];
                             Drotg(ref t1, ref f, out cs, out sn);
-                            VectorS[k] = t1;
+                            S[k] = t1;
                             if (k != l)
                             {
                                 f = -sn * e[k - 1];
@@ -433,7 +433,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
 
                             if (ComputeVectors)
                             {
-                                Drot(MatrixVT, matrixCopy.ColumnCount, k, m - 1, cs, sn);
+                                Drot(VT, matrixCopy.ColumnCount, k, m - 1, cs, sn);
                             }
                         }
 
@@ -445,14 +445,14 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                         e[l - 1] = 0.0;
                         for (k = l; k < m; k++)
                         {
-                            t1 = VectorS[k];
+                            t1 = S[k];
                             Drotg(ref t1, ref f, out cs, out sn);
-                            VectorS[k] = t1;
+                            S[k] = t1;
                             f = -sn * e[k];
                             e[k] = cs * e[k];
                             if (ComputeVectors)
                             {
-                                Drot(MatrixU, matrixCopy.RowCount, k, l - 1, cs, sn);
+                                Drot(U, matrixCopy.RowCount, k, l - 1, cs, sn);
                             }
                         }
 
@@ -462,15 +462,15 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                     case 3:
                         // Calculate the shift.
                         var scale = 0.0;
-                        scale = Math.Max(scale, Math.Abs(VectorS[m - 1]));
-                        scale = Math.Max(scale, Math.Abs(VectorS[m - 2]));
+                        scale = Math.Max(scale, Math.Abs(S[m - 1]));
+                        scale = Math.Max(scale, Math.Abs(S[m - 2]));
                         scale = Math.Max(scale, Math.Abs(e[m - 2]));
-                        scale = Math.Max(scale, Math.Abs(VectorS[l]));
+                        scale = Math.Max(scale, Math.Abs(S[l]));
                         scale = Math.Max(scale, Math.Abs(e[l]));
-                        var sm = VectorS[m - 1] / scale;
-                        var smm1 = VectorS[m - 2] / scale;
+                        var sm = S[m - 1] / scale;
+                        var smm1 = S[m - 2] / scale;
                         var emm1 = e[m - 2] / scale;
-                        var sl = VectorS[l] / scale;
+                        var sl = S[l] / scale;
                         var el = e[l] / scale;
                         var b = (((smm1 + sm) * (smm1 - sm)) + (emm1 * emm1)) / 2.0;
                         var c = (sm * emm1) * (sm * emm1);
@@ -498,24 +498,24 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                                 e[k - 1] = f;
                             }
 
-                            f = (cs * VectorS[k]) + (sn * e[k]);
-                            e[k] = (cs * e[k]) - (sn * VectorS[k]);
-                            g = sn * VectorS[k + 1];
-                            VectorS[k + 1] = cs * VectorS[k + 1];
+                            f = (cs * S[k]) + (sn * e[k]);
+                            e[k] = (cs * e[k]) - (sn * S[k]);
+                            g = sn * S[k + 1];
+                            S[k + 1] = cs * S[k + 1];
                             if (ComputeVectors)
                             {
-                                Drot(MatrixVT, matrixCopy.ColumnCount, k, k + 1, cs, sn);
+                                Drot(VT, matrixCopy.ColumnCount, k, k + 1, cs, sn);
                             }
 
                             Drotg(ref f, ref g, out cs, out sn);
-                            VectorS[k] = f;
-                            f = (cs * e[k]) + (sn * VectorS[k + 1]);
-                            VectorS[k + 1] = (-sn * e[k]) + (cs * VectorS[k + 1]);
+                            S[k] = f;
+                            f = (cs * e[k]) + (sn * S[k + 1]);
+                            S[k + 1] = (-sn * e[k]) + (cs * S[k + 1]);
                             g = sn * e[k + 1];
                             e[k + 1] = cs * e[k + 1];
                             if (ComputeVectors && k < matrixCopy.RowCount)
                             {
-                                Drot(MatrixU, matrixCopy.RowCount, k, k + 1, cs, sn);
+                                Drot(U, matrixCopy.RowCount, k, k + 1, cs, sn);
                             }
                         }
 
@@ -526,34 +526,34 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                     // Convergence.
                     case 4:
                         // Make the singular value  positive
-                        if (VectorS[l] < 0.0)
+                        if (S[l] < 0.0)
                         {
-                            VectorS[l] = -VectorS[l];
+                            S[l] = -S[l];
                             if (ComputeVectors)
                             {
-                                DscalColumn(MatrixVT, matrixCopy.ColumnCount, l, 0, -1.0);
+                                DscalColumn(VT, matrixCopy.ColumnCount, l, 0, -1.0);
                             }
                         }
 
                         // Order the singular value.
                         while (l != mn - 1)
                         {
-                            if (VectorS[l] >= VectorS[l + 1])
+                            if (S[l] >= S[l + 1])
                             {
                                 break;
                             }
 
-                            t = VectorS[l];
-                            VectorS[l] = VectorS[l + 1];
-                            VectorS[l + 1] = t;
+                            t = S[l];
+                            S[l] = S[l + 1];
+                            S[l + 1] = t;
                             if (ComputeVectors && l < matrixCopy.ColumnCount)
                             {
-                                Dswap(MatrixVT, matrixCopy.ColumnCount, l, l + 1);
+                                Dswap(VT, matrixCopy.ColumnCount, l, l + 1);
                             }
 
                             if (ComputeVectors && l < matrixCopy.RowCount)
                             {
-                                Dswap(MatrixU, matrixCopy.RowCount, l, l + 1);
+                                Dswap(U, matrixCopy.RowCount, l, l + 1);
                             }
 
                             l = l + 1;
@@ -567,7 +567,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
 
             if (ComputeVectors)
             {
-                MatrixVT = MatrixVT.Transpose();
+                VT = VT.Transpose();
             }
 
             // Adjust the size of s if rows < columns. We are using ported copy of linpack's svd code and it uses
@@ -579,10 +579,10 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
                 var tmp = matrixCopy.CreateVector(nm);
                 for (i = 0; i < nm; i++)
                 {
-                    tmp[i] = VectorS[i];
+                    tmp[i] = S[i];
                 }
 
-                VectorS = tmp;
+                S = tmp;
             }
         }
 
@@ -808,46 +808,46 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixU.RowCount != input.RowCount)
+            if (U.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (MatrixVT.ColumnCount != result.RowCount)
+            if (VT.ColumnCount != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
-            var mn = Math.Min(MatrixU.RowCount, MatrixVT.ColumnCount);
+            var mn = Math.Min(U.RowCount, VT.ColumnCount);
             var bn = input.ColumnCount;
 
-            var tmp = new double[MatrixVT.ColumnCount];
+            var tmp = new double[VT.ColumnCount];
 
             for (var k = 0; k < bn; k++)
             {
-                for (var j = 0; j < MatrixVT.ColumnCount; j++)
+                for (var j = 0; j < VT.ColumnCount; j++)
                 {
                     double value = 0;
                     if (j < mn)
                     {
-                        for (var i = 0; i < MatrixU.RowCount; i++)
+                        for (var i = 0; i < U.RowCount; i++)
                         {
-                            value += MatrixU.At(i, j) * input.At(i, k);
+                            value += U.At(i, j) * input.At(i, k);
                         }
 
-                        value /= VectorS[j];
+                        value /= S[j];
                     }
 
                     tmp[j] = value;
                 }
 
-                for (var j = 0; j < MatrixVT.ColumnCount; j++)
+                for (var j = 0; j < VT.ColumnCount; j++)
                 {
                     double value = 0;
-                    for (var i = 0; i < MatrixVT.ColumnCount; i++)
+                    for (var i = 0; i < VT.ColumnCount; i++)
                     {
-                        value += MatrixVT.At(i, j) * tmp[i];
+                        value += VT.At(i, j) * tmp[i];
                     }
 
                     result.At(j, k, value);
@@ -879,42 +879,42 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixU.RowCount != input.Count)
+            if (U.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (MatrixVT.ColumnCount != result.Count)
+            if (VT.ColumnCount != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(MatrixVT, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(VT, result);
             }
 
-            var mn = Math.Min(MatrixU.RowCount, MatrixVT.ColumnCount);
-            var tmp = new double[MatrixVT.ColumnCount];
+            var mn = Math.Min(U.RowCount, VT.ColumnCount);
+            var tmp = new double[VT.ColumnCount];
             double value;
-            for (var j = 0; j < MatrixVT.ColumnCount; j++)
+            for (var j = 0; j < VT.ColumnCount; j++)
             {
                 value = 0;
                 if (j < mn)
                 {
-                    for (var i = 0; i < MatrixU.RowCount; i++)
+                    for (var i = 0; i < U.RowCount; i++)
                     {
-                        value += MatrixU.At(i, j) * input[i];
+                        value += U.At(i, j) * input[i];
                     }
 
-                    value /= VectorS[j];
+                    value /= S[j];
                 }
 
                 tmp[j] = value;
             }
 
-            for (var j = 0; j < MatrixVT.ColumnCount; j++)
+            for (var j = 0; j < VT.ColumnCount; j++)
             {
                 value = 0;
-                for (int i = 0; i < MatrixVT.ColumnCount; i++)
+                for (int i = 0; i < VT.ColumnCount; i++)
                 {
-                    value += MatrixVT.At(i, j) * tmp[i];
+                    value += VT.At(i, j) * tmp[i];
                 }
 
                 result[j] = value;

src/Numerics/LinearAlgebra/Factorization/Cholesky.cs

@@ -45,21 +45,10 @@ namespace MathNet.Numerics.LinearAlgebra.Factorization
     public abstract class Cholesky<T> : ISolver<T>
     where T : struct, IEquatable<T>, IFormattable
     {
-        /// <summary>
-        /// Gets or sets the lower triangular form of the Cholesky matrix
-        /// </summary>
-        protected Matrix<T> CholeskyFactor { get; set; }
-
         /// <summary>
         /// Gets the lower triangular form of the Cholesky matrix.
         /// </summary>
-        public virtual Matrix<T> Factor
-        {
-            get
-            {
-                return CholeskyFactor.Clone();
-            }
-        }
+        public Matrix<T> Factor { get; protected set; }
 
         /// <summary>
         /// Gets the determinant of the matrix for which the Cholesky matrix was computed.

src/Numerics/LinearAlgebra/Factorization/Evd.cs

@@ -82,38 +82,17 @@ namespace MathNet.Numerics.LinearAlgebra.Factorization
         /// <summary>
         /// Gets or sets the eigen values (λ) of matrix in ascending value.
         /// </summary>
-        protected Vector<Complex> VectorEv { get; set; }
+        public Vector<Complex> EigenValues { get; protected set; }
         
         /// <summary>
         /// Gets or sets eigenvectors.
         /// </summary>
-        protected Matrix<T> MatrixEv { get; set; }
+        public Matrix<T> EigenVectors { get; protected set; }
 
         /// <summary>
         /// Gets or sets the block diagonal eigenvalue matrix.
         /// </summary>
-        protected Matrix<T> MatrixD { get; set; }
-
-        /// <summary>Returns the eigen values as a <see cref="Vector{T}"/>.</summary>
-        /// <returns>The eigen values.</returns>
-        public Vector<Complex> EigenValues()
-        {
-            return VectorEv.Clone();
-        }
-
-        /// <summary>Returns the right eigen vectors as a <see cref="Matrix{T}"/>.</summary>
-        /// <returns>The eigen vectors. </returns>
-        public Matrix<T> EigenVectors()
-        {
-            return MatrixEv.Clone();
-        }
-
-        /// <summary>Returns the block diagonal eigenvalue matrix <see cref="Matrix{T}"/>.</summary>
-        /// <returns>The block diagonal eigenvalue matrix <see cref="Matrix{T}"/>.</returns>        
-        public Matrix<T> D()
-        {
-            return MatrixD.Clone();
-        }
+        public Matrix<T> D { get; protected set; }
 
         /// <summary>
         /// Solves a system of linear equations, <b>AX = B</b>, with A SVD factorized.
@@ -128,7 +107,7 @@ namespace MathNet.Numerics.LinearAlgebra.Factorization
                 throw new ArgumentNullException("input");
             }
 
-            var result = MatrixEv.CreateMatrix(MatrixEv.ColumnCount, input.ColumnCount);
+            var result = EigenVectors.CreateMatrix(EigenVectors.ColumnCount, input.ColumnCount);
             Solve(input, result);
             return result;
         }
@@ -153,7 +132,7 @@ namespace MathNet.Numerics.LinearAlgebra.Factorization
                 throw new ArgumentNullException("input");
             }
 
-            var x = MatrixEv.CreateVector(MatrixEv.ColumnCount);
+            var x = EigenVectors.CreateVector(EigenVectors.ColumnCount);
             Solve(input, x);
             return x;
         }

src/Numerics/LinearAlgebra/Factorization/QR.cs

@@ -63,7 +63,7 @@ namespace MathNet.Numerics.LinearAlgebra.Factorization
         /// <summary>
         /// Gets or sets orthogonal Q matrix
         /// </summary>
-        protected Matrix<T> MatrixQ { get; set; }
+        public Matrix<T> Q { get; protected set; }
 
         /// <summary>
         /// Gets or sets upper triangular factor R
@@ -75,26 +75,12 @@ namespace MathNet.Numerics.LinearAlgebra.Factorization
         /// </summary>
         protected QRMethod QrMethod { get; set; }
 
-        /// <summary>
-        /// Gets orthogonal Q matrix
-        /// </summary>
-        public virtual Matrix<T> Q 
-        {
-            get
-            {
-                return MatrixQ.Clone();
-            }
-        }
-
         /// <summary>
         /// Gets the upper triangular factor R.
         /// </summary>
-        public virtual Matrix<T> R
+        public Matrix<T> R
         {
-            get
-            {
-                return MatrixR.UpperTriangle();
-            }
+            get { return MatrixR.UpperTriangle(); }
         }
 
         /// <summary>

src/Numerics/LinearAlgebra/Factorization/Svd.cs

@@ -59,17 +59,17 @@ namespace MathNet.Numerics.LinearAlgebra.Factorization
         /// <summary>
         /// Gets or sets the singular values (Σ) of matrix in ascending value.
         /// </summary>
-        protected Vector<T> VectorS { get; set; }
+        public Vector<T> S { get; protected set; }
 
         /// <summary>
         /// Gets or sets left singular vectors (U - m-by-m unitary matrix)
         /// </summary>
-        protected Matrix<T> MatrixU { get; set; }
+        public Matrix<T> U { get; protected set; }
 
         /// <summary>
         /// Gets or sets transpose right singular vectors (transpose of V, an n-by-n unitary matrix
         /// </summary>
-        protected Matrix<T> MatrixVT { get; set; }
+        public Matrix<T> VT { get; protected set; }
 
         /// <summary>
         /// Gets the effective numerical matrix rank.
@@ -94,35 +94,20 @@ namespace MathNet.Numerics.LinearAlgebra.Factorization
         /// </summary>
         public abstract T Determinant { get; }
 
-        /// <summary>Returns the left singular vectors as a <see cref="Matrix{T}"/>.</summary>
-        /// <returns>The left singular vectors. The matrix will be <c>null</c>, if <b>computeVectors</b> in the constructor is set to <c>false</c>.</returns>
-        public Matrix<T> U()
-        {
-            return ComputeVectors ? MatrixU.Clone() : null;
-        }
-
-        /// <summary>Returns the right singular vectors as a <see cref="Matrix{T}"/>.</summary>
-        /// <returns>The right singular vectors. The matrix will be <c>null</c>, if <b>computeVectors</b> in the constructor is set to <c>false</c>.</returns>
-        /// <remarks>This is the transpose of the V matrix.</remarks>
-        public Matrix<T> VT()
-        {
-            return ComputeVectors ? MatrixVT.Clone() : null;
-        }
-
         /// <summary>Returns the singular values as a diagonal <see cref="Matrix{T}"/>.</summary>
         /// <returns>The singular values as a diagonal <see cref="Matrix{T}"/>.</returns>        
         public Matrix<T> W()
         {
-            var rows = MatrixU.RowCount;
-            var columns = MatrixVT.ColumnCount;
-            var result = MatrixU.CreateMatrix(rows, columns);
+            var rows = U.RowCount;
+            var columns = VT.ColumnCount;
+            var result = U.CreateMatrix(rows, columns);
             for (var i = 0; i < rows; i++)
             {
                 for (var j = 0; j < columns; j++)
                 {
                     if (i == j)
                     {
-                        result.At(i, i, VectorS[i]);
+                        result.At(i, i, S[i]);
                     }
                 }
             }
@@ -130,13 +115,6 @@ namespace MathNet.Numerics.LinearAlgebra.Factorization
             return result;
         }
 
-        /// <summary>Returns the singular values as a <see cref="Vector{T}"/>.</summary>
-        /// <returns>the singular values as a <see cref="Vector{T}"/>.</returns>
-        public Vector<T> S()
-        {
-            return VectorS.Clone();
-        }
-
         /// <summary>
         /// Solves a system of linear equations, <b>AX = B</b>, with A SVD factorized.
         /// </summary>
@@ -155,7 +133,7 @@ namespace MathNet.Numerics.LinearAlgebra.Factorization
                 throw new InvalidOperationException(Resources.SingularVectorsNotComputed);
             }
 
-            var result = MatrixU.CreateMatrix(MatrixVT.ColumnCount, input.ColumnCount);
+            var result = U.CreateMatrix(VT.ColumnCount, input.ColumnCount);
             Solve(input, result);
             return result;
         }
@@ -185,7 +163,7 @@ namespace MathNet.Numerics.LinearAlgebra.Factorization
                 throw new InvalidOperationException(Resources.SingularVectorsNotComputed);
             }
 
-            var x = MatrixU.CreateVector(MatrixVT.ColumnCount);
+            var x = U.CreateVector(VT.ColumnCount);
             Solve(input, x);
             return x;
         }

src/Numerics/LinearAlgebra/Matrix.Arithmetic.cs

@@ -29,7 +29,6 @@
 // </copyright>
 
 using System;
-using MathNet.Numerics.LinearAlgebra.Factorization;
 using MathNet.Numerics.Properties;
 
 namespace MathNet.Numerics.LinearAlgebra

src/Numerics/LinearAlgebra/Matrix.cs

@@ -28,7 +28,6 @@
 // OTHER DEALINGS IN THE SOFTWARE.
 // </copyright>
 
-using MathNet.Numerics.LinearAlgebra.Factorization;
 using MathNet.Numerics.LinearAlgebra.Storage;
 using MathNet.Numerics.Properties;
 using System;

src/Numerics/LinearAlgebra/Single/Factorization/Cholesky.cs

@@ -53,9 +53,9 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             get
             {
                 var det = 1.0f;
-                for (var j = 0; j < CholeskyFactor.RowCount; j++)
+                for (var j = 0; j < Factor.RowCount; j++)
                 {
-                    var d = CholeskyFactor.At(j, j);
+                    var d = Factor.At(j, j);
                     det *= d * d;
                 }
 
@@ -71,9 +71,9 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             get
             {
                 var det = 0.0f;
-                for (var j = 0; j < CholeskyFactor.RowCount; j++)
+                for (var j = 0; j < Factor.RowCount; j++)
                 {
-                    det += 2.0f * Convert.ToSingle(Math.Log(CholeskyFactor.At(j, j)));
+                    det += 2.0f * Convert.ToSingle(Math.Log(Factor.At(j, j)));
                 }
 
                 return det;

src/Numerics/LinearAlgebra/Single/Factorization/DenseCholesky.cs

@@ -67,7 +67,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             // Create a new matrix for the Cholesky factor, then perform factorization (while overwriting).
             var factor = (DenseMatrix)matrix.Clone();
             Control.LinearAlgebraProvider.CholeskyFactor(factor.Values, factor.RowCount);
-            CholeskyFactor = factor;
+            Factor = factor;
         }
 
         /// <summary>
@@ -99,9 +99,9 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
-            if (input.RowCount != CholeskyFactor.RowCount)
+            if (input.RowCount != Factor.RowCount)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(input, CholeskyFactor);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(input, Factor);
             }
 
             var dinput = input as DenseMatrix;
@@ -120,7 +120,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             Buffer.BlockCopy(dinput.Values, 0, dresult.Values, 0, dinput.Values.Length * Constants.SizeOfFloat);
 
             // Cholesky solve by overwriting result.
-            var dfactor = (DenseMatrix)CholeskyFactor;
+            var dfactor = (DenseMatrix)Factor;
             Control.LinearAlgebraProvider.CholeskySolveFactored(dfactor.Values, dfactor.RowCount, dresult.Values, dresult.ColumnCount);
         }
 
@@ -148,9 +148,9 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
-            if (input.Count != CholeskyFactor.RowCount)
+            if (input.Count != Factor.RowCount)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(input, CholeskyFactor);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(input, Factor);
             }
 
             var dinput = input as DenseVector;
@@ -169,7 +169,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             Buffer.BlockCopy(dinput.Values, 0, dresult.Values, 0, dinput.Values.Length * Constants.SizeOfFloat);
 
             // Cholesky solve by overwriting result.
-            var dfactor = (DenseMatrix)CholeskyFactor;
+            var dfactor = (DenseMatrix)Factor;
             Control.LinearAlgebraProvider.CholeskySolveFactored(dfactor.Values, dfactor.RowCount, dresult.Values, 1);
         }
     }

src/Numerics/LinearAlgebra/Single/Factorization/DenseEvd.cs

@@ -79,9 +79,9 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             var order = matrix.RowCount;
 
             // Initialize matrices for eigenvalues and eigenvectors
-            MatrixEv = matrix.CreateMatrix(order, order);
-            MatrixD = matrix.CreateMatrix(order, order);
-            VectorEv = new LinearAlgebra.Complex.DenseVector(order);
+            EigenVectors = matrix.CreateMatrix(order, order);
+            D = matrix.CreateMatrix(order, order);
+            EigenValues = new LinearAlgebra.Complex.DenseVector(order);
 
             IsSymmetric = true;
 
@@ -93,8 +93,8 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 }
             }
 
-            Control.LinearAlgebraProvider.EigenDecomp(IsSymmetric, order, matrix.Values, ((DenseMatrix) MatrixEv).Values,
-                ((LinearAlgebra.Complex.DenseVector) VectorEv).Values, ((DenseMatrix) MatrixD).Values);
+            Control.LinearAlgebraProvider.EigenDecomp(IsSymmetric, order, matrix.Values, ((DenseMatrix) EigenVectors).Values,
+                ((LinearAlgebra.Complex.DenseVector) EigenValues).Values, ((DenseMatrix) D).Values);
         }
 
         /// <summary>
@@ -1132,20 +1132,20 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (VectorEv.Count != input.RowCount)
+            if (EigenValues.Count != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (VectorEv.Count != result.RowCount)
+            if (EigenValues.Count != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
             if (IsSymmetric)
             {
-                var order = VectorEv.Count;
+                var order = EigenValues.Count;
                 var tmp = new float[order];
 
                 for (var k = 0; k < order; k++)
@@ -1157,10 +1157,10 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                         {
                             for (var i = 0; i < order; i++)
                             {
-                                value += ((DenseMatrix) MatrixEv).Values[(j*order) + i]*input.At(i, k);
+                                value += ((DenseMatrix) EigenVectors).Values[(j*order) + i]*input.At(i, k);
                             }
 
-                            value /= (float) VectorEv[j].Real;
+                            value /= (float) EigenValues[j].Real;
                         }
 
                         tmp[j] = value;
@@ -1171,7 +1171,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                         float value = 0;
                         for (var i = 0; i < order; i++)
                         {
-                            value += ((DenseMatrix) MatrixEv).Values[(i*order) + j]*tmp[i];
+                            value += ((DenseMatrix) EigenVectors).Values[(i*order) + j]*tmp[i];
                         }
 
                         result.At(j, k, value);
@@ -1203,13 +1203,13 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
 
             // Ax=b where A is an m x m matrix
             // Check that b is a column vector with m entries
-            if (VectorEv.Count != input.Count)
+            if (EigenValues.Count != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (VectorEv.Count != result.Count)
+            if (EigenValues.Count != result.Count)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixDimensions);
             }
@@ -1217,7 +1217,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             if (IsSymmetric)
             {
                 // Symmetric case -> x = V * inv(λ) * VT * b;
-                var order = VectorEv.Count;
+                var order = EigenValues.Count;
                 var tmp = new float[order];
                 float value;
 
@@ -1228,10 +1228,10 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                     {
                         for (var i = 0; i < order; i++)
                         {
-                            value += ((DenseMatrix) MatrixEv).Values[(j*order) + i]*input[i];
+                            value += ((DenseMatrix) EigenVectors).Values[(j*order) + i]*input[i];
                         }
 
-                        value /= (float) VectorEv[j].Real;
+                        value /= (float) EigenValues[j].Real;
                     }
 
                     tmp[j] = value;
@@ -1242,7 +1242,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                     value = 0;
                     for (var i = 0; i < order; i++)
                     {
-                        value += ((DenseMatrix) MatrixEv).Values[(i*order) + j]*tmp[i];
+                        value += ((DenseMatrix) EigenVectors).Values[(i*order) + j]*tmp[i];
                     }
 
                     result[j] = value;

src/Numerics/LinearAlgebra/Single/Factorization/DenseGramSchmidt.cs

@@ -69,9 +69,9 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 throw Matrix.DimensionsDontMatch<ArgumentException>(matrix);
             }
 
-            MatrixQ = matrix.Clone();
+            Q = matrix.Clone();
             MatrixR = matrix.CreateMatrix(matrix.ColumnCount, matrix.ColumnCount);
-            Factorize(((DenseMatrix)MatrixQ).Values, MatrixQ.RowCount, MatrixQ.ColumnCount, ((DenseMatrix)MatrixR).Values);
+            Factorize(((DenseMatrix)Q).Values, Q.RowCount, Q.ColumnCount, ((DenseMatrix)MatrixR).Values);
         }
 
         /// <summary>
@@ -149,13 +149,13 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixQ.RowCount != input.RowCount)
+            if (Q.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (MatrixQ.ColumnCount != result.RowCount)
+            if (Q.ColumnCount != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
@@ -172,7 +172,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 throw new NotSupportedException("Can only do GramSchmidt factorization for dense matrices at the moment.");
             }
 
-            _provider.QRSolveFactored(((DenseMatrix)MatrixQ).Values, ((DenseMatrix)MatrixR).Values, MatrixQ.RowCount, MatrixR.ColumnCount, null, dinput.Values, input.ColumnCount, dresult.Values, QRMethod.Thin);
+            _provider.QRSolveFactored(((DenseMatrix)Q).Values, ((DenseMatrix)MatrixR).Values, Q.RowCount, MatrixR.ColumnCount, null, dinput.Values, input.ColumnCount, dresult.Values, QRMethod.Thin);
         }
 
         /// <summary>
@@ -194,15 +194,15 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixQ.RowCount != input.Count)
+            if (Q.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (MatrixQ.ColumnCount != result.Count)
+            if (Q.ColumnCount != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(MatrixQ, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(Q, result);
             }
 
             var dinput = input as DenseVector;
@@ -217,7 +217,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 throw new NotSupportedException("Can only do GramSchmidt factorization for dense vectors at the moment.");
             }
 
-            _provider.QRSolveFactored(((DenseMatrix)MatrixQ).Values, ((DenseMatrix)MatrixR).Values, MatrixQ.RowCount, MatrixR.ColumnCount, null, dinput.Values, 1, dresult.Values, QRMethod.Thin);
+            _provider.QRSolveFactored(((DenseMatrix)Q).Values, ((DenseMatrix)MatrixR).Values, Q.RowCount, MatrixR.ColumnCount, null, dinput.Values, 1, dresult.Values, QRMethod.Thin);
         }
     }
 }

src/Numerics/LinearAlgebra/Single/Factorization/DenseQR.cs

@@ -80,15 +80,15 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             if (method == QRMethod.Full)
             {
                 MatrixR = matrix.Clone();
-                MatrixQ = new DenseMatrix(matrix.RowCount);
+                Q = new DenseMatrix(matrix.RowCount);
                 Control.LinearAlgebraProvider.QRFactor(((DenseMatrix)MatrixR).Values, matrix.RowCount, matrix.ColumnCount,
-                                                       ((DenseMatrix)MatrixQ).Values, Tau);
+                                                       ((DenseMatrix)Q).Values, Tau);
             }
             else
             {
-                MatrixQ = matrix.Clone();
+                Q = matrix.Clone();
                 MatrixR = new DenseMatrix(matrix.ColumnCount);
-                Control.LinearAlgebraProvider.ThinQRFactor(((DenseMatrix)MatrixQ).Values, matrix.RowCount, matrix.ColumnCount,
+                Control.LinearAlgebraProvider.ThinQRFactor(((DenseMatrix)Q).Values, matrix.RowCount, matrix.ColumnCount,
                                                        ((DenseMatrix)MatrixR).Values, Tau);
             }
         }
@@ -118,7 +118,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixQ.RowCount != input.RowCount)
+            if (Q.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
@@ -141,7 +141,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 throw new NotSupportedException("Can only do QR factorization for dense matrices at the moment.");
             }
 
-            Control.LinearAlgebraProvider.QRSolveFactored(((DenseMatrix)MatrixQ).Values, ((DenseMatrix)MatrixR).Values, MatrixQ.RowCount, MatrixR.ColumnCount, Tau, dinput.Values, input.ColumnCount, dresult.Values, QrMethod);
+            Control.LinearAlgebraProvider.QRSolveFactored(((DenseMatrix)Q).Values, ((DenseMatrix)MatrixR).Values, Q.RowCount, MatrixR.ColumnCount, Tau, dinput.Values, input.ColumnCount, dresult.Values, QrMethod);
         }
 
         /// <summary>
@@ -163,7 +163,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixQ.RowCount != input.Count)
+            if (Q.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
@@ -186,7 +186,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 throw new NotSupportedException("Can only do QR factorization for dense vectors at the moment.");
             }
 
-            Control.LinearAlgebraProvider.QRSolveFactored(((DenseMatrix)MatrixQ).Values, ((DenseMatrix)MatrixR).Values, MatrixQ.RowCount, MatrixR.ColumnCount, Tau, dinput.Values, 1, dresult.Values, QrMethod);
+            Control.LinearAlgebraProvider.QRSolveFactored(((DenseMatrix)Q).Values, ((DenseMatrix)MatrixR).Values, Q.RowCount, MatrixR.ColumnCount, Tau, dinput.Values, 1, dresult.Values, QrMethod);
         }
     }
 }

src/Numerics/LinearAlgebra/Single/Factorization/DenseSvd.cs

@@ -66,10 +66,10 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
 
             ComputeVectors = computeVectors;
             var nm = Math.Min(matrix.RowCount, matrix.ColumnCount);
-            VectorS = new DenseVector(nm);
-            MatrixU = new DenseMatrix(matrix.RowCount);
-            MatrixVT = new DenseMatrix(matrix.ColumnCount);
-            Control.LinearAlgebraProvider.SingularValueDecomposition(computeVectors, ((DenseMatrix)matrix.Clone()).Values, matrix.RowCount, matrix.ColumnCount, ((DenseVector)VectorS).Values, ((DenseMatrix)MatrixU).Values, ((DenseMatrix)MatrixVT).Values);
+            S = new DenseVector(nm);
+            U = new DenseMatrix(matrix.RowCount);
+            VT = new DenseMatrix(matrix.ColumnCount);
+            Control.LinearAlgebraProvider.SingularValueDecomposition(computeVectors, ((DenseMatrix)matrix.Clone()).Values, matrix.RowCount, matrix.ColumnCount, ((DenseVector)S).Values, ((DenseMatrix)U).Values, ((DenseMatrix)VT).Values);
         }
 
         /// <summary>
@@ -102,13 +102,13 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixU.RowCount != input.RowCount)
+            if (U.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (MatrixVT.ColumnCount != result.RowCount)
+            if (VT.ColumnCount != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
@@ -125,7 +125,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 throw new NotSupportedException("Can only do SVD factorization for dense matrices at the moment.");
             }
 
-            Control.LinearAlgebraProvider.SvdSolveFactored(MatrixU.RowCount, MatrixVT.ColumnCount, ((DenseVector)VectorS).Values, ((DenseMatrix)MatrixU).Values, ((DenseMatrix)MatrixVT).Values, dinput.Values, input.ColumnCount, dresult.Values);
+            Control.LinearAlgebraProvider.SvdSolveFactored(U.RowCount, VT.ColumnCount, ((DenseVector)S).Values, ((DenseMatrix)U).Values, ((DenseMatrix)VT).Values, dinput.Values, input.ColumnCount, dresult.Values);
         }
 
         /// <summary>
@@ -152,15 +152,15 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixU.RowCount != input.Count)
+            if (U.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (MatrixVT.ColumnCount != result.Count)
+            if (VT.ColumnCount != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(MatrixVT, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(VT, result);
             }
 
             var dinput = input as DenseVector;
@@ -175,7 +175,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 throw new NotSupportedException("Can only do SVD factorization for dense vectors at the moment.");
             }
 
-            Control.LinearAlgebraProvider.SvdSolveFactored(MatrixU.RowCount, MatrixVT.ColumnCount, ((DenseVector)VectorS).Values, ((DenseMatrix)MatrixU).Values, ((DenseMatrix)MatrixVT).Values, dinput.Values, 1, dresult.Values);
+            Control.LinearAlgebraProvider.SvdSolveFactored(U.RowCount, VT.ColumnCount, ((DenseVector)S).Values, ((DenseMatrix)U).Values, ((DenseMatrix)VT).Values, dinput.Values, 1, dresult.Values);
         }
     }
 }

src/Numerics/LinearAlgebra/Single/Factorization/Evd.cs

@@ -60,11 +60,11 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             get
             {
                 var det = Complex.One;
-                for (var i = 0; i < VectorEv.Count; i++)
+                for (var i = 0; i < EigenValues.Count; i++)
                 {
-                    det *= VectorEv[i];
+                    det *= EigenValues[i];
 
-                    if (((Numerics.Complex32)VectorEv[i]).AlmostEqual(Numerics.Complex32.Zero))
+                    if (((Numerics.Complex32)EigenValues[i]).AlmostEqual(Numerics.Complex32.Zero))
                     {
                         return 0;
                     }
@@ -83,9 +83,9 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             get
             {
                 var rank = 0;
-                for (var i = 0; i < VectorEv.Count; i++)
+                for (var i = 0; i < EigenValues.Count; i++)
                 {
-                    if (((Numerics.Complex32)VectorEv[i]).AlmostEqual(Numerics.Complex32.Zero))
+                    if (((Numerics.Complex32)EigenValues[i]).AlmostEqual(Numerics.Complex32.Zero))
                     {
                         continue;
                     }
@@ -105,9 +105,9 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
         {
             get
             {
-                for (var i = 0; i < VectorEv.Count; i++)
+                for (var i = 0; i < EigenValues.Count; i++)
                 {
-                    if (VectorEv[i].AlmostEqual(Complex.Zero))
+                    if (EigenValues[i].AlmostEqual(Complex.Zero))
                     {
                         return false;
                     }

src/Numerics/LinearAlgebra/Single/Factorization/Svd.cs

@@ -59,7 +59,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
         {
             get
             {
-                return VectorS.Count(t => !Math.Abs(t).AlmostEqual(0.0f));
+                return S.Count(t => !Math.Abs(t).AlmostEqual(0.0f));
             }
         }
 
@@ -71,7 +71,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
         {
             get
             {
-                return Math.Abs(VectorS[0]);
+                return Math.Abs(S[0]);
             }
         }
 
@@ -83,8 +83,8 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
         {
             get
             {
-                var tmp = Math.Min(MatrixU.RowCount, MatrixVT.ColumnCount) - 1;
-                return Math.Abs(VectorS[0]) / Math.Abs(VectorS[tmp]);
+                var tmp = Math.Min(U.RowCount, VT.ColumnCount) - 1;
+                return Math.Abs(S[0]) / Math.Abs(S[tmp]);
             }
         }
 
@@ -95,13 +95,13 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
         {
             get
             {
-                if (MatrixU.RowCount != MatrixVT.ColumnCount)
+                if (U.RowCount != VT.ColumnCount)
                 {
                     throw new ArgumentException(Resources.ArgumentMatrixSquare);
                 }
 
                 var det = 1.0;
-                foreach (var value in VectorS)
+                foreach (var value in S)
                 {
                     det *= value;
                     if (Math.Abs(value).AlmostEqual(0.0f))

src/Numerics/LinearAlgebra/Single/Factorization/UserCholesky.cs

@@ -66,40 +66,40 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             }
 
             // Create a new matrix for the Cholesky factor, then perform factorization (while overwriting).
-            CholeskyFactor = matrix.Clone();
-            var tmpColumn = new float[CholeskyFactor.RowCount];
+            Factor = matrix.Clone();
+            var tmpColumn = new float[Factor.RowCount];
 
             // Main loop - along the diagonal
-            for (var ij = 0; ij < CholeskyFactor.RowCount; ij++)
+            for (var ij = 0; ij < Factor.RowCount; ij++)
             {
                 // "Pivot" element
-                var tmpVal = CholeskyFactor.At(ij, ij);
+                var tmpVal = Factor.At(ij, ij);
 
                 if (tmpVal > 0.0)
                 {
                     tmpVal = (float)Math.Sqrt(tmpVal);
-                    CholeskyFactor.At(ij, ij, tmpVal);
+                    Factor.At(ij, ij, tmpVal);
                     tmpColumn[ij] = tmpVal;
 
                     // Calculate multipliers and copy to local column
                     // Current column, below the diagonal
-                    for (var i = ij + 1; i < CholeskyFactor.RowCount; i++)
+                    for (var i = ij + 1; i < Factor.RowCount; i++)
                     {
-                        CholeskyFactor.At(i, ij, CholeskyFactor.At(i, ij) / tmpVal);
-                        tmpColumn[i] = CholeskyFactor.At(i, ij);
+                        Factor.At(i, ij, Factor.At(i, ij) / tmpVal);
+                        tmpColumn[i] = Factor.At(i, ij);
                     }
 
                     // Remaining columns, below the diagonal
-                    DoCholeskyStep(CholeskyFactor, CholeskyFactor.RowCount, ij + 1, CholeskyFactor.RowCount, tmpColumn, Control.NumberOfParallelWorkerThreads);
+                    DoCholeskyStep(Factor, Factor.RowCount, ij + 1, Factor.RowCount, tmpColumn, Control.NumberOfParallelWorkerThreads);
                 }
                 else
                 {
                     throw new ArgumentException(Resources.ArgumentMatrixPositiveDefinite);
                 }
 
-                for (var i = ij + 1; i < CholeskyFactor.RowCount; i++)
+                for (var i = ij + 1; i < Factor.RowCount; i++)
                 {
-                    CholeskyFactor.At(ij, i, 0.0f);
+                    Factor.At(ij, i, 0.0f);
                 }
             }
         }
@@ -167,13 +167,13 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
-            if (input.RowCount != CholeskyFactor.RowCount)
+            if (input.RowCount != Factor.RowCount)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(input, CholeskyFactor);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(input, Factor);
             }
 
             input.CopyTo(result);
-            var order = CholeskyFactor.RowCount;
+            var order = Factor.RowCount;
 
             for (var c = 0; c < result.ColumnCount; c++)
             {
@@ -184,10 +184,10 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                     sum = result.At(i, c);
                     for (var k = i - 1; k >= 0; k--)
                     {
-                        sum -= CholeskyFactor.At(i, k) * result.At(k, c);
+                        sum -= Factor.At(i, k) * result.At(k, c);
                     }
 
-                    result.At(i, c, sum / CholeskyFactor.At(i, i));
+                    result.At(i, c, sum / Factor.At(i, i));
                 }
 
                 // Solve L'*X = Y;
@@ -196,10 +196,10 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                     sum = result.At(i, c);
                     for (var k = i + 1; k < order; k++)
                     {
-                        sum -= CholeskyFactor.At(k, i) * result.At(k, c);
+                        sum -= Factor.At(k, i) * result.At(k, c);
                     }
 
-                    result.At(i, c, sum / CholeskyFactor.At(i, i));
+                    result.At(i, c, sum / Factor.At(i, i));
                 }
             }
         }
@@ -228,13 +228,13 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
-            if (input.Count != CholeskyFactor.RowCount)
+            if (input.Count != Factor.RowCount)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(input, CholeskyFactor);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(input, Factor);
             }
 
             input.CopyTo(result);
-            var order = CholeskyFactor.RowCount;
+            var order = Factor.RowCount;
 
             // Solve L*Y = B;
             float sum;
@@ -243,10 +243,10 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 sum = result[i];
                 for (var k = i - 1; k >= 0; k--)
                 {
-                    sum -= CholeskyFactor.At(i, k) * result[k];
+                    sum -= Factor.At(i, k) * result[k];
                 }
 
-                result[i] = sum / CholeskyFactor.At(i, i);
+                result[i] = sum / Factor.At(i, i);
             }
 
             // Solve L'*X = Y;
@@ -255,10 +255,10 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 sum = result[i];
                 for (var k = i + 1; k < order; k++)
                 {
-                    sum -= CholeskyFactor.At(k, i) * result[k];
+                    sum -= Factor.At(k, i) * result[k];
                 }
 
-                result[i] = sum / CholeskyFactor.At(i, i);
+                result[i] = sum / Factor.At(i, i);
             }
         }
     }

src/Numerics/LinearAlgebra/Single/Factorization/UserEvd.cs

@@ -78,9 +78,9 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             var order = matrix.RowCount;
 
             // Initialize matricies for eigenvalues and eigenvectors
-            MatrixEv = matrix.CreateMatrix(order, order);
-            MatrixD = matrix.CreateMatrix(order, order);
-            VectorEv = new LinearAlgebra.Complex.DenseVector(order);
+            EigenVectors = matrix.CreateMatrix(order, order);
+            D = matrix.CreateMatrix(order, order);
+            EigenValues = new LinearAlgebra.Complex.DenseVector(order);
            
             IsSymmetric = true;
 
@@ -97,8 +97,8 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
 
             if (IsSymmetric)
             {
-                matrix.CopyTo(MatrixEv);
-                d = MatrixEv.Row(order - 1).ToArray();
+                matrix.CopyTo(EigenVectors);
+                d = EigenVectors.Row(order - 1).ToArray();
 
                 SymmetricTridiagonalize(d, e, order);
                 SymmetricDiagonalize(d, e, order);
@@ -113,21 +113,21 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
 
             for (var i = 0; i < order; i++)
             {
-                MatrixD.At(i, i, d[i]);
+                D.At(i, i, d[i]);
 
                 if (e[i] > 0)
                 {
-                    MatrixD.At(i, i + 1, e[i]);
+                    D.At(i, i + 1, e[i]);
                 }
                 else if (e[i] < 0)
                 {
-                    MatrixD.At(i, i - 1, e[i]);
+                    D.At(i, i - 1, e[i]);
                 }
             }
 
             for (var i = 0; i < order; i++)
             {
-                VectorEv[i] = new Complex(d[i], e[i]);
+                EigenValues[i] = new Complex(d[i], e[i]);
             }
         }
 
@@ -160,9 +160,9 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                     e[i] = d[i - 1];
                     for (var j = 0; j < i; j++)
                     {
-                        d[j] = MatrixEv.At(i - 1, j);
-                        MatrixEv.At(i, j, 0.0f);
-                        MatrixEv.At(j, i, 0.0f);
+                        d[j] = EigenVectors.At(i - 1, j);
+                        EigenVectors.At(i, j, 0.0f);
+                        EigenVectors.At(j, i, 0.0f);
                     }
                 }
                 else
@@ -194,13 +194,13 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                     for (var j = 0; j < i; j++)
                     {
                         f = d[j];
-                        MatrixEv.At(j, i, f);
-                        g = e[j] + (MatrixEv.At(j, j) * f);
+                        EigenVectors.At(j, i, f);
+                        g = e[j] + (EigenVectors.At(j, j) * f);
 
                         for (var k = j + 1; k <= i - 1; k++)
                         {
-                            g += MatrixEv.At(k, j) * d[k];
-                            e[k] += MatrixEv.At(k, j) * f;
+                            g += EigenVectors.At(k, j) * d[k];
+                            e[k] += EigenVectors.At(k, j) * f;
                         }
 
                         e[j] = g;
@@ -228,11 +228,11 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
 
                         for (var k = j; k <= i - 1; k++)
                         {
-                            MatrixEv.At(k, j, MatrixEv.At(k, j) - (f * e[k]) - (g * d[k]));
+                            EigenVectors.At(k, j, EigenVectors.At(k, j) - (f * e[k]) - (g * d[k]));
                         }
 
-                        d[j] = MatrixEv.At(i - 1, j);
-                        MatrixEv.At(i, j, 0.0f);
+                        d[j] = EigenVectors.At(i - 1, j);
+                        EigenVectors.At(i, j, 0.0f);
                     }
                 }
 
@@ -242,14 +242,14 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             // Accumulate transformations.
             for (var i = 0; i < order - 1; i++)
             {
-                MatrixEv.At(order - 1, i, MatrixEv.At(i, i));
-                MatrixEv.At(i, i, 1.0f);
+                EigenVectors.At(order - 1, i, EigenVectors.At(i, i));
+                EigenVectors.At(i, i, 1.0f);
                 var h = d[i + 1];
                 if (h != 0.0f)
                 {
                     for (var k = 0; k <= i; k++)
                     {
-                        d[k] = MatrixEv.At(k, i + 1) / h;
+                        d[k] = EigenVectors.At(k, i + 1) / h;
                     }
 
                     for (var j = 0; j <= i; j++)
@@ -257,29 +257,29 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                         var g = 0.0f;
                         for (var k = 0; k <= i; k++)
                         {
-                            g += MatrixEv.At(k, i + 1) * MatrixEv.At(k, j);
+                            g += EigenVectors.At(k, i + 1) * EigenVectors.At(k, j);
                         }
 
                         for (var k = 0; k <= i; k++)
                         {
-                            MatrixEv.At(k, j, MatrixEv.At(k, j) - g * d[k]);
+                            EigenVectors.At(k, j, EigenVectors.At(k, j) - g * d[k]);
                         }
                     }
                 }
 
                 for (var k = 0; k <= i; k++)
                 {
-                    MatrixEv.At(k, i + 1, 0.0f);
+                    EigenVectors.At(k, i + 1, 0.0f);
                 }
             }
 
             for (var j = 0; j < order; j++)
             {
-                d[j] = MatrixEv.At(order - 1, j);
-                MatrixEv.At(order - 1, j, 0.0f);
+                d[j] = EigenVectors.At(order - 1, j);
+                EigenVectors.At(order - 1, j, 0.0f);
             }
 
-            MatrixEv.At(order - 1, order - 1, 1.0f);
+            EigenVectors.At(order - 1, order - 1, 1.0f);
             e[0] = 0.0f;
         }
 
@@ -378,9 +378,9 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                             // Accumulate transformation.
                             for (var k = 0; k < order; k++)
                             {
-                                h = MatrixEv.At(k, i + 1);
-                                MatrixEv.At(k, i + 1, (s * MatrixEv.At(k, i)) + (c * h));
-                                MatrixEv.At(k, i, (c * MatrixEv.At(k, i)) - (s * h));
+                                h = EigenVectors.At(k, i + 1);
+                                EigenVectors.At(k, i + 1, (s * EigenVectors.At(k, i)) + (c * h));
+                                EigenVectors.At(k, i, (c * EigenVectors.At(k, i)) - (s * h));
                             }
                         }
 
@@ -422,9 +422,9 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                     d[i] = p;
                     for (var j = 0; j < order; j++)
                     {
-                        p = MatrixEv.At(j, i);
-                        MatrixEv.At(j, i, MatrixEv.At(j, k));
-                        MatrixEv.At(j, k, p);
+                        p = EigenVectors.At(j, i);
+                        EigenVectors.At(j, i, EigenVectors.At(j, k));
+                        EigenVectors.At(j, k, p);
                     }
                 }
             }
@@ -513,7 +513,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             {
                 for (var j = 0; j < order; j++)
                 {
-                    MatrixEv.At(i, j, i == j ? 1.0f : 0.0f);
+                    EigenVectors.At(i, j, i == j ? 1.0f : 0.0f);
                 }
             }
 
@@ -531,14 +531,14 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                         var g = 0.0f;
                         for (var i = m; i < order; i++)
                         {
-                            g += ort[i] * MatrixEv.At(i, j);
+                            g += ort[i] * EigenVectors.At(i, j);
                         }
 
                         // Double division avoids possible underflow
                         g = (g / ort[m]) / matrixH[m, m - 1];
                         for (var i = m; i < order; i++)
                         {
-                            MatrixEv.At(i, j, MatrixEv.At(i, j) + g * ort[i]);
+                            EigenVectors.At(i, j, EigenVectors.At(i, j) + g * ort[i]);
                         }
                     }
                 }
@@ -668,9 +668,9 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                         // Accumulate transformations
                         for (var i = 0; i < order; i++)
                         {
-                            z = MatrixEv.At(i, n - 1);
-                            MatrixEv.At(i, n - 1, (q * z) + (p * MatrixEv.At(i, n)));
-                            MatrixEv.At(i, n, (q * MatrixEv.At(i, n)) - (p * z));
+                            z = EigenVectors.At(i, n - 1);
+                            EigenVectors.At(i, n - 1, (q * z) + (p * EigenVectors.At(i, n)));
+                            EigenVectors.At(i, n, (q * EigenVectors.At(i, n)) - (p * z));
                         }
 
                         // Complex pair
@@ -858,16 +858,16 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                             // Accumulate transformations
                             for (var i = 0; i < order; i++)
                             {
-                                p = (x * MatrixEv.At(i, k)) + (y * MatrixEv.At(i, k + 1));
+                                p = (x * EigenVectors.At(i, k)) + (y * EigenVectors.At(i, k + 1));
 
                                 if (notlast)
                                 {
-                                    p = p + (z * MatrixEv.At(i, k + 2));
-                                    MatrixEv.At(i, k + 2, MatrixEv.At(i, k + 2) - (p * r));
+                                    p = p + (z * EigenVectors.At(i, k + 2));
+                                    EigenVectors.At(i, k + 2, EigenVectors.At(i, k + 2) - (p * r));
                                 }
 
-                                MatrixEv.At(i, k, MatrixEv.At(i, k) - p);
-                                MatrixEv.At(i, k + 1, MatrixEv.At(i, k + 1) - (p * q));
+                                EigenVectors.At(i, k, EigenVectors.At(i, k) - p);
+                                EigenVectors.At(i, k + 1, EigenVectors.At(i, k + 1) - (p * q));
                             }
                         } // (s != 0)
                     } // k loop
@@ -1051,10 +1051,10 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                     z = 0.0f;
                     for (var k = 0; k <= j; k++)
                     {
-                        z = z + (MatrixEv.At(i, k) * matrixH[k, j]);
+                        z = z + (EigenVectors.At(i, k) * matrixH[k, j]);
                     }
 
-                    MatrixEv.At(i, j, z);
+                    EigenVectors.At(i, j, z);
                 }
             }
         }
@@ -1102,20 +1102,20 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (VectorEv.Count != input.RowCount)
+            if (EigenValues.Count != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (VectorEv.Count != result.RowCount)
+            if (EigenValues.Count != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
             if (IsSymmetric)
             {
-                var order = VectorEv.Count;
+                var order = EigenValues.Count;
                 var tmp = new float[order];
 
                 for (var k = 0; k < order; k++)
@@ -1127,10 +1127,10 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                         {
                             for (var i = 0; i < order; i++)
                             {
-                                value += MatrixEv.At(i, j) * input.At(i, k);
+                                value += EigenVectors.At(i, j) * input.At(i, k);
                             }
 
-                            value /= (float)VectorEv[j].Real;
+                            value /= (float)EigenValues[j].Real;
                         }
 
                         tmp[j] = value;
@@ -1141,7 +1141,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                         float value = 0;
                         for (var i = 0; i < order; i++)
                         {
-                            value += MatrixEv.At(j, i) * tmp[i];
+                            value += EigenVectors.At(j, i) * tmp[i];
                         }
 
                         result.At(j, k, value);
@@ -1173,13 +1173,13 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
 
             // Ax=b where A is an m x m matrix
             // Check that b is a column vector with m entries
-            if (VectorEv.Count != input.Count)
+            if (EigenValues.Count != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (VectorEv.Count != result.Count)
+            if (EigenValues.Count != result.Count)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixDimensions);
             }
@@ -1187,7 +1187,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             if (IsSymmetric)
             {
                 // Symmetric case -> x = V * inv(λ) * VT * b;
-                var order = VectorEv.Count;
+                var order = EigenValues.Count;
                 var tmp = new float[order];
                 float value;
 
@@ -1198,10 +1198,10 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                     {
                         for (var i = 0; i < order; i++)
                         {
-                            value += MatrixEv.At(i, j) * input[i];
+                            value += EigenVectors.At(i, j) * input[i];
                         }
 
-                        value /= (float)VectorEv[j].Real;
+                        value /= (float)EigenValues[j].Real;
                     }
 
                     tmp[j] = value;
@@ -1212,7 +1212,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                     value = 0;
                     for (int i = 0; i < order; i++)
                     {
-                        value += MatrixEv.At(j, i) * tmp[i];
+                        value += EigenVectors.At(j, i) * tmp[i];
                     }
 
                     result[j] = value;

src/Numerics/LinearAlgebra/Single/Factorization/UserGramSchmidt.cs

@@ -62,31 +62,31 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 throw Matrix.DimensionsDontMatch<ArgumentException>(matrix);
             }
 
-            MatrixQ = matrix.Clone();
+            Q = matrix.Clone();
             MatrixR = matrix.CreateMatrix(matrix.ColumnCount, matrix.ColumnCount);
 
-            for (var k = 0; k < MatrixQ.ColumnCount; k++)
+            for (var k = 0; k < Q.ColumnCount; k++)
             {
-                var norm = MatrixQ.Column(k).L2Norm();
+                var norm = Q.Column(k).L2Norm();
                 if (norm == 0.0)
                 {
                     throw new ArgumentException(Resources.ArgumentMatrixNotRankDeficient);
                 }
 
                 MatrixR.At(k, k, norm);
-                for (var i = 0; i < MatrixQ.RowCount; i++)
+                for (var i = 0; i < Q.RowCount; i++)
                 {
-                    MatrixQ.At(i, k, MatrixQ.At(i, k) / norm);
+                    Q.At(i, k, Q.At(i, k) / norm);
                 }
 
-                for (var j = k + 1; j < MatrixQ.ColumnCount; j++)
+                for (var j = k + 1; j < Q.ColumnCount; j++)
                 {
-                    var dot = MatrixQ.Column(k).DotProduct(MatrixQ.Column(j));
+                    var dot = Q.Column(k).DotProduct(Q.Column(j));
                     MatrixR.At(k, j, dot);
-                    for (var i = 0; i < MatrixQ.RowCount; i++)
+                    for (var i = 0; i < Q.RowCount; i++)
                     {
-                        var value = MatrixQ.At(i, j) - (MatrixQ.At(i, k) * dot);
-                        MatrixQ.At(i, j, value);
+                        var value = Q.At(i, j) - (Q.At(i, k) * dot);
+                        Q.At(i, j, value);
                     }
                 }
             }
@@ -117,13 +117,13 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixQ.RowCount != input.RowCount)
+            if (Q.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (MatrixQ.ColumnCount != result.RowCount)
+            if (Q.ColumnCount != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
@@ -131,20 +131,20 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             var inputCopy = input.Clone();
             
             // Compute Y = transpose(Q)*B
-            var column = new float[MatrixQ.RowCount];
+            var column = new float[Q.RowCount];
             for (var j = 0; j < input.ColumnCount; j++)
             {
-                for (var k = 0; k < MatrixQ.RowCount; k++)
+                for (var k = 0; k < Q.RowCount; k++)
                 {
                     column[k] = inputCopy.At(k, j);
                 }
 
-                for (var i = 0; i < MatrixQ.ColumnCount; i++)
+                for (var i = 0; i < Q.ColumnCount; i++)
                 {
                     float s = 0;
-                    for (var k = 0; k < MatrixQ.RowCount; k++)
+                    for (var k = 0; k < Q.RowCount; k++)
                     {
-                        s += MatrixQ.At(k, i) * column[k];
+                        s += Q.At(k, i) * column[k];
                     }
 
                     inputCopy.At(i, j, s);
@@ -152,7 +152,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             }
 
             // Solve R*X = Y;
-            for (var k = MatrixQ.ColumnCount - 1; k >= 0; k--)
+            for (var k = Q.ColumnCount - 1; k >= 0; k--)
             {
                 for (var j = 0; j < input.ColumnCount; j++)
                 {
@@ -196,39 +196,39 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixQ.RowCount != input.Count)
+            if (Q.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (MatrixQ.ColumnCount != result.Count)
+            if (Q.ColumnCount != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(MatrixQ, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(Q, result);
             }
 
             var inputCopy = input.Clone();
 
             // Compute Y = transpose(Q)*B
-            var column = new float[MatrixQ.RowCount];
-            for (var k = 0; k < MatrixQ.RowCount; k++)
+            var column = new float[Q.RowCount];
+            for (var k = 0; k < Q.RowCount; k++)
             {
                 column[k] = inputCopy[k];
             }
 
-            for (var i = 0; i < MatrixQ.ColumnCount; i++)
+            for (var i = 0; i < Q.ColumnCount; i++)
             {
                 float s = 0;
-                for (var k = 0; k < MatrixQ.RowCount; k++)
+                for (var k = 0; k < Q.RowCount; k++)
                 {
-                    s += MatrixQ.At(k, i) * column[k];
+                    s += Q.At(k, i) * column[k];
                 }
 
                 inputCopy[i] = s;
             }
 
             // Solve R*X = Y;
-            for (var k = MatrixQ.ColumnCount - 1; k >= 0; k--)
+            for (var k = Q.ColumnCount - 1; k >= 0; k--)
             {
                 inputCopy[k] /= MatrixR.At(k, k);
                 for (var i = 0; i < k; i++)

src/Numerics/LinearAlgebra/Single/Factorization/UserQR.cs

@@ -73,11 +73,11 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             if (method == QRMethod.Full)
             {
                 MatrixR = matrix.Clone();
-                MatrixQ = matrix.CreateMatrix(matrix.RowCount, matrix.RowCount);
+                Q = matrix.CreateMatrix(matrix.RowCount, matrix.RowCount);
 
                 for (var i = 0; i < matrix.RowCount; i++)
                 {
-                    MatrixQ.At(i, i, 1.0f);
+                    Q.At(i, i, 1.0f);
                 }
 
                 for (var i = 0; i < minmn; i++)
@@ -89,33 +89,33 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
 
                 for (var i = minmn - 1; i >= 0; i--)
                 {
-                    ComputeQR(u[i], MatrixQ, i, matrix.RowCount, i, matrix.RowCount,
+                    ComputeQR(u[i], Q, i, matrix.RowCount, i, matrix.RowCount,
                               Control.NumberOfParallelWorkerThreads);
                 }
             }
             else
             {
                 MatrixR = matrix.CreateMatrix(matrix.ColumnCount, matrix.ColumnCount);
-                MatrixQ = matrix.Clone();
+                Q = matrix.Clone();
 
                 for (var i = 0; i < minmn; i++)
                 {
-                    u[i] = GenerateColumn(MatrixQ, i, i);
-                    ComputeQR(u[i], MatrixQ, i, matrix.RowCount, i + 1, matrix.ColumnCount,
+                    u[i] = GenerateColumn(Q, i, i);
+                    ComputeQR(u[i], Q, i, matrix.RowCount, i + 1, matrix.ColumnCount,
                               Control.NumberOfParallelWorkerThreads);
                 }
 
-                MatrixR = MatrixQ.SubMatrix(0, matrix.ColumnCount, 0, matrix.ColumnCount);
-                MatrixQ.Clear();
+                MatrixR = Q.SubMatrix(0, matrix.ColumnCount, 0, matrix.ColumnCount);
+                Q.Clear();
 
                 for (var i = 0; i < matrix.ColumnCount; i++)
                 {
-                    MatrixQ.At(i, i, 1.0f);
+                    Q.At(i, i, 1.0f);
                 }
 
                 for (var i = minmn - 1; i >= 0; i--)
                 {
-                    ComputeQR(u[i], MatrixQ, i, matrix.RowCount, i, matrix.ColumnCount,
+                    ComputeQR(u[i], Q, i, matrix.RowCount, i, matrix.ColumnCount,
                               Control.NumberOfParallelWorkerThreads);
                 }
             }
@@ -271,7 +271,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                     float s = 0;
                     for (var k = 0; k < MatrixR.RowCount; k++)
                     {
-                        s += MatrixQ.At(k, i) * column[k];
+                        s += Q.At(k, i) * column[k];
                     }
 
                     inputCopy.At(i, j, s);
@@ -348,7 +348,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 float s = 0;
                 for (var k = 0; k < MatrixR.RowCount; k++)
                 {
-                    s += MatrixQ.At(k, i) * column[k];
+                    s += Q.At(k, i) * column[k];
                 }
 
                 inputCopy[i] = s;

src/Numerics/LinearAlgebra/Single/Factorization/UserSvd.cs

@@ -68,9 +68,9 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             var nm = Math.Min(matrix.RowCount + 1, matrix.ColumnCount);
             var matrixCopy = matrix.Clone();
 
-            VectorS = matrixCopy.CreateVector(nm);
-            MatrixU = matrixCopy.CreateMatrix(matrixCopy.RowCount, matrixCopy.RowCount);
-            MatrixVT = matrixCopy.CreateMatrix(matrixCopy.ColumnCount, matrixCopy.ColumnCount);
+            S = matrixCopy.CreateVector(nm);
+            U = matrixCopy.CreateMatrix(matrixCopy.RowCount, matrixCopy.RowCount);
+            VT = matrixCopy.CreateMatrix(matrixCopy.ColumnCount, matrixCopy.ColumnCount);
 
             const int maxiter = 1000;
             var e = new float[matrixCopy.ColumnCount];
@@ -94,26 +94,26 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 {
                     // Compute the transformation for the l-th column and place the l-th diagonal in VectorS[l].
                     var xnorm = Dnrm2Column(matrixCopy, matrixCopy.RowCount, l, l);
-                    VectorS[l] = xnorm;
-                    if (VectorS[l] != 0.0)
+                    S[l] = xnorm;
+                    if (S[l] != 0.0)
                     {
                         if (matrixCopy.At(l, l) != 0.0)
                         {
-                            VectorS[l] = Dsign(VectorS[l], matrixCopy.At(l, l));
+                            S[l] = Dsign(S[l], matrixCopy.At(l, l));
                         }
 
-                        DscalColumn(matrixCopy, matrixCopy.RowCount, l, l, 1.0f / VectorS[l]);
+                        DscalColumn(matrixCopy, matrixCopy.RowCount, l, l, 1.0f / S[l]);
                         matrixCopy.At(l, l, (1.0f + matrixCopy.At(l, l)));
                     }
 
-                    VectorS[l] = -VectorS[l];
+                    S[l] = -S[l];
                 }
 
                 for (j = lp1; j < matrixCopy.ColumnCount; j++)
                 {
                     if (l < nct)
                     {
-                        if (VectorS[l] != 0.0)
+                        if (S[l] != 0.0)
                         {
                             // Apply the transformation.
                             t = -Ddot(matrixCopy, matrixCopy.RowCount, l, j, l) / matrixCopy.At(l, l);
@@ -134,7 +134,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                     // Place the transformation in u for subsequent back multiplication.
                     for (i = l; i < matrixCopy.RowCount; i++)
                     {
-                        MatrixU.At(i, l, matrixCopy.At(i, l));
+                        U.At(i, l, matrixCopy.At(i, l));
                     }
                 }
 
@@ -189,7 +189,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                     // Place the transformation in v for subsequent back multiplication.
                     for (i = lp1; i < matrixCopy.ColumnCount; i++)
                     {
-                        MatrixVT.At(i, l, e[i]);
+                        VT.At(i, l, e[i]);
                     }
                 }
             }
@@ -200,12 +200,12 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             var nrtp1 = nrt + 1;
             if (nct < matrixCopy.ColumnCount)
             {
-                VectorS[nctp1 - 1] = matrixCopy.At((nctp1 - 1), (nctp1 - 1));
+                S[nctp1 - 1] = matrixCopy.At((nctp1 - 1), (nctp1 - 1));
             }
 
             if (matrixCopy.RowCount < m)
             {
-                VectorS[m - 1] = 0.0f;
+                S[m - 1] = 0.0f;
             }
 
             if (nrtp1 < m)
@@ -222,40 +222,40 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 {
                     for (i = 0; i < matrixCopy.RowCount; i++)
                     {
-                        MatrixU.At(i, j, 0.0f);
+                        U.At(i, j, 0.0f);
                     }
 
-                    MatrixU.At(j, j, 1.0f);
+                    U.At(j, j, 1.0f);
                 }
 
                 for (l = nct - 1; l >= 0; l--)
                 {
-                    if (VectorS[l] != 0.0)
+                    if (S[l] != 0.0)
                     {
                         for (j = l + 1; j < ncu; j++)
                         {
-                            t = -Ddot(MatrixU, matrixCopy.RowCount, l, j, l) / MatrixU.At(l, l);
+                            t = -Ddot(U, matrixCopy.RowCount, l, j, l) / U.At(l, l);
                             for (var ii = l; ii < matrixCopy.RowCount; ii++)
                             {
-                                MatrixU.At(ii, j, MatrixU.At(ii, j) + (t * MatrixU.At(ii, l)));
+                                U.At(ii, j, U.At(ii, j) + (t * U.At(ii, l)));
                             }
                         }
 
-                        DscalColumn(MatrixU, matrixCopy.RowCount, l, l, -1.0f);
-                        MatrixU.At(l, l, 1.0f + MatrixU.At(l, l));
+                        DscalColumn(U, matrixCopy.RowCount, l, l, -1.0f);
+                        U.At(l, l, 1.0f + U.At(l, l));
                         for (i = 0; i < l; i++)
                         {
-                            MatrixU.At(i, l, 0.0f);
+                            U.At(i, l, 0.0f);
                         }
                     }
                     else
                     {
                         for (i = 0; i < matrixCopy.RowCount; i++)
                         {
-                            MatrixU.At(i, l, 0.0f);
+                            U.At(i, l, 0.0f);
                         }
 
-                        MatrixU.At(l, l, 1.0f);
+                        U.At(l, l, 1.0f);
                     }
                 }
             }
@@ -272,10 +272,10 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                         {
                             for (j = lp1; j < matrixCopy.ColumnCount; j++)
                             {
-                                t = -Ddot(MatrixVT, matrixCopy.ColumnCount, l, j, lp1) / MatrixVT.At(lp1, l);
+                                t = -Ddot(VT, matrixCopy.ColumnCount, l, j, lp1) / VT.At(lp1, l);
                                 for (var ii = l; ii < matrixCopy.ColumnCount; ii++)
                                 {
-                                    MatrixVT.At(ii, j, MatrixVT.At(ii, j) + (t * MatrixVT.At(ii, l)));
+                                    VT.At(ii, j, VT.At(ii, j) + (t * VT.At(ii, l)));
                                 }
                             }
                         }
@@ -283,10 +283,10 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
 
                     for (i = 0; i < matrixCopy.ColumnCount; i++)
                     {
-                        MatrixVT.At(i, l, 0.0f);
+                        VT.At(i, l, 0.0f);
                     }
 
-                    MatrixVT.At(l, l, 1.0f);
+                    VT.At(l, l, 1.0f);
                 }
             }
 
@@ -294,11 +294,11 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             for (i = 0; i < m; i++)
             {
                 float r;
-                if (VectorS[i] != 0.0)
+                if (S[i] != 0.0)
                 {
-                    t = VectorS[i];
-                    r = VectorS[i] / t;
-                    VectorS[i] = t;
+                    t = S[i];
+                    r = S[i] / t;
+                    S[i] = t;
                     if (i < m - 1)
                     {
                         e[i] = e[i] / r;
@@ -306,7 +306,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
 
                     if (ComputeVectors)
                     {
-                        DscalColumn(MatrixU, matrixCopy.RowCount, i, 0, r);
+                        DscalColumn(U, matrixCopy.RowCount, i, 0, r);
                     }
                 }
 
@@ -321,10 +321,10 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                     t = e[i];
                     r = t / e[i];
                     e[i] = t;
-                    VectorS[i + 1] = VectorS[i + 1] * r;
+                    S[i + 1] = S[i + 1] * r;
                     if (ComputeVectors)
                     {
-                        DscalColumn(MatrixVT, matrixCopy.ColumnCount, i + 1, 0, r);
+                        DscalColumn(VT, matrixCopy.ColumnCount, i + 1, 0, r);
                     }
                 }
             }
@@ -352,7 +352,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 float test;
                 for (l = m - 2; l >= 0; l--)
                 {
-                    test = Math.Abs(VectorS[l]) + Math.Abs(VectorS[l + 1]);
+                    test = Math.Abs(S[l]) + Math.Abs(S[l + 1]);
                     ztest = test + Math.Abs(e[l]);
                     if (ztest.AlmostEqualInDecimalPlaces(test, 7))
                     {
@@ -382,10 +382,10 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                             test = test + Math.Abs(e[ls - 1]);
                         }
 
-                        ztest = test + Math.Abs(VectorS[ls]);
+                        ztest = test + Math.Abs(S[ls]);
                         if (ztest.AlmostEqualInDecimalPlaces(test, 7))
                         {
-                            VectorS[ls] = 0.0f;
+                            S[ls] = 0.0f;
                             break;
                         }
                     }
@@ -422,9 +422,9 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                         for (var kk = l; kk < m - 1; kk++)
                         {
                             k = m - 2 - kk + l;
-                            t1 = VectorS[k];
+                            t1 = S[k];
                             Drotg(ref t1, ref f, out cs, out sn);
-                            VectorS[k] = t1;
+                            S[k] = t1;
                             if (k != l)
                             {
                                 f = -sn * e[k - 1];
@@ -433,7 +433,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
 
                             if (ComputeVectors)
                             {
-                                Drot(MatrixVT, matrixCopy.ColumnCount, k, m - 1, cs, sn);
+                                Drot(VT, matrixCopy.ColumnCount, k, m - 1, cs, sn);
                             }
                         }
 
@@ -445,14 +445,14 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                         e[l - 1] = 0.0f;
                         for (k = l; k < m; k++)
                         {
-                            t1 = VectorS[k];
+                            t1 = S[k];
                             Drotg(ref t1, ref f, out cs, out sn);
-                            VectorS[k] = t1;
+                            S[k] = t1;
                             f = -sn * e[k];
                             e[k] = cs * e[k];
                             if (ComputeVectors)
                             {
-                                Drot(MatrixU, matrixCopy.RowCount, k, l - 1, cs, sn);
+                                Drot(U, matrixCopy.RowCount, k, l - 1, cs, sn);
                             }
                         }
 
@@ -462,15 +462,15 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                     case 3:
                         // Calculate the shift.
                         var scale = 0.0f;
-                        scale = Math.Max(scale, Math.Abs(VectorS[m - 1]));
-                        scale = Math.Max(scale, Math.Abs(VectorS[m - 2]));
+                        scale = Math.Max(scale, Math.Abs(S[m - 1]));
+                        scale = Math.Max(scale, Math.Abs(S[m - 2]));
                         scale = Math.Max(scale, Math.Abs(e[m - 2]));
-                        scale = Math.Max(scale, Math.Abs(VectorS[l]));
+                        scale = Math.Max(scale, Math.Abs(S[l]));
                         scale = Math.Max(scale, Math.Abs(e[l]));
-                        var sm = VectorS[m - 1] / scale;
-                        var smm1 = VectorS[m - 2] / scale;
+                        var sm = S[m - 1] / scale;
+                        var smm1 = S[m - 2] / scale;
                         var emm1 = e[m - 2] / scale;
-                        var sl = VectorS[l] / scale;
+                        var sl = S[l] / scale;
                         var el = e[l] / scale;
                         var b = (((smm1 + sm) * (smm1 - sm)) + (emm1 * emm1)) / 2.0f;
                         var c = (sm * emm1) * (sm * emm1);
@@ -498,24 +498,24 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                                 e[k - 1] = f;
                             }
 
-                            f = (cs * VectorS[k]) + (sn * e[k]);
-                            e[k] = (cs * e[k]) - (sn * VectorS[k]);
-                            g = sn * VectorS[k + 1];
-                            VectorS[k + 1] = cs * VectorS[k + 1];
+                            f = (cs * S[k]) + (sn * e[k]);
+                            e[k] = (cs * e[k]) - (sn * S[k]);
+                            g = sn * S[k + 1];
+                            S[k + 1] = cs * S[k + 1];
                             if (ComputeVectors)
                             {
-                                Drot(MatrixVT, matrixCopy.ColumnCount, k, k + 1, cs, sn);
+                                Drot(VT, matrixCopy.ColumnCount, k, k + 1, cs, sn);
                             }
 
                             Drotg(ref f, ref g, out cs, out sn);
-                            VectorS[k] = f;
-                            f = (cs * e[k]) + (sn * VectorS[k + 1]);
-                            VectorS[k + 1] = (-sn * e[k]) + (cs * VectorS[k + 1]);
+                            S[k] = f;
+                            f = (cs * e[k]) + (sn * S[k + 1]);
+                            S[k + 1] = (-sn * e[k]) + (cs * S[k + 1]);
                             g = sn * e[k + 1];
                             e[k + 1] = cs * e[k + 1];
                             if (ComputeVectors && k < matrixCopy.RowCount)
                             {
-                                Drot(MatrixU, matrixCopy.RowCount, k, k + 1, cs, sn);
+                                Drot(U, matrixCopy.RowCount, k, k + 1, cs, sn);
                             }
                         }
 
@@ -526,34 +526,34 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                     // Convergence.
                     case 4:
                         // Make the singular value  positive
-                        if (VectorS[l] < 0.0)
+                        if (S[l] < 0.0)
                         {
-                            VectorS[l] = -VectorS[l];
+                            S[l] = -S[l];
                             if (ComputeVectors)
                             {
-                                DscalColumn(MatrixVT, matrixCopy.ColumnCount, l, 0, -1.0f);
+                                DscalColumn(VT, matrixCopy.ColumnCount, l, 0, -1.0f);
                             }
                         }
 
                         // Order the singular value.
                         while (l != mn - 1)
                         {
-                            if (VectorS[l] >= VectorS[l + 1])
+                            if (S[l] >= S[l + 1])
                             {
                                 break;
                             }
 
-                            t = VectorS[l];
-                            VectorS[l] = VectorS[l + 1];
-                            VectorS[l + 1] = t;
+                            t = S[l];
+                            S[l] = S[l + 1];
+                            S[l + 1] = t;
                             if (ComputeVectors && l < matrixCopy.ColumnCount)
                             {
-                                Dswap(MatrixVT, matrixCopy.ColumnCount, l, l + 1);
+                                Dswap(VT, matrixCopy.ColumnCount, l, l + 1);
                             }
 
                             if (ComputeVectors && l < matrixCopy.RowCount)
                             {
-                                Dswap(MatrixU, matrixCopy.RowCount, l, l + 1);
+                                Dswap(U, matrixCopy.RowCount, l, l + 1);
                             }
 
                             l = l + 1;
@@ -567,7 +567,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
 
             if (ComputeVectors)
             {
-                MatrixVT = MatrixVT.Transpose();
+                VT = VT.Transpose();
             }
 
             // Adjust the size of s if rows < columns. We are using ported copy of linpack's svd code and it uses
@@ -579,10 +579,10 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
                 var tmp = matrixCopy.CreateVector(nm);
                 for (i = 0; i < nm; i++)
                 {
-                    tmp[i] = VectorS[i];
+                    tmp[i] = S[i];
                 }
 
-                VectorS = tmp;
+                S = tmp;
             }
         }
 
@@ -808,46 +808,46 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
             }
 
             // The dimension compatibility conditions for X = A\B require the two matrices A and B to have the same number of rows
-            if (MatrixU.RowCount != input.RowCount)
+            if (U.RowCount != input.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameRowDimension);
             }
 
             // The solution X row dimension is equal to the column dimension of A
-            if (MatrixVT.ColumnCount != result.RowCount)
+            if (VT.ColumnCount != result.RowCount)
             {
                 throw new ArgumentException(Resources.ArgumentMatrixSameColumnDimension);
             }
 
-            var mn = Math.Min(MatrixU.RowCount, MatrixVT.ColumnCount);
+            var mn = Math.Min(U.RowCount, VT.ColumnCount);
             var bn = input.ColumnCount;
 
-            var tmp = new float[MatrixVT.ColumnCount];
+            var tmp = new float[VT.ColumnCount];
 
             for (var k = 0; k < bn; k++)
             {
-                for (var j = 0; j < MatrixVT.ColumnCount; j++)
+                for (var j = 0; j < VT.ColumnCount; j++)
                 {
                     float value = 0;
                     if (j < mn)
                     {
-                        for (var i = 0; i < MatrixU.RowCount; i++)
+                        for (var i = 0; i < U.RowCount; i++)
                         {
-                            value += MatrixU.At(i, j) * input.At(i, k);
+                            value += U.At(i, j) * input.At(i, k);
                         }
 
-                        value /= VectorS[j];
+                        value /= S[j];
                     }
 
                     tmp[j] = value;
                 }
 
-                for (var j = 0; j < MatrixVT.ColumnCount; j++)
+                for (var j = 0; j < VT.ColumnCount; j++)
                 {
                     float value = 0;
-                    for (var i = 0; i < MatrixVT.ColumnCount; i++)
+                    for (var i = 0; i < VT.ColumnCount; i++)
                     {
-                        value += MatrixVT.At(i, j) * tmp[i];
+                        value += VT.At(i, j) * tmp[i];
                     }
 
                     result.At(j, k, value);
@@ -879,42 +879,42 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Factorization
 
             // Ax=b where A is an m x n matrix
             // Check that b is a column vector with m entries
-            if (MatrixU.RowCount != input.Count)
+            if (U.RowCount != input.Count)
             {
                 throw new ArgumentException(Resources.ArgumentVectorsSameLength);
             }
 
             // Check that x is a column vector with n entries
-            if (MatrixVT.ColumnCount != result.Count)
+            if (VT.ColumnCount != result.Count)
             {
-                throw Matrix.DimensionsDontMatch<ArgumentException>(MatrixVT, result);
+                throw Matrix.DimensionsDontMatch<ArgumentException>(VT, result);
             }
 
-            var mn = Math.Min(MatrixU.RowCount, MatrixVT.ColumnCount);
-            var tmp = new float[MatrixVT.ColumnCount];
+            var mn = Math.Min(U.RowCount, VT.ColumnCount);
+            var tmp = new float[VT.ColumnCount];
             float value;
-            for (var j = 0; j < MatrixVT.ColumnCount; j++)
+            for (var j = 0; j < VT.ColumnCount; j++)
             {
                 value = 0;
                 if (j < mn)
                 {
-                    for (var i = 0; i < MatrixU.RowCount; i++)
+                    for (var i = 0; i < U.RowCount; i++)
                     {
-                        value += MatrixU.At(i, j) * input[i];
+                        value += U.At(i, j) * input[i];
                     }
 
-                    value /= VectorS[j];
+                    value /= S[j];
                 }
 
                 tmp[j] = value;
             }
 
-            for (var j = 0; j < MatrixVT.ColumnCount; j++)
+            for (var j = 0; j < VT.ColumnCount; j++)
             {
                 value = 0;
-                for (int i = 0; i < MatrixVT.ColumnCount; i++)
+                for (int i = 0; i < VT.ColumnCount; i++)
                 {
-                    value += MatrixVT.At(i, j) * tmp[i];
+                    value += VT.At(i, j) * tmp[i];
                 }
 
                 result[j] = value;

src/UnitTests/ArrayHelpers.cs

@@ -27,8 +27,6 @@
 namespace MathNet.Numerics.UnitTests
 {
     using System;
-    using System.Collections.Generic;
-    using System.Linq;
 
     /// <summary>
     /// Array and List helper/extention for Silverlight

src/UnitTests/LinearAlgebraTests/Complex/Factorization/EvdTests.cs

@@ -57,9 +57,9 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.Factorization
         {
             var matrixI = DenseMatrix.Identity(order);
             var factorEvd = matrixI.Evd();
-            var eigenValues = factorEvd.EigenValues();
-            var eigenVectors = factorEvd.EigenVectors();
-            var d = factorEvd.D();
+            var eigenValues = factorEvd.EigenValues;
+            var eigenVectors = factorEvd.EigenVectors;
+            var d = factorEvd.D;
 
             Assert.AreEqual(matrixI.RowCount, eigenVectors.RowCount);
             Assert.AreEqual(matrixI.RowCount, eigenVectors.ColumnCount);
@@ -87,17 +87,17 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.Factorization
         {
             var matrixA = MatrixLoader.GenerateRandomDenseMatrix(order, order);
             var factorEvd = matrixA.Evd();
-            var eigenVectors = factorEvd.EigenVectors();
+            var eigenVectors = factorEvd.EigenVectors;
 
             Assert.AreEqual(order, eigenVectors.RowCount);
             Assert.AreEqual(order, eigenVectors.ColumnCount);
 
-            Assert.AreEqual(order, factorEvd.D().RowCount);
-            Assert.AreEqual(order, factorEvd.D().ColumnCount);
+            Assert.AreEqual(order, factorEvd.D.RowCount);
+            Assert.AreEqual(order, factorEvd.D.ColumnCount);
 
             // Make sure the A*V = λ*V 
             var matrixAv = matrixA * eigenVectors;
-            var matrixLv = eigenVectors * factorEvd.D();
+            var matrixLv = eigenVectors * factorEvd.D;
 
             for (var i = 0; i < matrixAv.RowCount; i++)
             {
@@ -123,8 +123,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.Factorization
             var matrixA = MatrixLoader.GenerateRandomPositiveDefiniteHermitianDenseMatrix(order);
             MatrixHelpers.ForceConjugateSymmetric(matrixA);
             var factorEvd = matrixA.Evd();
-            var eigenVectors = factorEvd.EigenVectors();
-            var d = factorEvd.D();
+            var eigenVectors = factorEvd.EigenVectors;
+            var d = factorEvd.D;
 
             Assert.AreEqual(order, eigenVectors.RowCount);
             Assert.AreEqual(order, eigenVectors.ColumnCount);

src/UnitTests/LinearAlgebraTests/Complex/Factorization/GramSchmidtTests.cs

@@ -1,4 +1,4 @@
-// <copyright file="GramSchmidtTests.cs" company="Math.NET">
+// <copyright file="GramSchmidtTests.cs" company="Math.NET">
 // Math.NET Numerics, part of the Math.NET Project
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics

src/UnitTests/LinearAlgebraTests/Complex/Factorization/SvdTests.cs

@@ -58,8 +58,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.Factorization
         {
             var matrixI = DenseMatrix.Identity(order);
             var factorSvd = matrixI.Svd(true);
-            var u = factorSvd.U();
-            var vt = factorSvd.VT();
+            var u = factorSvd.U;
+            var vt = factorSvd.VT;
             var w = factorSvd.W();
 
             Assert.AreEqual(matrixI.RowCount, u.RowCount);
@@ -95,8 +95,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.Factorization
         {
             var matrixA = MatrixLoader.GenerateRandomDenseMatrix(row, column);
             var factorSvd = matrixA.Svd(true);
-            var u = factorSvd.U();
-            var vt = factorSvd.VT();
+            var u = factorSvd.U;
+            var vt = factorSvd.VT;
             var w = factorSvd.W();
 
             // Make sure the U has the right dimensions.

src/UnitTests/LinearAlgebraTests/Complex/Factorization/UserCholeskyTests.cs

@@ -28,7 +28,6 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.Factorization
 {
     using System;
     using System.Numerics;
-    using LinearAlgebra.Complex;
     using NUnit.Framework;
 
     /// <summary>

src/UnitTests/LinearAlgebraTests/Complex/Factorization/UserEvdTests.cs

@@ -28,7 +28,6 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.Factorization
 {
     using System;
     using System.Numerics;
-    using LinearAlgebra.Complex;
     using LinearAlgebra.Complex.Factorization;
     using NUnit.Framework;
 
@@ -57,9 +56,9 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.Factorization
         {
             var matrixI = UserDefinedMatrix.Identity(order);
             var factorEvd = matrixI.Evd();
-            var eigenValues = factorEvd.EigenValues();
-            var eigenVectors = factorEvd.EigenVectors();
-            var d = factorEvd.D();
+            var eigenValues = factorEvd.EigenValues;
+            var eigenVectors = factorEvd.EigenVectors;
+            var d = factorEvd.D;
 
             Assert.AreEqual(matrixI.RowCount, eigenVectors.RowCount);
             Assert.AreEqual(matrixI.RowCount, eigenVectors.ColumnCount);
@@ -87,8 +86,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.Factorization
         {
             var matrixA = MatrixLoader.GenerateRandomUserDefinedMatrix(order, order);
             var factorEvd = matrixA.Evd();
-            var eigenVectors = factorEvd.EigenVectors();
-            var d = factorEvd.D();
+            var eigenVectors = factorEvd.EigenVectors;
+            var d = factorEvd.D;
 
             Assert.AreEqual(order, eigenVectors.RowCount);
             Assert.AreEqual(order, eigenVectors.ColumnCount);
@@ -123,8 +122,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.Factorization
         {
             var matrixA = MatrixLoader.GenerateRandomPositiveDefiniteHermitianUserDefinedMatrix(order);
             var factorEvd = matrixA.Evd();
-            var eigenVectors = factorEvd.EigenVectors();
-            var d = factorEvd.D();
+            var eigenVectors = factorEvd.EigenVectors;
+            var d = factorEvd.D;
 
             Assert.AreEqual(order, eigenVectors.RowCount);
             Assert.AreEqual(order, eigenVectors.ColumnCount);

src/UnitTests/LinearAlgebraTests/Complex/Factorization/UserGramSchmidtTests.cs

@@ -1,4 +1,4 @@
-// <copyright file="UserGramSchmidtTests.cs" company="Math.NET">
+// <copyright file="UserGramSchmidtTests.cs" company="Math.NET">
 // Math.NET Numerics, part of the Math.NET Project
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
@@ -28,7 +28,6 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.Factorization
 {
     using System;
     using System.Numerics;
-    using LinearAlgebra.Complex;
     using LinearAlgebra.Complex.Factorization;
     using NUnit.Framework;
 

src/UnitTests/LinearAlgebraTests/Complex/Factorization/UserLUTests.cs

@@ -28,7 +28,6 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.Factorization
 {
     using System;
     using System.Numerics;
-    using LinearAlgebra.Complex;
     using NUnit.Framework;
 
     /// <summary>

src/UnitTests/LinearAlgebraTests/Complex/Factorization/UserQRTests.cs

@@ -24,7 +24,6 @@
 // OTHER DEALINGS IN THE SOFTWARE.
 // </copyright>
 
-using MathNet.Numerics.LinearAlgebra.Complex;
 using MathNet.Numerics.LinearAlgebra.Complex.Factorization;
 using MathNet.Numerics.LinearAlgebra.Factorization;
 using NUnit.Framework;

src/UnitTests/LinearAlgebraTests/Complex/Factorization/UserSvdTests.cs

@@ -28,7 +28,6 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.Factorization
 {
     using System;
     using System.Numerics;
-    using LinearAlgebra.Complex;
     using LinearAlgebra.Complex.Factorization;
     using NUnit.Framework;
 
@@ -57,8 +56,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.Factorization
         {
             var matrixI = UserDefinedMatrix.Identity(order);
             var factorSvd = matrixI.Svd(true);
-            var u = factorSvd.U();
-            var vt = factorSvd.VT();
+            var u = factorSvd.U;
+            var vt = factorSvd.VT;
             var w = factorSvd.W();
 
             Assert.AreEqual(matrixI.RowCount, u.RowCount);
@@ -94,8 +93,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.Factorization
         {
             var matrixA = MatrixLoader.GenerateRandomUserDefinedMatrix(row, column);
             var factorSvd = matrixA.Svd(true);
-            var u = factorSvd.U();
-            var vt = factorSvd.VT();
+            var u = factorSvd.U;
+            var vt = factorSvd.VT;
             var w = factorSvd.W();
 
             // Make sure the U has the right dimensions.

src/UnitTests/LinearAlgebraTests/Complex/MatrixTests.cs

@@ -26,7 +26,6 @@
 
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
 {
-    using System.Numerics;
     using NUnit.Framework;
 
     /// <summary>

src/UnitTests/LinearAlgebraTests/Complex/Solvers/Iterative/BiCgStabTest.cs

@@ -30,7 +30,6 @@
 
 using System;
 using MathNet.Numerics.LinearAlgebra.Complex;
-using MathNet.Numerics.LinearAlgebra.Complex.Solvers;
 using MathNet.Numerics.LinearAlgebra.Complex.Solvers.Iterative;
 using MathNet.Numerics.LinearAlgebra.Complex.Solvers.StopCriterium;
 using MathNet.Numerics.LinearAlgebra.Solvers;

src/UnitTests/LinearAlgebraTests/Complex/Solvers/Iterative/GpBiCgTest.cs

@@ -30,7 +30,6 @@
 
 using System;
 using MathNet.Numerics.LinearAlgebra.Complex;
-using MathNet.Numerics.LinearAlgebra.Complex.Solvers;
 using MathNet.Numerics.LinearAlgebra.Complex.Solvers.Iterative;
 using MathNet.Numerics.LinearAlgebra.Complex.Solvers.StopCriterium;
 using MathNet.Numerics.LinearAlgebra.Solvers;

src/UnitTests/LinearAlgebraTests/Complex/Solvers/Iterative/MlkBiCgStabTest.cs

@@ -30,7 +30,6 @@
 
 using System;
 using MathNet.Numerics.LinearAlgebra.Complex;
-using MathNet.Numerics.LinearAlgebra.Complex.Solvers;
 using MathNet.Numerics.LinearAlgebra.Complex.Solvers.Iterative;
 using MathNet.Numerics.LinearAlgebra.Complex.Solvers.StopCriterium;
 using MathNet.Numerics.LinearAlgebra.Solvers;

src/UnitTests/LinearAlgebraTests/Complex/Solvers/Iterative/TFQMRTest.cs

@@ -30,7 +30,6 @@
 
 using System;
 using MathNet.Numerics.LinearAlgebra.Complex;
-using MathNet.Numerics.LinearAlgebra.Complex.Solvers;
 using MathNet.Numerics.LinearAlgebra.Complex.Solvers.Iterative;
 using MathNet.Numerics.LinearAlgebra.Complex.Solvers.StopCriterium;
 using MathNet.Numerics.LinearAlgebra.Solvers;

src/UnitTests/LinearAlgebraTests/Complex/Solvers/IteratorTest.cs

@@ -31,7 +31,6 @@
 using System;
 using System.Collections.Generic;
 using MathNet.Numerics.LinearAlgebra.Complex;
-using MathNet.Numerics.LinearAlgebra.Complex.Solvers;
 using MathNet.Numerics.LinearAlgebra.Complex.Solvers.StopCriterium;
 using MathNet.Numerics.LinearAlgebra.Solvers;
 using MathNet.Numerics.LinearAlgebra.Solvers.Status;

src/UnitTests/LinearAlgebraTests/Complex/UserDefinedMatrix.cs

@@ -24,7 +24,6 @@
 // OTHER DEALINGS IN THE SOFTWARE.
 // </copyright>
 
-using MathNet.Numerics.LinearAlgebra;
 using MathNet.Numerics.LinearAlgebra.Complex;
 using MathNet.Numerics.LinearAlgebra.Storage;
 

src/UnitTests/LinearAlgebraTests/Complex/UserDefinedVector.cs

@@ -24,7 +24,6 @@
 // OTHER DEALINGS IN THE SOFTWARE.
 // </copyright>
 
-using MathNet.Numerics.LinearAlgebra;
 using MathNet.Numerics.LinearAlgebra.Complex;
 using MathNet.Numerics.LinearAlgebra.Storage;
 

src/UnitTests/LinearAlgebraTests/Complex32/Factorization/EvdTests.cs

@@ -58,9 +58,9 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.Factorization
         {
             var matrixI = DenseMatrix.Identity(order);
             var factorEvd = matrixI.Evd();
-            var eigenValues = factorEvd.EigenValues();
-            var eigenVectors = factorEvd.EigenVectors();
-            var d = factorEvd.D();
+            var eigenValues = factorEvd.EigenValues;
+            var eigenVectors = factorEvd.EigenVectors;
+            var d = factorEvd.D;
 
             Assert.AreEqual(matrixI.RowCount, eigenVectors.RowCount);
             Assert.AreEqual(matrixI.RowCount, eigenVectors.ColumnCount);
@@ -68,7 +68,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.Factorization
             Assert.AreEqual(matrixI.ColumnCount, d.RowCount);
             Assert.AreEqual(matrixI.ColumnCount, d.ColumnCount);
 
-            for (var i = 0; i < factorEvd.EigenValues().Count; i++)
+            for (var i = 0; i < factorEvd.EigenValues.Count; i++)
             {
                 Assert.AreEqual(Complex.One, eigenValues[i]);
             }
@@ -88,8 +88,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.Factorization
         {
             var matrixA = MatrixLoader.GenerateRandomDenseMatrix(order, order);
             var factorEvd = matrixA.Evd();
-            var eigenVectors = factorEvd.EigenVectors();
-            var d = factorEvd.D();
+            var eigenVectors = factorEvd.EigenVectors;
+            var d = factorEvd.D;
 
             Assert.AreEqual(order, eigenVectors.RowCount);
             Assert.AreEqual(order, eigenVectors.ColumnCount);
@@ -99,7 +99,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.Factorization
 
             // Make sure the A*V = λ*V 
             var matrixAv = matrixA * eigenVectors;
-            var matrixLv = eigenVectors * factorEvd.D();
+            var matrixLv = eigenVectors * factorEvd.D;
 
             for (var i = 0; i < matrixAv.RowCount; i++)
             {
@@ -120,8 +120,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.Factorization
             var matrixA = MatrixLoader.GenerateRandomPositiveDefiniteHermitianDenseMatrix(order);
             MatrixHelpers.ForceConjugateSymmetric(matrixA);
             var factorEvd = matrixA.Evd();
-            var eigenVectors = factorEvd.EigenVectors();
-            var d = factorEvd.D();
+            var eigenVectors = factorEvd.EigenVectors;
+            var d = factorEvd.D;
 
             Assert.AreEqual(order, eigenVectors.RowCount);
             Assert.AreEqual(order, eigenVectors.ColumnCount);

src/UnitTests/LinearAlgebraTests/Complex32/Factorization/GramSchmidtTests.cs

@@ -1,4 +1,4 @@
-// <copyright file="GramSchmidtTests.cs" company="Math.NET">
+// <copyright file="GramSchmidtTests.cs" company="Math.NET">
 // Math.NET Numerics, part of the Math.NET Project
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics

src/UnitTests/LinearAlgebraTests/Complex32/Factorization/QRTests.cs

@@ -1,4 +1,4 @@
-// <copyright file="QRTests.cs" company="Math.NET">
+// <copyright file="QRTests.cs" company="Math.NET">
 // Math.NET Numerics, part of the Math.NET Project
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics

src/UnitTests/LinearAlgebraTests/Complex32/Factorization/SvdTests.cs

@@ -58,8 +58,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.Factorization
         {
             var matrixI = DenseMatrix.Identity(order);
             var factorSvd = matrixI.Svd(true);
-            var u = factorSvd.U();
-            var vt = factorSvd.VT();
+            var u = factorSvd.U;
+            var vt = factorSvd.VT;
             var w = factorSvd.W();
 
             Assert.AreEqual(matrixI.RowCount, u.RowCount);
@@ -95,8 +95,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.Factorization
         {
             var matrixA = MatrixLoader.GenerateRandomDenseMatrix(row, column);
             var factorSvd = matrixA.Svd(true);
-            var u = factorSvd.U();
-            var vt = factorSvd.VT();
+            var u = factorSvd.U;
+            var vt = factorSvd.VT;
             var w = factorSvd.W();
 
             // Make sure the U has the right dimensions.

src/UnitTests/LinearAlgebraTests/Complex32/Factorization/UserCholeskyTests.cs

@@ -27,7 +27,6 @@
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.Factorization
 {
     using System;
-    using LinearAlgebra.Complex32;
     using NUnit.Framework;
     using Complex32 = Numerics.Complex32;
 

src/UnitTests/LinearAlgebraTests/Complex32/Factorization/UserEvdTests.cs

@@ -28,7 +28,6 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.Factorization
 {
     using System;
     using System.Numerics;
-    using LinearAlgebra.Complex32;
     using LinearAlgebra.Complex32.Factorization;
     using NUnit.Framework;
     using Complex32 = Numerics.Complex32;
@@ -58,9 +57,9 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.Factorization
         {
             var matrixI = UserDefinedMatrix.Identity(order);
             var factorEvd = matrixI.Evd();
-            var eigenValues = factorEvd.EigenValues();
-            var eigenVectors = factorEvd.EigenVectors();
-            var d = factorEvd.D();
+            var eigenValues = factorEvd.EigenValues;
+            var eigenVectors = factorEvd.EigenVectors;
+            var d = factorEvd.D;
 
             Assert.AreEqual(matrixI.RowCount, eigenVectors.RowCount);
             Assert.AreEqual(matrixI.RowCount, eigenVectors.ColumnCount);
@@ -88,8 +87,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.Factorization
         {
             var matrixA = MatrixLoader.GenerateRandomUserDefinedMatrix(order, order);
             var factorEvd = matrixA.Evd();
-            var eigenVectors = factorEvd.EigenVectors();
-            var d = factorEvd.D();
+            var eigenVectors = factorEvd.EigenVectors;
+            var d = factorEvd.D;
 
             Assert.AreEqual(order, eigenVectors.RowCount);
             Assert.AreEqual(order, eigenVectors.ColumnCount);
@@ -120,8 +119,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.Factorization
         {
             var matrixA = MatrixLoader.GenerateRandomPositiveDefiniteHermitianUserDefinedMatrix(order);
             var factorEvd = matrixA.Evd();
-            var eigenVectors = factorEvd.EigenVectors();
-            var d = factorEvd.D();
+            var eigenVectors = factorEvd.EigenVectors;
+            var d = factorEvd.D;
 
             Assert.AreEqual(order, eigenVectors.RowCount);
             Assert.AreEqual(order, eigenVectors.ColumnCount);

src/UnitTests/LinearAlgebraTests/Complex32/Factorization/UserGramSchmidtTests.cs

@@ -1,4 +1,4 @@
-// <copyright file="UserGramSchmidtTests.cs" company="Math.NET">
+// <copyright file="UserGramSchmidtTests.cs" company="Math.NET">
 // Math.NET Numerics, part of the Math.NET Project
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
@@ -27,7 +27,6 @@
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.Factorization
 {
     using System;
-    using LinearAlgebra.Complex32;
     using LinearAlgebra.Complex32.Factorization;
     using NUnit.Framework;
     using Complex32 = Numerics.Complex32;

src/UnitTests/LinearAlgebraTests/Complex32/Factorization/UserLUTests.cs

@@ -27,7 +27,6 @@
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.Factorization
 {
     using System;
-    using LinearAlgebra.Complex32;
     using NUnit.Framework;
     using Complex32 = Numerics.Complex32;
 

src/UnitTests/LinearAlgebraTests/Complex32/Factorization/UserQRTests.cs

@@ -1,4 +1,4 @@
-// <copyright file="UserQRTests.cs" company="Math.NET">
+// <copyright file="UserQRTests.cs" company="Math.NET">
 // Math.NET Numerics, part of the Math.NET Project
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
@@ -24,7 +24,6 @@
 // OTHER DEALINGS IN THE SOFTWARE.
 // </copyright>
 
-using MathNet.Numerics.LinearAlgebra.Complex32;
 using MathNet.Numerics.LinearAlgebra.Complex32.Factorization;
 using MathNet.Numerics.LinearAlgebra.Factorization;
 using NUnit.Framework;

src/UnitTests/LinearAlgebraTests/Complex32/Factorization/UserSvdTests.cs

@@ -27,7 +27,6 @@
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.Factorization
 {
     using System;
-    using LinearAlgebra.Complex32;
     using LinearAlgebra.Complex32.Factorization;
     using NUnit.Framework;
     using Complex32 = Numerics.Complex32;
@@ -57,8 +56,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.Factorization
         {
             var matrixI = UserDefinedMatrix.Identity(order);
             var factorSvd = matrixI.Svd(true);
-            var u = factorSvd.U();
-            var vt = factorSvd.VT();
+            var u = factorSvd.U;
+            var vt = factorSvd.VT;
             var w = factorSvd.W();
 
             Assert.AreEqual(matrixI.RowCount, u.RowCount);
@@ -94,8 +93,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.Factorization
         {
             var matrixA = MatrixLoader.GenerateRandomUserDefinedMatrix(row, column);
             var factorSvd = matrixA.Svd(true);
-            var u = factorSvd.U();
-            var vt = factorSvd.VT();
+            var u = factorSvd.U;
+            var vt = factorSvd.VT;
             var w = factorSvd.W();
 
             // Make sure the U has the right dimensions.

src/UnitTests/LinearAlgebraTests/Complex32/Solvers/IteratorTest.cs

@@ -31,7 +31,6 @@
 using System;
 using System.Collections.Generic;
 using MathNet.Numerics.LinearAlgebra.Complex32;
-using MathNet.Numerics.LinearAlgebra.Complex32.Solvers;
 using MathNet.Numerics.LinearAlgebra.Complex32.Solvers.StopCriterium;
 using MathNet.Numerics.LinearAlgebra.Solvers;
 using MathNet.Numerics.LinearAlgebra.Solvers.Status;

src/UnitTests/LinearAlgebraTests/Complex32/UserDefinedMatrix.cs

@@ -24,7 +24,6 @@
 // OTHER DEALINGS IN THE SOFTWARE.
 // </copyright>
 
-using MathNet.Numerics.LinearAlgebra;
 using MathNet.Numerics.LinearAlgebra.Complex32;
 using MathNet.Numerics.LinearAlgebra.Storage;
 

src/UnitTests/LinearAlgebraTests/Complex32/UserDefinedVector.cs

@@ -24,7 +24,6 @@
 // OTHER DEALINGS IN THE SOFTWARE.
 // </copyright>
 
-using MathNet.Numerics.LinearAlgebra;
 using MathNet.Numerics.LinearAlgebra.Complex32;
 using MathNet.Numerics.LinearAlgebra.Storage;
 

src/UnitTests/LinearAlgebraTests/Double/Factorization/EvdTests.cs

@@ -57,9 +57,9 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.Factorization
         {
             var matrixI = DenseMatrix.Identity(order);
             var factorEvd = matrixI.Evd();
-            var eigenValues = factorEvd.EigenValues();
-            var eigenVectors = factorEvd.EigenVectors();
-            var d = factorEvd.D();
+            var eigenValues = factorEvd.EigenValues;
+            var eigenVectors = factorEvd.EigenVectors;
+            var d = factorEvd.D;
 
             Assert.AreEqual(matrixI.RowCount, eigenVectors.RowCount);
             Assert.AreEqual(matrixI.RowCount, eigenVectors.ColumnCount);
@@ -87,8 +87,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.Factorization
         {
             var matrixA = MatrixLoader.GenerateRandomDenseMatrix(order, order);
             var factorEvd = matrixA.Evd();
-            var eigenVectors = factorEvd.EigenVectors();
-            var d = factorEvd.D();
+            var eigenVectors = factorEvd.EigenVectors;
+            var d = factorEvd.D;
 
             Assert.AreEqual(order, eigenVectors.RowCount);
             Assert.AreEqual(order, eigenVectors.ColumnCount);
@@ -98,7 +98,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.Factorization
 
             // Make sure the A*V = λ*V 
             var matrixAv = matrixA * eigenVectors;
-            var matrixLv = eigenVectors * factorEvd.D();
+            var matrixLv = eigenVectors * factorEvd.D;
 
             for (var i = 0; i < matrixAv.RowCount; i++)
             {
@@ -124,8 +124,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.Factorization
             var matrixA = MatrixLoader.GenerateRandomPositiveDefiniteDenseMatrix(order);
             MatrixHelpers.ForceSymmetric(matrixA);
             var factorEvd = matrixA.Evd();
-            var eigenVectors = factorEvd.EigenVectors();
-            var d = factorEvd.D();
+            var eigenVectors = factorEvd.EigenVectors;
+            var d = factorEvd.D;
             
             Assert.AreEqual(order, eigenVectors.RowCount);
             Assert.AreEqual(order, eigenVectors.ColumnCount);

src/UnitTests/LinearAlgebraTests/Double/Factorization/SvdTests.cs

@@ -56,8 +56,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.Factorization
         {
             var matrixI = DenseMatrix.Identity(order);
             var factorSvd = matrixI.Svd(true);
-            var u = factorSvd.U();
-            var vt = factorSvd.VT();
+            var u = factorSvd.U;
+            var vt = factorSvd.VT;
             var w = factorSvd.W();
 
             Assert.AreEqual(matrixI.RowCount, u.RowCount);
@@ -93,8 +93,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.Factorization
         {
             var matrixA = MatrixLoader.GenerateRandomDenseMatrix(row, column);
             var factorSvd = matrixA.Svd(true);
-            var u = factorSvd.U();
-            var vt = factorSvd.VT();
+            var u = factorSvd.U;
+            var vt = factorSvd.VT;
             var w = factorSvd.W();
 
             // Make sure the U has the right dimensions.

src/UnitTests/LinearAlgebraTests/Double/Factorization/UserCholeskyTests.cs

@@ -27,7 +27,6 @@
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.Factorization
 {
     using System;
-    using LinearAlgebra.Double;
     using NUnit.Framework;
 
     /// <summary>

src/UnitTests/LinearAlgebraTests/Double/Factorization/UserEvdTests.cs

@@ -28,7 +28,6 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.Factorization
 {
     using System;
     using System.Numerics;
-    using LinearAlgebra.Double;
     using LinearAlgebra.Double.Factorization;
     using NUnit.Framework;
 
@@ -57,9 +56,9 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.Factorization
         {
             var matrixI = UserDefinedMatrix.Identity(order);
             var factorEvd = matrixI.Evd();
-            var eigenValues = factorEvd.EigenValues();
-            var eigenVectors = factorEvd.EigenVectors();
-            var d = factorEvd.D();
+            var eigenValues = factorEvd.EigenValues;
+            var eigenVectors = factorEvd.EigenVectors;
+            var d = factorEvd.D;
 
             Assert.AreEqual(matrixI.RowCount, eigenVectors.RowCount);
             Assert.AreEqual(matrixI.RowCount, eigenVectors.ColumnCount);
@@ -87,8 +86,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.Factorization
         {
             var matrixA = MatrixLoader.GenerateRandomUserDefinedMatrix(order, order);
             var factorEvd = matrixA.Evd();
-            var eigenVectors = factorEvd.EigenVectors();
-            var d = factorEvd.D();
+            var eigenVectors = factorEvd.EigenVectors;
+            var d = factorEvd.D;
 
             Assert.AreEqual(order, eigenVectors.RowCount);
             Assert.AreEqual(order, eigenVectors.ColumnCount);
@@ -123,8 +122,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.Factorization
         {
             var matrixA = MatrixLoader.GenerateRandomPositiveDefiniteUserDefinedMatrix(order);
             var factorEvd = matrixA.Evd();
-            var eigenVectors = factorEvd.EigenVectors();
-            var d = factorEvd.D();
+            var eigenVectors = factorEvd.EigenVectors;
+            var d = factorEvd.D;
 
             Assert.AreEqual(order, eigenVectors.RowCount);
             Assert.AreEqual(order, eigenVectors.ColumnCount);

src/UnitTests/LinearAlgebraTests/Double/Factorization/UserGramSchmidtTests.cs

@@ -27,7 +27,6 @@
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.Factorization
 {
     using System;
-    using LinearAlgebra.Double;
     using LinearAlgebra.Double.Factorization;
     using NUnit.Framework;