LA: matrix construction rework #104

src/Examples/LinearAlgebra/DirectSolvers.cs

@@ -73,7 +73,7 @@ namespace Examples.LinearAlgebraExamples
             // 4*x + 1*y + 5*z = 43
 
             // Create matrix "A" with coefficients 
-            var matrixA = new DenseMatrix(new[,] { { 5.00, 2.00, -4.00 }, { 3.00, -7.00, 6.00 }, { 4.00, 1.00, 5.00 } });
+            var matrixA = DenseMatrix.OfArray(new[,] { { 5.00, 2.00, -4.00 }, { 3.00, -7.00, 6.00 }, { 4.00, 1.00, 5.00 } });
             Console.WriteLine(@"Matrix 'A' with coefficients");
             Console.WriteLine(matrixA.ToString("#0.00\t", formatProvider));
             Console.WriteLine();

src/Examples/LinearAlgebra/Factorization/Cholesky.cs

@@ -70,7 +70,7 @@ namespace Examples.LinearAlgebra.FactorizationExamples
             formatProvider.TextInfo.ListSeparator = " ";
 
             // Create square, symmetric, positive definite matrix
-            var matrix = new DenseMatrix(new[,] { { 2.0, 1.0 }, { 1.0, 2.0 } });
+            var matrix = DenseMatrix.OfArray(new[,] { { 2.0, 1.0 }, { 1.0, 2.0 } });
             Console.WriteLine(@"Initial square, symmetric, positive definite matrix");
             Console.WriteLine(matrix.ToString("#0.00\t", formatProvider));
             Console.WriteLine();

src/Examples/LinearAlgebra/Factorization/Evd.cs

@@ -76,7 +76,7 @@ namespace Examples.LinearAlgebra.FactorizationExamples
             formatProvider.TextInfo.ListSeparator = " ";
 
             // Create square symmetric matrix
-            var matrix = new DenseMatrix(new[,] { { 1.0, 2.0, 3.0 }, { 2.0, 1.0, 4.0 }, { 3.0, 4.0, 1.0 } });
+            var matrix = DenseMatrix.OfArray(new[,] { { 1.0, 2.0, 3.0 }, { 2.0, 1.0, 4.0 }, { 3.0, 4.0, 1.0 } });
             Console.WriteLine(@"Initial square symmetric matrix");
             Console.WriteLine(matrix.ToString("#0.00\t", formatProvider));
             Console.WriteLine();

src/Examples/LinearAlgebra/Factorization/LU.cs

@@ -73,7 +73,7 @@ namespace Examples.LinearAlgebra.FactorizationExamples
             formatProvider.TextInfo.ListSeparator = " ";
 
             // Create square matrix
-            var matrix = new DenseMatrix(new[,] { { 1.0, 2.0 }, { 3.0, 4.0 } });
+            var matrix = DenseMatrix.OfArray(new[,] { { 1.0, 2.0 }, { 3.0, 4.0 } });
             Console.WriteLine(@"Initial square matrix");
             Console.WriteLine(matrix.ToString("#0.00\t", formatProvider));
             Console.WriteLine();

src/Examples/LinearAlgebra/Factorization/QR.cs

@@ -72,7 +72,7 @@ namespace Examples.LinearAlgebra.FactorizationExamples
             formatProvider.TextInfo.ListSeparator = " ";
 
             // Create 3 x 2 matrix
-            var matrix = new DenseMatrix(new[,] { { 1.0, 2.0 }, { 3.0, 4.0 }, { 5.0, 6.0 } });
+            var matrix = DenseMatrix.OfArray(new[,] { { 1.0, 2.0 }, { 3.0, 4.0 }, { 5.0, 6.0 } });
             Console.WriteLine(@"Initial 3x2 matrix");
             Console.WriteLine(matrix.ToString("#0.00\t", formatProvider));
             Console.WriteLine();

src/Examples/LinearAlgebra/Factorization/Svd.cs

@@ -76,7 +76,7 @@ namespace Examples.LinearAlgebra.FactorizationExamples
             formatProvider.TextInfo.ListSeparator = " ";
 
             // Create square matrix
-            var matrix = new DenseMatrix(new[,] { { 4.0, 1.0 }, { 3.0, 2.0 } });
+            var matrix = DenseMatrix.OfArray(new[,] { { 4.0, 1.0 }, { 3.0, 2.0 } });
             Console.WriteLine(@"Initial square matrix");
             Console.WriteLine(matrix.ToString("#0.00\t", formatProvider));
             Console.WriteLine();

src/Examples/LinearAlgebra/IterativeSolvers/BiCgStabSolver.cs

@@ -77,7 +77,7 @@ namespace Examples.LinearAlgebra.IterativeSolversExamples
             // 4*x + 1*y + 5*z = 43
 
             // Create matrix "A" with coefficients 
-            var matrixA = new DenseMatrix(new[,] { { 5.00, 2.00, -4.00 }, { 3.00, -7.00, 6.00 }, { 4.00, 1.00, 5.00 } });
+            var matrixA = DenseMatrix.OfArray(new[,] { { 5.00, 2.00, -4.00 }, { 3.00, -7.00, 6.00 }, { 4.00, 1.00, 5.00 } });
             Console.WriteLine(@"Matrix 'A' with coefficients");
             Console.WriteLine(matrixA.ToString("#0.00\t", formatProvider));
             Console.WriteLine();

src/Examples/LinearAlgebra/IterativeSolvers/CompositeSolverExample.cs

@@ -76,7 +76,7 @@ namespace Examples.LinearAlgebra.IterativeSolversExamples
             // 4*x + 1*y + 5*z = 43
 
             // Create matrix "A" with coefficients 
-            var matrixA = new DenseMatrix(new[,] { { 5.00, 2.00, -4.00 }, { 3.00, -7.00, 6.00 }, { 4.00, 1.00, 5.00 } });
+            var matrixA = DenseMatrix.OfArray(new[,] { { 5.00, 2.00, -4.00 }, { 3.00, -7.00, 6.00 }, { 4.00, 1.00, 5.00 } });
             Console.WriteLine(@"Matrix 'A' with coefficients");
             Console.WriteLine(matrixA.ToString("#0.00\t", formatProvider));
             Console.WriteLine();

src/Examples/LinearAlgebra/IterativeSolvers/GpBiCgSolver.cs

@@ -75,7 +75,7 @@ namespace Examples.LinearAlgebra.IterativeSolversExamples
             // 4*x + 1*y + 5*z = 43
 
             // Create matrix "A" with coefficients 
-            var matrixA = new DenseMatrix(new[,] { { 5.00, 2.00, -4.00 }, { 3.00, -7.00, 6.00 }, { 4.00, 1.00, 5.00 } });
+            var matrixA = DenseMatrix.OfArray(new[,] { { 5.00, 2.00, -4.00 }, { 3.00, -7.00, 6.00 }, { 4.00, 1.00, 5.00 } });
             Console.WriteLine(@"Matrix 'A' with coefficients");
             Console.WriteLine(matrixA.ToString("#0.00\t", formatProvider));
             Console.WriteLine();

src/Examples/LinearAlgebra/IterativeSolvers/MlkBiCgStabSolver.cs

@@ -76,7 +76,7 @@ namespace Examples.LinearAlgebra.IterativeSolversExamples
             // 4*x + 1*y + 5*z = 43
 
             // Create matrix "A" with coefficients 
-            var matrixA = new DenseMatrix(new[,] { { 5.00, 2.00, -4.00 }, { 3.00, -7.00, 6.00 }, { 4.00, 1.00, 5.00 } });
+            var matrixA = DenseMatrix.OfArray(new[,] { { 5.00, 2.00, -4.00 }, { 3.00, -7.00, 6.00 }, { 4.00, 1.00, 5.00 } });
             Console.WriteLine(@"Matrix 'A' with coefficients");
             Console.WriteLine(matrixA.ToString("#0.00\t", formatProvider));
             Console.WriteLine();

src/Examples/LinearAlgebra/IterativeSolvers/TFQMRSolver.cs

@@ -76,7 +76,7 @@ namespace Examples.LinearAlgebra.IterativeSolversExamples
             // 4*x + 1*y + 5*z = 43
 
             // Create matrix "A" with coefficients 
-            var matrixA = new DenseMatrix(new[,] { { 5.00, 2.00, -4.00 }, { 3.00, -7.00, 6.00 }, { 4.00, 1.00, 5.00 } });
+            var matrixA = DenseMatrix.OfArray(new[,] { { 5.00, 2.00, -4.00 }, { 3.00, -7.00, 6.00 }, { 4.00, 1.00, 5.00 } });
             Console.WriteLine(@"Matrix 'A' with coefficients");
             Console.WriteLine(matrixA.ToString("#0.00\t", formatProvider));
             Console.WriteLine();

src/Examples/LinearAlgebra/MatrixArithmeticOperations.cs

@@ -73,13 +73,13 @@ namespace Examples.LinearAlgebraExamples
             formatProvider.TextInfo.ListSeparator = " ";
 
             // Create matrix "A"
-            var matrixA = new DenseMatrix(new[,] { { 1.0, 2.0, 3.0 }, { 4.0, 5.0, 6.0 }, { 7.0, 8.0, 9.0 } });
+            var matrixA = DenseMatrix.OfArray(new[,] { { 1.0, 2.0, 3.0 }, { 4.0, 5.0, 6.0 }, { 7.0, 8.0, 9.0 } });
             Console.WriteLine(@"Matrix A");
             Console.WriteLine(matrixA.ToString("#0.00\t", formatProvider));
             Console.WriteLine();
 
             // Create matrix "B"
-            var matrixB = new DenseMatrix(new[,] { { 1.0, 3.0, 5.0 }, { 2.0, 4.0, 6.0 }, { 3.0, 5.0, 7.0 } });
+            var matrixB = DenseMatrix.OfArray(new[,] { { 1.0, 3.0, 5.0 }, { 2.0, 4.0, 6.0 }, { 3.0, 5.0, 7.0 } });
             Console.WriteLine(@"Matrix B");
             Console.WriteLine(matrixB.ToString("#0.00\t", formatProvider));
             Console.WriteLine();

src/Examples/LinearAlgebra/MatrixInitialization.cs

@@ -63,7 +63,7 @@ namespace Examples.LinearAlgebraExamples
         public void Run()
         {
             // 1. Initialize a new instance of the matrix from a 2D array. This constructor will allocate a completely new memory block for storing the dense matrix.
-            var matrix1 = new DenseMatrix(new[,] { { 1.0, 2.0, 3.0 }, { 4.0, 5.0, 6.0 } });
+            var matrix1 = DenseMatrix.OfArray(new[,] { { 1.0, 2.0, 3.0 }, { 4.0, 5.0, 6.0 } });
 
             // 2. Initialize a new instance of the empty square matrix with a given order.
             var matrix2 = new DenseMatrix(3);

src/Examples/LinearAlgebra/MatrixNorms.cs

@@ -68,7 +68,7 @@ namespace Examples.LinearAlgebraExamples
             formatProvider.TextInfo.ListSeparator = " ";
 
             // Create square matrix
-            var matrix = new DenseMatrix(new[,] { { 1.0, 2.0, 3.0 }, { 6.0, 5.0, 4.0 }, { 8.0, 9.0, 7.0 } });
+            var matrix = DenseMatrix.OfArray(new[,] { { 1.0, 2.0, 3.0 }, { 6.0, 5.0, 4.0 }, { 8.0, 9.0, 7.0 } });
             Console.WriteLine(@"Initial square matrix");
             Console.WriteLine(matrix.ToString("#0.00\t", formatProvider));
             Console.WriteLine();

src/FSharp/LinearAlgebra.Double.Matrix.fs

@@ -275,7 +275,7 @@ module DenseMatrix =
         A
 
     /// Create a matrix from a 2D array of floating point numbers.
-    let inline ofArray2 (arr: float[,]) = new DenseMatrix(arr)
+    let inline ofArray2 (arr: float[,]) = DenseMatrix.OfArray(arr)
 
     /// Create a matrix with the given entries.
     let inline initDense (n: int) (m: int) (es: #seq<int * int * float>) =

src/FSharpUnitTests/DenseMatrixTests.fs

@@ -9,10 +9,10 @@ open MathNet.Numerics.LinearAlgebra.Double
 module DenseMatrixTests =
 
     /// A small uniform vector.
-    let smallM = new DenseMatrix( Array2D.create 2 2 0.3 )
+    let smallM = DenseMatrix.OfArray( Array2D.create 2 2 0.3 )
 
     /// A large vector with increasingly large entries
-    let largeM = new DenseMatrix( Array2D.init 100 100 (fun i j -> float i * 100.0 + float j) )
+    let largeM = DenseMatrix.OfArray( Array2D.init 100 100 (fun i j -> float i * 100.0 + float j) )
 
     [<Test>]
     let ``DenseMatrix.init`` () =

src/FSharpUnitTests/MatrixTests.fs

@@ -9,11 +9,11 @@ open MathNet.Numerics.LinearAlgebra.Double
 module MatrixTests =
 
     /// A small uniform vector.
-    let smallM = new DenseMatrix( Array2D.create 2 2 0.3 )
+    let smallM = DenseMatrix.OfArray( Array2D.create 2 2 0.3 )
     let failingFoldBackM = DenseMatrix.init 2 3 (fun i j -> 1.0)
 
     /// A large vector with increasingly large entries
-    let largeM = new DenseMatrix( Array2D.init 100 100 (fun i j -> float i * 100.0 + float j) )
+    let largeM = DenseMatrix.OfArray( Array2D.init 100 100 (fun i j -> float i * 100.0 + float j) )
 
     [<Test>]
     let ``Matrix.GetSlice`` () =

src/Numerics/Distributions/Multivariate/Wishart.cs

@@ -313,7 +313,7 @@ namespace MathNet.Numerics.Distributions
 
             // First generate a lower triangular matrix with Sqrt(Chi-Squares) on the diagonal
             // and normal distributed variables in the lower triangle.
-            var a = new DenseMatrix(count, count, 0.0);
+            var a = new DenseMatrix(count, count);
             for (var d = 0; d < count; d++)
             {
                 a.At(d, d, Math.Sqrt(Gamma.Sample(rnd, (nu - d)/2.0, 0.5)));

src/Numerics/LinearAlgebra/Complex/DenseMatrix.cs

@@ -103,12 +103,65 @@ namespace MathNet.Numerics.LinearAlgebra.Complex
         {
         }
 
+        /// <summary>
+        /// Create a new dense matrix with the given number of rows and columns directly binding to a raw array.
+        /// The array is assumed to be in column-major order (column by column) and is used directly without copying.
+        /// Very efficient, but changes to the array and the matrix will affect each other.
+        /// </summary>
+        /// <seealso href="http://en.wikipedia.org/wiki/Row-major_order"/>
+        public DenseMatrix(int rows, int columns, Complex[] storage)
+            : this(new DenseColumnMajorMatrixStorage<Complex>(rows, columns, storage))
+        {
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given other matrix.
+        /// This new matrix will be independent from the other matrix.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static DenseMatrix OfMatrix(Matrix<Complex> matrix)
+        {
+            var storage = new DenseColumnMajorMatrixStorage<Complex>(matrix.RowCount, matrix.ColumnCount);
+            matrix.Storage.CopyToUnchecked(storage, skipClearing: true);
+            return new DenseMatrix(storage);
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given two-dimensional array.
+        /// This new matrix will be independent from the provided array.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static DenseMatrix OfArray(Complex[,] array)
+        {
+            var storage = new DenseColumnMajorMatrixStorage<Complex>(array.GetLength(0), array.GetLength(1));
+            for (var i = 0; i < storage.RowCount; i++)
+            {
+                for (var j = 0; j < storage.ColumnCount; j++)
+                {
+                    storage.Data[(j * storage.RowCount) + i] = array[i, j];
+                }
+            }
+            return new DenseMatrix(storage);
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given enumerable.
+        /// The enumerable is assumed to be in column-major order (column by column).
+        /// This new matrix will be independent from the enumerable.
+        /// A new memory block will be allocated for storing the vector.
+        /// </summary>
+        public static DenseMatrix OfColumnMajor(int rows, int columns, IEnumerable<Complex> columnMajor)
+        {
+            return new DenseMatrix(DenseColumnMajorMatrixStorage<Complex>.OfColumnMajorEnumerable(rows, columns, columnMajor));
+        }
+
         /// <summary>
         /// Create a new dense matrix with the given number of rows and columns.
         /// All cells of the matrix will be initialized to the provided value.
         /// Zero-length matrices are not supported.
         /// </summary>
         /// <exception cref="ArgumentException">If the row or column count is less than one.</exception>
+        [Obsolete("Scheduled for removal in v3.0.")]
         public DenseMatrix(int rows, int columns, Complex value)
             : this(rows, columns)
         {
@@ -118,22 +171,12 @@ namespace MathNet.Numerics.LinearAlgebra.Complex
             }
         }
 
-        /// <summary>
-        /// Create a new dense matrix with the given number of rows and columns directly binding to a raw array.
-        /// The array is assumed to be in column-major order (column by column) and is used directly without copying.
-        /// Very efficient, but changes to the array and the matrix will affect each other.
-        /// </summary>
-        /// <seealso cref="http://en.wikipedia.org/wiki/Row-major_order"/>
-        public DenseMatrix(int rows, int columns, Complex[] storage)
-            : this(new DenseColumnMajorMatrixStorage<Complex>(rows, columns, storage))
-        {
-        }
-
         /// <summary>
         /// Create a new dense matrix as a copy of the given two-dimensional array.
         /// This new matrix will be independent from the provided array.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
+        [Obsolete("Use DenseMatrix.OfArray instead. Scheduled for removal in v3.0.")]
         public DenseMatrix(Complex[,] array)
             : this(array.GetLength(0), array.GetLength(1))
         {
@@ -145,23 +188,13 @@ namespace MathNet.Numerics.LinearAlgebra.Complex
                 }
             }
         }
-        
-        /// <summary>
-        /// Create a new dense matrix as a copy of the given enumerable.
-        /// The enumerable is assumed to be in column-major order (column by column).
-        /// This new matrix will be independent from the enumerable.
-        /// A new memory block will be allocated for storing the vector.
-        /// </summary>
-        public DenseMatrix(int rows, int columns, IEnumerable<Complex> columnMajor)
-            : this(DenseColumnMajorMatrixStorage<Complex>.FromColumnMajorEnumerable(rows, columns, columnMajor))
-        {
-        }
 
         /// <summary>
         /// Create a new dense matrix as a copy of the given other matrix.
         /// This new matrix will be independent from the other matrix.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
+        [Obsolete("Use DenseMatrix.OfMatrix instead. Scheduled for removal in v3.0.")]
         public DenseMatrix(Matrix<Complex> matrix)
             : this(matrix.RowCount, matrix.ColumnCount)
         {

src/Numerics/LinearAlgebra/Complex/DenseVector.cs

@@ -113,7 +113,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex
         /// A new memory block will be allocated for storing the vector.
         /// </summary>
         public DenseVector(IEnumerable<Complex> other)
-            : this(DenseVectorStorage<Complex>.FromEnumerable(other))
+            : this(DenseVectorStorage<Complex>.OfEnumerable(other))
         {
         }
 

src/Numerics/LinearAlgebra/Complex/Solvers/Preconditioners/Ilutp.cs

@@ -314,7 +314,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Solvers.Preconditioners
                 throw new ArgumentException(Resources.ArgumentMatrixSquare, "matrix");
             }
 
-            var sparseMatrix = (matrix is SparseMatrix) ? matrix as SparseMatrix : new SparseMatrix(matrix);
+            var sparseMatrix = (matrix is SparseMatrix) ? matrix as SparseMatrix : SparseMatrix.OfMatrix(matrix);
 
             // The creation of the preconditioner follows the following algorithm.
             // spaceLeft = lfilNnz * nnz(A)

src/Numerics/LinearAlgebra/Complex/Solvers/Preconditioners/IncompleteLU.cs

@@ -112,7 +112,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex.Solvers.Preconditioners
                 throw new ArgumentException(Resources.ArgumentMatrixSquare, "matrix");
             }
 
-            _decompositionLU = new SparseMatrix(matrix);
+            _decompositionLU = SparseMatrix.OfMatrix(matrix);
 
             // M == A
             // for i = 2, ... , n do

src/Numerics/LinearAlgebra/Complex/SparseMatrix.cs

@@ -70,6 +70,17 @@ namespace MathNet.Numerics.LinearAlgebra.Complex
             _storage = storage;
         }
 
+        /// <summary>
+        /// Create a new square sparse matrix with the given number of rows and columns.
+        /// All cells of the matrix will be initialized to zero.
+        /// Zero-length matrices are not supported.
+        /// </summary>
+        /// <exception cref="ArgumentException">If the order is less than one.</exception>
+        public SparseMatrix(int order)
+            : this(order, order)
+        {
+        }
+
         /// <summary>
         /// Create a new sparse matrix with the given number of rows and columns.
         /// All cells of the matrix will be initialized to zero.
@@ -82,14 +93,70 @@ namespace MathNet.Numerics.LinearAlgebra.Complex
         }
 
         /// <summary>
-        /// Create a new square sparse matrix with the given number of rows and columns.
+        /// Create a new sparse matrix as a copy of the given other matrix.
-        /// All cells of the matrix will be initialized to zero.
+        /// This new matrix will be independent from the other matrix.
-        /// Zero-length matrices are not supported.
+        /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        /// <exception cref="ArgumentException">If the order is less than one.</exception>
+        public static SparseMatrix OfMatrix(Matrix<Complex> matrix)
-        public SparseMatrix(int order)
+        {
-            : this(order, order)
+            var storage = new SparseCompressedRowMatrixStorage<Complex>(matrix.RowCount, matrix.ColumnCount);
+            matrix.Storage.CopyToUnchecked(storage, skipClearing: true);
+            return new SparseMatrix(storage);
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given two-dimensional array.
+        /// This new matrix will be independent from the provided array.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfArray(Complex[,] array)
+        {
+            var storage = new SparseCompressedRowMatrixStorage<Complex>(array.GetLength(0), array.GetLength(1));
+            for (var i = 0; i < storage.RowCount; i++)
+            {
+                for (var j = 0; j < storage.ColumnCount; j++)
+                {
+                    storage.At(i, j, array[i, j]);
+                }
+            }
+            return new SparseMatrix(storage);
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given enumerable.
+        /// The enumerable is assumed to be in row-major order (row by row).
+        /// This new matrix will be independent from the enumerable.
+        /// A new memory block will be allocated for storing the vector.
+        /// </summary>
+        /// <seealso href="http://en.wikipedia.org/wiki/Row-major_order"/>
+        public static SparseMatrix OfRowMajor(int rows, int columns, IEnumerable<Complex> rowMajor)
         {
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<Complex>.OfRowMajorEnumerable(rows, columns, rowMajor));
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix with the given number of rows and columns as a copy of the given array.
+        /// The array is assumed to be in column-major order (column by column).
+        /// This new matrix will be independent from the provided array.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        /// <seealso href="http://en.wikipedia.org/wiki/Row-major_order"/>
+        public static SparseMatrix OfColumnMajor(int rows, int columns, Complex[] array)
+        {
+            if (rows * columns > array.Length)
+            {
+                throw new ArgumentOutOfRangeException(Resources.ArgumentMatrixDimensions);
+            }
+
+            var storage = new SparseCompressedRowMatrixStorage<Complex>(rows, columns);
+            for (var i = 0; i < rows; i++)
+            {
+                for (var j = 0; j < columns; j++)
+                {
+                    storage.At(i, j, array[i + (j * rows)]);
+                }
+            }
+            return new SparseMatrix(storage);
         }
 
         /// <summary>
@@ -137,7 +204,8 @@ namespace MathNet.Numerics.LinearAlgebra.Complex
         /// This new matrix will be independent from the provided array.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        /// <seealso cref="http://en.wikipedia.org/wiki/Row-major_order"/>
+        /// <seealso href="http://en.wikipedia.org/wiki/Row-major_order"/>
+        [Obsolete("Use SparseMatrix.OfColumnMajor instead. Scheduled for removal in v3.0.")]
         public SparseMatrix(int rows, int columns, Complex[] array)
             : this(rows, columns)
         {
@@ -160,6 +228,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex
         /// This new matrix will be independent from the provided array.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
+        [Obsolete("Use SparseMatrix.OfArray instead. Scheduled for removal in v3.0.")]
         public SparseMatrix(Complex[,] array)
             : this(array.GetLength(0), array.GetLength(1))
         {
@@ -172,22 +241,12 @@ namespace MathNet.Numerics.LinearAlgebra.Complex
             }
         }
 
-        /// <summary>
-        /// Create a new sparse matrix as a copy of the given enumerable.
-        /// The enumerable is assumed to be in row-major order (row by row).
-        /// This new matrix will be independent from the enumerable.
-        /// A new memory block will be allocated for storing the vector.
-        /// </summary>
-        public SparseMatrix(int rows, int columns, IEnumerable<Complex> rowMajor)
-            : this(SparseCompressedRowMatrixStorage<Complex>.FromRowMajorEnumerable(rows, columns, rowMajor))
-        {
-        }
-
         /// <summary>
         /// Create a new sparse matrix as a copy of the given other matrix.
         /// This new matrix will be independent from the other matrix.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
+        [Obsolete("Use SparseMatrix.OfMatrix instead. Scheduled for removal in v3.0.")]
         public SparseMatrix(Matrix<Complex> matrix)
             : this(matrix.RowCount, matrix.ColumnCount)
         {

src/Numerics/LinearAlgebra/Complex/SparseVector.cs

@@ -124,7 +124,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex
         /// A new memory block will be allocated for storing the vector.
         /// </summary>
         public SparseVector(IEnumerable<Complex> other)
-            : this(SparseVectorStorage<Complex>.FromEnumerable(other))
+            : this(SparseVectorStorage<Complex>.OfEnumerable(other))
         {
         }
 

src/Numerics/LinearAlgebra/Complex32/DenseMatrix.cs

@@ -103,12 +103,65 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32
         {
         }
 
+        /// <summary>
+        /// Create a new dense matrix with the given number of rows and columns directly binding to a raw array.
+        /// The array is assumed to be in column-major order (column by column) and is used directly without copying.
+        /// Very efficient, but changes to the array and the matrix will affect each other.
+        /// </summary>
+        /// <seealso href="http://en.wikipedia.org/wiki/Row-major_order"/>
+        public DenseMatrix(int rows, int columns, Complex32[] storage)
+            : this(new DenseColumnMajorMatrixStorage<Complex32>(rows, columns, storage))
+        {
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given other matrix.
+        /// This new matrix will be independent from the other matrix.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static DenseMatrix OfMatrix(Matrix<Complex32> matrix)
+        {
+            var storage = new DenseColumnMajorMatrixStorage<Complex32>(matrix.RowCount, matrix.ColumnCount);
+            matrix.Storage.CopyToUnchecked(storage, skipClearing: true);
+            return new DenseMatrix(storage);
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given two-dimensional array.
+        /// This new matrix will be independent from the provided array.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static DenseMatrix OfArray(Complex32[,] array)
+        {
+            var storage = new DenseColumnMajorMatrixStorage<Complex32>(array.GetLength(0), array.GetLength(1));
+            for (var i = 0; i < storage.RowCount; i++)
+            {
+                for (var j = 0; j < storage.ColumnCount; j++)
+                {
+                    storage.Data[(j * storage.RowCount) + i] = array[i, j];
+                }
+            }
+            return new DenseMatrix(storage);
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given enumerable.
+        /// The enumerable is assumed to be in column-major order (column by column).
+        /// This new matrix will be independent from the enumerable.
+        /// A new memory block will be allocated for storing the vector.
+        /// </summary>
+        public static DenseMatrix OfColumnMajor(int rows, int columns, IEnumerable<Complex32> columnMajor)
+        {
+            return new DenseMatrix(DenseColumnMajorMatrixStorage<Complex32>.OfColumnMajorEnumerable(rows, columns, columnMajor));
+        }
+
         /// <summary>
         /// Create a new dense matrix with the given number of rows and columns.
         /// All cells of the matrix will be initialized to the provided value.
         /// Zero-length matrices are not supported.
         /// </summary>
         /// <exception cref="ArgumentException">If the row or column count is less than one.</exception>
+        [Obsolete("Scheduled for removal in v3.0.")]
         public DenseMatrix(int rows, int columns, Complex32 value)
             : this(rows, columns)
         {
@@ -118,22 +171,12 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32
             }
         }
 
-        /// <summary>
-        /// Create a new dense matrix with the given number of rows and columns directly binding to a raw array.
-        /// The array is assumed to be in column-major order (column by column) and is used directly without copying.
-        /// Very efficient, but changes to the array and the matrix will affect each other.
-        /// </summary>
-        /// <seealso cref="http://en.wikipedia.org/wiki/Row-major_order"/>
-        public DenseMatrix(int rows, int columns, Complex32[] storage)
-            : this(new DenseColumnMajorMatrixStorage<Complex32>(rows, columns, storage))
-        {
-        }
-
         /// <summary>
         /// Create a new dense matrix as a copy of the given two-dimensional array.
         /// This new matrix will be independent from the provided array.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
+        [Obsolete("Use DenseMatrix.OfArray instead. Scheduled for removal in v3.0.")]
         public DenseMatrix(Complex32[,] array)
             : this(array.GetLength(0), array.GetLength(1))
         {
@@ -145,23 +188,13 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32
                 }
             }
         }
-        
-        /// <summary>
-        /// Create a new dense matrix as a copy of the given enumerable.
-        /// The enumerable is assumed to be in column-major order (column by column).
-        /// This new matrix will be independent from the enumerable.
-        /// A new memory block will be allocated for storing the vector.
-        /// </summary>
-        public DenseMatrix(int rows, int columns, IEnumerable<Complex32> columnMajor)
-            : this(DenseColumnMajorMatrixStorage<Complex32>.FromColumnMajorEnumerable(rows, columns, columnMajor))
-        {
-        }
 
         /// <summary>
         /// Create a new dense matrix as a copy of the given other matrix.
         /// This new matrix will be independent from the other matrix.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
+        [Obsolete("Use DenseMatrix.OfMatrix instead. Scheduled for removal in v3.0.")]
         public DenseMatrix(Matrix<Complex32> matrix)
             : this(matrix.RowCount, matrix.ColumnCount)
         {

src/Numerics/LinearAlgebra/Complex32/DenseVector.cs

@@ -113,7 +113,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32
         /// A new memory block will be allocated for storing the vector.
         /// </summary>
         public DenseVector(IEnumerable<Complex32> other)
-            : this(DenseVectorStorage<Complex32>.FromEnumerable(other))
+            : this(DenseVectorStorage<Complex32>.OfEnumerable(other))
         {
         }
 

src/Numerics/LinearAlgebra/Complex32/Solvers/Preconditioners/Ilutp.cs

@@ -314,7 +314,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Solvers.Preconditioners
                 throw new ArgumentException(Resources.ArgumentMatrixSquare, "matrix");
             }
 
-            var sparseMatrix = (matrix is SparseMatrix) ? matrix as SparseMatrix : new SparseMatrix(matrix);
+            var sparseMatrix = (matrix is SparseMatrix) ? matrix as SparseMatrix : SparseMatrix.OfMatrix(matrix);
 
             // The creation of the preconditioner follows the following algorithm.
             // spaceLeft = lfilNnz * nnz(A)

src/Numerics/LinearAlgebra/Complex32/Solvers/Preconditioners/IncompleteLU.cs

@@ -112,7 +112,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32.Solvers.Preconditioners
                 throw new ArgumentException(Resources.ArgumentMatrixSquare, "matrix");
             }
 
-            _decompositionLU = new SparseMatrix(matrix);
+            _decompositionLU = SparseMatrix.OfMatrix(matrix);
 
             // M == A
             // for i = 2, ... , n do

src/Numerics/LinearAlgebra/Complex32/SparseMatrix.cs

@@ -70,6 +70,17 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32
             _storage = storage;
         }
 
+        /// <summary>
+        /// Create a new square sparse matrix with the given number of rows and columns.
+        /// All cells of the matrix will be initialized to zero.
+        /// Zero-length matrices are not supported.
+        /// </summary>
+        /// <exception cref="ArgumentException">If the order is less than one.</exception>
+        public SparseMatrix(int order)
+            : this(order, order)
+        {
+        }
+
         /// <summary>
         /// Create a new sparse matrix with the given number of rows and columns.
         /// All cells of the matrix will be initialized to zero.
@@ -82,14 +93,70 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32
         }
 
         /// <summary>
-        /// Create a new square sparse matrix with the given number of rows and columns.
+        /// Create a new sparse matrix as a copy of the given other matrix.
-        /// All cells of the matrix will be initialized to zero.
+        /// This new matrix will be independent from the other matrix.
-        /// Zero-length matrices are not supported.
+        /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        /// <exception cref="ArgumentException">If the order is less than one.</exception>
+        public static SparseMatrix OfMatrix(Matrix<Complex32> matrix)
-        public SparseMatrix(int order)
+        {
-            : this(order, order)
+            var storage = new SparseCompressedRowMatrixStorage<Complex32>(matrix.RowCount, matrix.ColumnCount);
+            matrix.Storage.CopyToUnchecked(storage, skipClearing: true);
+            return new SparseMatrix(storage);
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given two-dimensional array.
+        /// This new matrix will be independent from the provided array.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfArray(Complex32[,] array)
+        {
+            var storage = new SparseCompressedRowMatrixStorage<Complex32>(array.GetLength(0), array.GetLength(1));
+            for (var i = 0; i < storage.RowCount; i++)
+            {
+                for (var j = 0; j < storage.ColumnCount; j++)
+                {
+                    storage.At(i, j, array[i, j]);
+                }
+            }
+            return new SparseMatrix(storage);
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given enumerable.
+        /// The enumerable is assumed to be in row-major order (row by row).
+        /// This new matrix will be independent from the enumerable.
+        /// A new memory block will be allocated for storing the vector.
+        /// </summary>
+        /// <seealso href="http://en.wikipedia.org/wiki/Row-major_order"/>
+        public static SparseMatrix OfRowMajor(int rows, int columns, IEnumerable<Complex32> rowMajor)
         {
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<Complex32>.OfRowMajorEnumerable(rows, columns, rowMajor));
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix with the given number of rows and columns as a copy of the given array.
+        /// The array is assumed to be in column-major order (column by column).
+        /// This new matrix will be independent from the provided array.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        /// <seealso href="http://en.wikipedia.org/wiki/Row-major_order"/>
+        public static SparseMatrix OfColumnMajor(int rows, int columns, Complex32[] array)
+        {
+            if (rows * columns > array.Length)
+            {
+                throw new ArgumentOutOfRangeException(Resources.ArgumentMatrixDimensions);
+            }
+
+            var storage = new SparseCompressedRowMatrixStorage<Complex32>(rows, columns);
+            for (var i = 0; i < rows; i++)
+            {
+                for (var j = 0; j < columns; j++)
+                {
+                    storage.At(i, j, array[i + (j * rows)]);
+                }
+            }
+            return new SparseMatrix(storage);
         }
 
         /// <summary>
@@ -137,7 +204,8 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32
         /// This new matrix will be independent from the provided array.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        /// <seealso cref="http://en.wikipedia.org/wiki/Row-major_order"/>
+        /// <seealso href="http://en.wikipedia.org/wiki/Row-major_order"/>
+        [Obsolete("Use SparseMatrix.OfColumnMajor instead. Scheduled for removal in v3.0.")]
         public SparseMatrix(int rows, int columns, Complex32[] array)
             : this(rows, columns)
         {
@@ -160,6 +228,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32
         /// This new matrix will be independent from the provided array.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
+        [Obsolete("Use SparseMatrix.OfArray instead. Scheduled for removal in v3.0.")]
         public SparseMatrix(Complex32[,] array)
             : this(array.GetLength(0), array.GetLength(1))
         {
@@ -172,22 +241,12 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32
             }
         }
 
-        /// <summary>
-        /// Create a new sparse matrix as a copy of the given enumerable.
-        /// The enumerable is assumed to be in row-major order (row by row).
-        /// This new matrix will be independent from the enumerable.
-        /// A new memory block will be allocated for storing the vector.
-        /// </summary>
-        public SparseMatrix(int rows, int columns, IEnumerable<Complex32> rowMajor)
-            : this(SparseCompressedRowMatrixStorage<Complex32>.FromRowMajorEnumerable(rows, columns, rowMajor))
-        {
-        }
-
         /// <summary>
         /// Create a new sparse matrix as a copy of the given other matrix.
         /// This new matrix will be independent from the other matrix.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
+        [Obsolete("Use SparseMatrix.OfMatrix instead. Scheduled for removal in v3.0.")]
         public SparseMatrix(Matrix<Complex32> matrix)
             : this(matrix.RowCount, matrix.ColumnCount)
         {

src/Numerics/LinearAlgebra/Complex32/SparseVector.cs

@@ -124,7 +124,7 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32
         /// A new memory block will be allocated for storing the vector.
         /// </summary>
         public SparseVector(IEnumerable<Complex32> other)
-            : this(SparseVectorStorage<Complex32>.FromEnumerable(other))
+            : this(SparseVectorStorage<Complex32>.OfEnumerable(other))
         {
         }
 

src/Numerics/LinearAlgebra/Double/DenseMatrix.cs

@@ -103,12 +103,65 @@ namespace MathNet.Numerics.LinearAlgebra.Double
         {
         }
 
+        /// <summary>
+        /// Create a new dense matrix with the given number of rows and columns directly binding to a raw array.
+        /// The array is assumed to be in column-major order (column by column) and is used directly without copying.
+        /// Very efficient, but changes to the array and the matrix will affect each other.
+        /// </summary>
+        /// <seealso href="http://en.wikipedia.org/wiki/Row-major_order"/>
+        public DenseMatrix(int rows, int columns, double[] storage)
+            : this(new DenseColumnMajorMatrixStorage<double>(rows, columns, storage))
+        {
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given other matrix.
+        /// This new matrix will be independent from the other matrix.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static DenseMatrix OfMatrix(Matrix<double> matrix)
+        {
+            var storage = new DenseColumnMajorMatrixStorage<double>(matrix.RowCount, matrix.ColumnCount);
+            matrix.Storage.CopyToUnchecked(storage, skipClearing: true);
+            return new DenseMatrix(storage);
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given two-dimensional array.
+        /// This new matrix will be independent from the provided array.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static DenseMatrix OfArray(double[,] array)
+        {
+            var storage = new DenseColumnMajorMatrixStorage<double>(array.GetLength(0), array.GetLength(1));
+            for (var i = 0; i < storage.RowCount; i++)
+            {
+                for (var j = 0; j < storage.ColumnCount; j++)
+                {
+                    storage.Data[(j * storage.RowCount) + i] = array[i, j];
+                }
+            }
+            return new DenseMatrix(storage);
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given enumerable.
+        /// The enumerable is assumed to be in column-major order (column by column).
+        /// This new matrix will be independent from the enumerable.
+        /// A new memory block will be allocated for storing the vector.
+        /// </summary>
+        public static DenseMatrix OfColumnMajor(int rows, int columns, IEnumerable<double> columnMajor)
+        {
+            return new DenseMatrix(DenseColumnMajorMatrixStorage<double>.OfColumnMajorEnumerable(rows, columns, columnMajor));
+        }
+
         /// <summary>
         /// Create a new dense matrix with the given number of rows and columns.
         /// All cells of the matrix will be initialized to the provided value.
         /// Zero-length matrices are not supported.
         /// </summary>
         /// <exception cref="ArgumentException">If the row or column count is less than one.</exception>
+        [Obsolete("Scheduled for removal in v3.0.")]
         public DenseMatrix(int rows, int columns, double value)
             : this(rows, columns)
         {
@@ -118,22 +171,12 @@ namespace MathNet.Numerics.LinearAlgebra.Double
             }
         }
 
-        /// <summary>
-        /// Create a new dense matrix with the given number of rows and columns directly binding to a raw array.
-        /// The array is assumed to be in column-major order (column by column) and is used directly without copying.
-        /// Very efficient, but changes to the array and the matrix will affect each other.
-        /// </summary>
-        /// <seealso cref="http://en.wikipedia.org/wiki/Row-major_order"/>
-        public DenseMatrix(int rows, int columns, double[] storage)
-            : this(new DenseColumnMajorMatrixStorage<double>(rows, columns, storage))
-        {
-        }
-
         /// <summary>
         /// Create a new dense matrix as a copy of the given two-dimensional array.
         /// This new matrix will be independent from the provided array.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
+        [Obsolete("Use DenseMatrix.OfArray instead. Scheduled for removal in v3.0.")]
         public DenseMatrix(double[,] array)
             : this(array.GetLength(0), array.GetLength(1))
         {
@@ -145,23 +188,13 @@ namespace MathNet.Numerics.LinearAlgebra.Double
                 }
             }
         }
-        
-        /// <summary>
-        /// Create a new dense matrix as a copy of the given enumerable.
-        /// The enumerable is assumed to be in column-major order (column by column).
-        /// This new matrix will be independent from the enumerable.
-        /// A new memory block will be allocated for storing the vector.
-        /// </summary>
-        public DenseMatrix(int rows, int columns, IEnumerable<double> columnMajor)
-            : this(DenseColumnMajorMatrixStorage<double>.FromColumnMajorEnumerable(rows, columns, columnMajor))
-        {
-        }
 
         /// <summary>
         /// Create a new dense matrix as a copy of the given other matrix.
         /// This new matrix will be independent from the other matrix.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
+        [Obsolete("Use DenseMatrix.OfMatrix instead. Scheduled for removal in v3.0.")]
         public DenseMatrix(Matrix<double> matrix)
             : this(matrix.RowCount, matrix.ColumnCount)
         {

src/Numerics/LinearAlgebra/Double/DenseVector.cs

@@ -114,7 +114,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double
         /// A new memory block will be allocated for storing the vector.
         /// </summary>
         public DenseVector(IEnumerable<double> other)
-            : this(DenseVectorStorage<double>.FromEnumerable(other))
+            : this(DenseVectorStorage<double>.OfEnumerable(other))
         {
         }
 

src/Numerics/LinearAlgebra/Double/Solvers/Preconditioners/Ilutp.cs

@@ -313,7 +313,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Solvers.Preconditioners
                 throw new ArgumentException(Resources.ArgumentMatrixSquare, "matrix");
             }
 
-            var sparseMatrix = (matrix is SparseMatrix) ? matrix as SparseMatrix : new SparseMatrix(matrix);
+            var sparseMatrix = (matrix is SparseMatrix) ? matrix as SparseMatrix : SparseMatrix.OfMatrix(matrix);
 
             // The creation of the preconditioner follows the following algorithm.
             // spaceLeft = lfilNnz * nnz(A)

src/Numerics/LinearAlgebra/Double/Solvers/Preconditioners/IncompleteLU.cs

@@ -111,7 +111,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double.Solvers.Preconditioners
                 throw new ArgumentException(Resources.ArgumentMatrixSquare, "matrix");
             }
 
-            _decompositionLU = new SparseMatrix(matrix);
+            _decompositionLU = SparseMatrix.OfMatrix(matrix);
 
             // M == A
             // for i = 2, ... , n do

src/Numerics/LinearAlgebra/Double/SparseMatrix.cs

@@ -69,6 +69,17 @@ namespace MathNet.Numerics.LinearAlgebra.Double
             _storage = storage;
         }
 
+        /// <summary>
+        /// Create a new square sparse matrix with the given number of rows and columns.
+        /// All cells of the matrix will be initialized to zero.
+        /// Zero-length matrices are not supported.
+        /// </summary>
+        /// <exception cref="ArgumentException">If the order is less than one.</exception>
+        public SparseMatrix(int order)
+            : this(order, order)
+        {
+        }
+
         /// <summary>
         /// Create a new sparse matrix with the given number of rows and columns.
         /// All cells of the matrix will be initialized to zero.
@@ -81,14 +92,70 @@ namespace MathNet.Numerics.LinearAlgebra.Double
         }
 
         /// <summary>
-        /// Create a new square sparse matrix with the given number of rows and columns.
+        /// Create a new sparse matrix as a copy of the given other matrix.
-        /// All cells of the matrix will be initialized to zero.
+        /// This new matrix will be independent from the other matrix.
-        /// Zero-length matrices are not supported.
+        /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        /// <exception cref="ArgumentException">If the order is less than one.</exception>
+        public static SparseMatrix OfMatrix(Matrix<double> matrix)
-        public SparseMatrix(int order)
+        {
-            : this(order, order)
+            var storage = new SparseCompressedRowMatrixStorage<double>(matrix.RowCount, matrix.ColumnCount);
+            matrix.Storage.CopyToUnchecked(storage, skipClearing: true);
+            return new SparseMatrix(storage);
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given two-dimensional array.
+        /// This new matrix will be independent from the provided array.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfArray(double[,] array)
+        {
+            var storage = new SparseCompressedRowMatrixStorage<double>(array.GetLength(0), array.GetLength(1));
+            for (var i = 0; i < storage.RowCount; i++)
+            {
+                for (var j = 0; j < storage.ColumnCount; j++)
+                {
+                    storage.At(i, j, array[i, j]);
+                }
+            }
+            return new SparseMatrix(storage);
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given enumerable.
+        /// The enumerable is assumed to be in row-major order (row by row).
+        /// This new matrix will be independent from the enumerable.
+        /// A new memory block will be allocated for storing the vector.
+        /// </summary>
+        /// <seealso href="http://en.wikipedia.org/wiki/Row-major_order"/>
+        public static SparseMatrix OfRowMajor(int rows, int columns, IEnumerable<double> rowMajor)
         {
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<double>.OfRowMajorEnumerable(rows, columns, rowMajor));
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix with the given number of rows and columns as a copy of the given array.
+        /// The array is assumed to be in column-major order (column by column).
+        /// This new matrix will be independent from the provided array.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        /// <seealso href="http://en.wikipedia.org/wiki/Row-major_order"/>
+        public static SparseMatrix OfColumnMajor(int rows, int columns, double[] array)
+        {
+            if (rows * columns > array.Length)
+            {
+                throw new ArgumentOutOfRangeException(Resources.ArgumentMatrixDimensions);
+            }
+
+            var storage = new SparseCompressedRowMatrixStorage<double>(rows, columns);
+            for (var i = 0; i < rows; i++)
+            {
+                for (var j = 0; j < columns; j++)
+                {
+                    storage.At(i, j, array[i + (j * rows)]);
+                }
+            }
+            return new SparseMatrix(storage);
         }
 
         /// <summary>
@@ -136,7 +203,8 @@ namespace MathNet.Numerics.LinearAlgebra.Double
         /// This new matrix will be independent from the provided array.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        /// <seealso cref="http://en.wikipedia.org/wiki/Row-major_order"/>
+        /// <seealso href="http://en.wikipedia.org/wiki/Row-major_order"/>
+        [Obsolete("Use SparseMatrix.OfColumnMajor instead. Scheduled for removal in v3.0.")]
         public SparseMatrix(int rows, int columns, double[] array)
             : this(rows, columns)
         {
@@ -159,6 +227,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double
         /// This new matrix will be independent from the provided array.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
+        [Obsolete("Use SparseMatrix.OfArray instead. Scheduled for removal in v3.0.")]
         public SparseMatrix(double[,] array)
             : this(array.GetLength(0), array.GetLength(1))
         {
@@ -171,22 +240,12 @@ namespace MathNet.Numerics.LinearAlgebra.Double
             }
         }
 
-        /// <summary>
-        /// Create a new sparse matrix as a copy of the given enumerable.
-        /// The enumerable is assumed to be in row-major order (row by row).
-        /// This new matrix will be independent from the enumerable.
-        /// A new memory block will be allocated for storing the vector.
-        /// </summary>
-        public SparseMatrix(int rows, int columns, IEnumerable<double> rowMajor)
-            : this(SparseCompressedRowMatrixStorage<double>.FromRowMajorEnumerable(rows, columns, rowMajor))
-        {
-        }
-
         /// <summary>
         /// Create a new sparse matrix as a copy of the given other matrix.
         /// This new matrix will be independent from the other matrix.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
+        [Obsolete("Use SparseMatrix.OfMatrix instead. Scheduled for removal in v3.0.")]
         public SparseMatrix(Matrix<double> matrix)
             : this(matrix.RowCount, matrix.ColumnCount)
         {

src/Numerics/LinearAlgebra/Double/SparseVector.cs

@@ -124,7 +124,7 @@ namespace MathNet.Numerics.LinearAlgebra.Double
         /// A new memory block will be allocated for storing the vector.
         /// </summary>
         public SparseVector(IEnumerable<double> other)
-            : this(SparseVectorStorage<double>.FromEnumerable(other))
+            : this(SparseVectorStorage<double>.OfEnumerable(other))
         {
         }
 

src/Numerics/LinearAlgebra/Single/DenseMatrix.cs

@@ -103,12 +103,65 @@ namespace MathNet.Numerics.LinearAlgebra.Single
         {
         }
 
+        /// <summary>
+        /// Create a new dense matrix with the given number of rows and columns directly binding to a raw array.
+        /// The array is assumed to be in column-major order (column by column) and is used directly without copying.
+        /// Very efficient, but changes to the array and the matrix will affect each other.
+        /// </summary>
+        /// <seealso href="http://en.wikipedia.org/wiki/Row-major_order"/>
+        public DenseMatrix(int rows, int columns, float[] storage)
+            : this(new DenseColumnMajorMatrixStorage<float>(rows, columns, storage))
+        {
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given other matrix.
+        /// This new matrix will be independent from the other matrix.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static DenseMatrix OfMatrix(Matrix<float> matrix)
+        {
+            var storage = new DenseColumnMajorMatrixStorage<float>(matrix.RowCount, matrix.ColumnCount);
+            matrix.Storage.CopyToUnchecked(storage, skipClearing: true);
+            return new DenseMatrix(storage);
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given two-dimensional array.
+        /// This new matrix will be independent from the provided array.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static DenseMatrix OfArray(float[,] array)
+        {
+            var storage = new DenseColumnMajorMatrixStorage<float>(array.GetLength(0), array.GetLength(1));
+            for (var i = 0; i < storage.RowCount; i++)
+            {
+                for (var j = 0; j < storage.ColumnCount; j++)
+                {
+                    storage.Data[(j * storage.RowCount) + i] = array[i, j];
+                }
+            }
+            return new DenseMatrix(storage);
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given enumerable.
+        /// The enumerable is assumed to be in column-major order (column by column).
+        /// This new matrix will be independent from the enumerable.
+        /// A new memory block will be allocated for storing the vector.
+        /// </summary>
+        public static DenseMatrix OfColumnMajor(int rows, int columns, IEnumerable<float> columnMajor)
+        {
+            return new DenseMatrix(DenseColumnMajorMatrixStorage<float>.OfColumnMajorEnumerable(rows, columns, columnMajor));
+        }
+
         /// <summary>
         /// Create a new dense matrix with the given number of rows and columns.
         /// All cells of the matrix will be initialized to the provided value.
         /// Zero-length matrices are not supported.
         /// </summary>
         /// <exception cref="ArgumentException">If the row or column count is less than one.</exception>
+        [Obsolete("Scheduled for removal in v3.0.")]
         public DenseMatrix(int rows, int columns, float value)
             : this(rows, columns)
         {
@@ -118,22 +171,12 @@ namespace MathNet.Numerics.LinearAlgebra.Single
             }
         }
 
-        /// <summary>
-        /// Create a new dense matrix with the given number of rows and columns directly binding to a raw array.
-        /// The array is assumed to be in column-major order (column by column) and is used directly without copying.
-        /// Very efficient, but changes to the array and the matrix will affect each other.
-        /// </summary>
-        /// <seealso cref="http://en.wikipedia.org/wiki/Row-major_order"/>
-        public DenseMatrix(int rows, int columns, float[] storage)
-            : this(new DenseColumnMajorMatrixStorage<float>(rows, columns, storage))
-        {
-        }
-
         /// <summary>
         /// Create a new dense matrix as a copy of the given two-dimensional array.
         /// This new matrix will be independent from the provided array.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
+        [Obsolete("Use DenseMatrix.OfArray instead. Scheduled for removal in v3.0.")]
         public DenseMatrix(float[,] array)
             : this(array.GetLength(0), array.GetLength(1))
         {
@@ -146,22 +189,12 @@ namespace MathNet.Numerics.LinearAlgebra.Single
             }
         }
 
-        /// <summary>
-        /// Create a new dense matrix as a copy of the given enumerable.
-        /// The enumerable is assumed to be in column-major order (column by column).
-        /// This new matrix will be independent from the enumerable.
-        /// A new memory block will be allocated for storing the vector.
-        /// </summary>
-        public DenseMatrix(int rows, int columns, IEnumerable<float> columnMajor)
-            : this(DenseColumnMajorMatrixStorage<float>.FromColumnMajorEnumerable(rows, columns, columnMajor))
-        {
-        }
-
         /// <summary>
         /// Create a new dense matrix as a copy of the given other matrix.
         /// This new matrix will be independent from the other matrix.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
+        [Obsolete("Use DenseMatrix.OfMatrix instead. Scheduled for removal in v3.0.")]
         public DenseMatrix(Matrix<float> matrix)
             : this(matrix.RowCount, matrix.ColumnCount)
         {

src/Numerics/LinearAlgebra/Single/DenseVector.cs

@@ -113,7 +113,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single
         /// A new memory block will be allocated for storing the vector.
         /// </summary>
         public DenseVector(IEnumerable<float> other)
-            : this(DenseVectorStorage<float>.FromEnumerable(other))
+            : this(DenseVectorStorage<float>.OfEnumerable(other))
         {
         }
 

src/Numerics/LinearAlgebra/Single/Solvers/Preconditioners/Ilutp.cs

@@ -313,7 +313,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Solvers.Preconditioners
                 throw new ArgumentException(Resources.ArgumentMatrixSquare, "matrix");
             }
 
-            var sparseMatrix = (matrix is SparseMatrix) ? matrix as SparseMatrix : new SparseMatrix(matrix);
+            var sparseMatrix = (matrix is SparseMatrix) ? matrix as SparseMatrix : SparseMatrix.OfMatrix(matrix);
 
             // The creation of the preconditioner follows the following algorithm.
             // spaceLeft = lfilNnz * nnz(A)

src/Numerics/LinearAlgebra/Single/Solvers/Preconditioners/IncompleteLU.cs

@@ -111,7 +111,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single.Solvers.Preconditioners
                 throw new ArgumentException(Resources.ArgumentMatrixSquare, "matrix");
             }
 
-            _decompositionLU = new SparseMatrix(matrix);
+            _decompositionLU = SparseMatrix.OfMatrix(matrix);
 
             // M == A
             // for i = 2, ... , n do

src/Numerics/LinearAlgebra/Single/SparseMatrix.cs

@@ -68,6 +68,17 @@ namespace MathNet.Numerics.LinearAlgebra.Single
         {
             _storage = storage;
         }
+        
+        /// <summary>
+        /// Create a new square sparse matrix with the given number of rows and columns.
+        /// All cells of the matrix will be initialized to zero.
+        /// Zero-length matrices are not supported.
+        /// </summary>
+        /// <exception cref="ArgumentException">If the order is less than one.</exception>
+        public SparseMatrix(int order)
+            : this(order, order)
+        {
+        }
 
         /// <summary>
         /// Create a new sparse matrix with the given number of rows and columns.
@@ -81,14 +92,70 @@ namespace MathNet.Numerics.LinearAlgebra.Single
         }
 
         /// <summary>
-        /// Create a new square sparse matrix with the given number of rows and columns.
+        /// Create a new sparse matrix as a copy of the given other matrix.
-        /// All cells of the matrix will be initialized to zero.
+        /// This new matrix will be independent from the other matrix.
-        /// Zero-length matrices are not supported.
+        /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        /// <exception cref="ArgumentException">If the order is less than one.</exception>
+        public static SparseMatrix OfMatrix(Matrix<float> matrix)
-        public SparseMatrix(int order)
-            : this(order, order)
         {
+            var storage = new SparseCompressedRowMatrixStorage<float>(matrix.RowCount, matrix.ColumnCount);
+            matrix.Storage.CopyToUnchecked(storage, skipClearing: true);
+            return new SparseMatrix(storage);
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given two-dimensional array.
+        /// This new matrix will be independent from the provided array.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfArray(float[,] array)
+        {
+            var storage = new SparseCompressedRowMatrixStorage<float>(array.GetLength(0), array.GetLength(1));
+            for (var i = 0; i < storage.RowCount; i++)
+            {
+                for (var j = 0; j < storage.ColumnCount; j++)
+                {
+                    storage.At(i, j, array[i, j]);
+                }
+            }
+            return new SparseMatrix(storage);
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given enumerable.
+        /// The enumerable is assumed to be in row-major order (row by row).
+        /// This new matrix will be independent from the enumerable.
+        /// A new memory block will be allocated for storing the vector.
+        /// </summary>
+        /// <seealso href="http://en.wikipedia.org/wiki/Row-major_order"/>
+        public static SparseMatrix OfRowMajor(int rows, int columns, IEnumerable<float> rowMajor)
+        {
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<float>.OfRowMajorEnumerable(rows, columns, rowMajor));
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix with the given number of rows and columns as a copy of the given array.
+        /// The array is assumed to be in column-major order (column by column).
+        /// This new matrix will be independent from the provided array.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        /// <seealso href="http://en.wikipedia.org/wiki/Row-major_order"/>
+        public static SparseMatrix OfColumnMajor(int rows, int columns, float[] array)
+        {
+            if (rows * columns > array.Length)
+            {
+                throw new ArgumentOutOfRangeException(Resources.ArgumentMatrixDimensions);
+            }
+
+            var storage = new SparseCompressedRowMatrixStorage<float>(rows, columns);
+            for (var i = 0; i < rows; i++)
+            {
+                for (var j = 0; j < columns; j++)
+                {
+                    storage.At(i, j, array[i + (j * rows)]);
+                }
+            }
+            return new SparseMatrix(storage);
         }
 
         /// <summary>
@@ -136,7 +203,8 @@ namespace MathNet.Numerics.LinearAlgebra.Single
         /// This new matrix will be independent from the provided array.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        /// <seealso cref="http://en.wikipedia.org/wiki/Row-major_order"/>
+        /// <seealso href="http://en.wikipedia.org/wiki/Row-major_order"/>
+        [Obsolete("Use SparseMatrix.OfColumnMajor instead. Scheduled for removal in v3.0.")]
         public SparseMatrix(int rows, int columns, float[] array)
             : this(rows, columns)
         {
@@ -159,6 +227,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single
         /// This new matrix will be independent from the provided array.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
+        [Obsolete("Use SparseMatrix.OfArray instead. Scheduled for removal in v3.0.")]
         public SparseMatrix(float[,] array)
             : this(array.GetLength(0), array.GetLength(1))
         {
@@ -171,22 +240,12 @@ namespace MathNet.Numerics.LinearAlgebra.Single
             }
         }
 
-        /// <summary>
-        /// Create a new sparse matrix as a copy of the given enumerable.
-        /// The enumerable is assumed to be in row-major order (row by row).
-        /// This new matrix will be independent from the enumerable.
-        /// A new memory block will be allocated for storing the vector.
-        /// </summary>
-        public SparseMatrix(int rows, int columns, IEnumerable<float> rowMajor)
-            : this(SparseCompressedRowMatrixStorage<float>.FromRowMajorEnumerable(rows, columns, rowMajor))
-        {
-        }
-
         /// <summary>
         /// Create a new sparse matrix as a copy of the given other matrix.
         /// This new matrix will be independent from the other matrix.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
+        [Obsolete("Use SparseMatrix.OfMatrix instead. Scheduled for removal in v3.0.")]
         public SparseMatrix(Matrix<float> matrix)
             : this(matrix.RowCount, matrix.ColumnCount)
         {

src/Numerics/LinearAlgebra/Single/SparseVector.cs

@@ -124,7 +124,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single
         /// A new memory block will be allocated for storing the vector.
         /// </summary>
         public SparseVector(IEnumerable<float> other)
-            : this(SparseVectorStorage<float>.FromEnumerable(other))
+            : this(SparseVectorStorage<float>.OfEnumerable(other))
         {
         }
 

src/Numerics/LinearAlgebra/Storage/DenseColumnMajorMatrixStorage.cs

@@ -101,7 +101,7 @@ namespace MathNet.Numerics.LinearAlgebra.Storage
 
         // INITIALIZATION
 
-        public static DenseColumnMajorMatrixStorage<T> FromColumnMajorEnumerable(int rows, int columns, IEnumerable<T> data)
+        public static DenseColumnMajorMatrixStorage<T> OfColumnMajorEnumerable(int rows, int columns, IEnumerable<T> data)
         {
             if (data == null)
             {

src/Numerics/LinearAlgebra/Storage/DenseVectorStorage.cs

@@ -92,7 +92,7 @@ namespace MathNet.Numerics.LinearAlgebra.Storage
 
         // INITIALIZATION
 
-        public static DenseVectorStorage<T> FromEnumerable(IEnumerable<T> data)
+        public static DenseVectorStorage<T> OfEnumerable(IEnumerable<T> data)
         {
             if (data == null)
             {

src/Numerics/LinearAlgebra/Storage/SparseCompressedRowMatrixStorage.cs

@@ -363,7 +363,7 @@ namespace MathNet.Numerics.LinearAlgebra.Storage
 
         // INITIALIZATION
 
-        public static SparseCompressedRowMatrixStorage<T> FromRowMajorEnumerable(int rows, int columns, IEnumerable<T> data)
+        public static SparseCompressedRowMatrixStorage<T> OfRowMajorEnumerable(int rows, int columns, IEnumerable<T> data)
         {
             if (data == null)
             {

src/Numerics/LinearAlgebra/Storage/SparseVectorStorage.cs

@@ -284,7 +284,7 @@ namespace MathNet.Numerics.LinearAlgebra.Storage
 
         // INITIALIZATION
 
-        public static SparseVectorStorage<T> FromEnumerable(IEnumerable<T> data)
+        public static SparseVectorStorage<T> OfEnumerable(IEnumerable<T> data)
         {
             if (data == null)
             {

src/UnitTests/LinearAlgebraProviderTests/Complex/LinearAlgebraProviderTests.cs

@@ -63,12 +63,12 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraProviderTests.Complex
         /// </summary>
         readonly IDictionary<string, DenseMatrix> _matrices = new Dictionary<string, DenseMatrix>
             {
-                {"Singular3x3", new DenseMatrix(new[,] {{new Complex(1.0, 0), 1.0, 2.0}, {1.0, 1.0, 2.0}, {1.0, 1.0, 2.0}})},
+                {"Singular3x3", DenseMatrix.OfArray(new[,] {{new Complex(1.0, 0), 1.0, 2.0}, {1.0, 1.0, 2.0}, {1.0, 1.0, 2.0}})},
-                {"Square3x3", new DenseMatrix(new[,] {{new Complex(-1.1, 0), -2.2, -3.3}, {0.0, 1.1, 2.2}, {-4.4, 5.5, 6.6}})},
+                {"Square3x3", DenseMatrix.OfArray(new[,] {{new Complex(-1.1, 0), -2.2, -3.3}, {0.0, 1.1, 2.2}, {-4.4, 5.5, 6.6}})},
-                {"Square4x4", new DenseMatrix(new[,] {{new Complex(-1.1, 0), -2.2, -3.3, -4.4}, {0.0, 1.1, 2.2, 3.3}, {1.0, 2.1, 6.2, 4.3}, {-4.4, 5.5, 6.6, -7.7}})},
+                {"Square4x4", DenseMatrix.OfArray(new[,] {{new Complex(-1.1, 0), -2.2, -3.3, -4.4}, {0.0, 1.1, 2.2, 3.3}, {1.0, 2.1, 6.2, 4.3}, {-4.4, 5.5, 6.6, -7.7}})},
-                {"Singular4x4", new DenseMatrix(new[,] {{new Complex(-1.1, 0), -2.2, -3.3, -4.4}, {-1.1, -2.2, -3.3, -4.4}, {-1.1, -2.2, -3.3, -4.4}, {-1.1, -2.2, -3.3, -4.4}})},
+                {"Singular4x4", DenseMatrix.OfArray(new[,] {{new Complex(-1.1, 0), -2.2, -3.3, -4.4}, {-1.1, -2.2, -3.3, -4.4}, {-1.1, -2.2, -3.3, -4.4}, {-1.1, -2.2, -3.3, -4.4}})},
-                {"Tall3x2", new DenseMatrix(new[,] {{new Complex(-1.1, 0), -2.2}, {0.0, 1.1}, {-4.4, 5.5}})},
+                {"Tall3x2", DenseMatrix.OfArray(new[,] {{new Complex(-1.1, 0), -2.2}, {0.0, 1.1}, {-4.4, 5.5}})},
-                {"Wide2x3", new DenseMatrix(new[,] {{new Complex(-1.1, 0), -2.2, -3.3}, {0.0, 1.1, 2.2}})},
+                {"Wide2x3", DenseMatrix.OfArray(new[,] {{new Complex(-1.1, 0), -2.2, -3.3}, {0.0, 1.1, 2.2}})},
                 {"Tall50000x10", DenseMatrix.CreateRandom(50000, 10, Dist)},
                 {"Wide10x50000", DenseMatrix.CreateRandom(10, 50000, Dist)},
                 {"Square1000x1000", DenseMatrix.CreateRandom(1000, 1000, Dist)}

src/UnitTests/LinearAlgebraProviderTests/Complex32/LinearAlgebraProviderTests.cs

@@ -63,12 +63,12 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraProviderTests.Complex32
         /// </summary>
         readonly IDictionary<string, DenseMatrix> _matrices = new Dictionary<string, DenseMatrix>
             {
-                {"Singular3x3", new DenseMatrix(new[,] {{new Complex32(1.0f, 0.0f), 1.0f, 2.0f}, {1.0f, 1.0f, 2.0f}, {1.0f, 1.0f, 2.0f}})},
+                {"Singular3x3", DenseMatrix.OfArray(new[,] {{new Complex32(1.0f, 0.0f), 1.0f, 2.0f}, {1.0f, 1.0f, 2.0f}, {1.0f, 1.0f, 2.0f}})},
-                {"Square3x3", new DenseMatrix(new[,] {{new Complex32(-1.1f, 0.0f), -2.2f, -3.3f}, {0.0f, 1.1f, 2.2f}, {-4.4f, 5.5f, 6.6f}})},
+                {"Square3x3", DenseMatrix.OfArray(new[,] {{new Complex32(-1.1f, 0.0f), -2.2f, -3.3f}, {0.0f, 1.1f, 2.2f}, {-4.4f, 5.5f, 6.6f}})},
-                {"Square4x4", new DenseMatrix(new[,] {{new Complex32(-1.1f, 0.0f), -2.2f, -3.3f, -4.4f}, {0.0f, 1.1f, 2.2f, 3.3f}, {1.0f, 2.1f, 6.2f, 4.3f}, {-4.4f, 5.5f, 6.6f, -7.7f}})},
+                {"Square4x4", DenseMatrix.OfArray(new[,] {{new Complex32(-1.1f, 0.0f), -2.2f, -3.3f, -4.4f}, {0.0f, 1.1f, 2.2f, 3.3f}, {1.0f, 2.1f, 6.2f, 4.3f}, {-4.4f, 5.5f, 6.6f, -7.7f}})},
-                {"Singular4x4", new DenseMatrix(new[,] {{new Complex32(-1.1f, 0.0f), -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}})},
+                {"Singular4x4", DenseMatrix.OfArray(new[,] {{new Complex32(-1.1f, 0.0f), -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}})},
-                {"Tall3x2", new DenseMatrix(new[,] {{new Complex32(-1.1f, 0.0f), -2.2f}, {0.0f, 1.1f}, {-4.4f, 5.5f}})},
+                {"Tall3x2", DenseMatrix.OfArray(new[,] {{new Complex32(-1.1f, 0.0f), -2.2f}, {0.0f, 1.1f}, {-4.4f, 5.5f}})},
-                {"Wide2x3", new DenseMatrix(new[,] {{new Complex32(-1.1f, 0.0f), -2.2f, -3.3f}, {0.0f, 1.1f, 2.2f}})},
+                {"Wide2x3", DenseMatrix.OfArray(new[,] {{new Complex32(-1.1f, 0.0f), -2.2f, -3.3f}, {0.0f, 1.1f, 2.2f}})},
                 {"Tall50000x10", DenseMatrix.CreateRandom(50000, 10, Dist)},
                 {"Wide10x50000", DenseMatrix.CreateRandom(10, 50000, Dist)},
                 {"Square1000x1000", DenseMatrix.CreateRandom(1000, 1000, Dist)}

src/UnitTests/LinearAlgebraProviderTests/Double/LinearAlgebraProviderTests.cs

@@ -62,12 +62,12 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraProviderTests.Double
         /// </summary>
         readonly IDictionary<string, DenseMatrix> _matrices = new Dictionary<string, DenseMatrix>
             {
-                {"Singular3x3", new DenseMatrix(new[,] {{1.0, 1.0, 2.0}, {1.0, 1.0, 2.0}, {1.0, 1.0, 2.0}})},
+                {"Singular3x3", DenseMatrix.OfArray(new[,] {{1.0, 1.0, 2.0}, {1.0, 1.0, 2.0}, {1.0, 1.0, 2.0}})},
-                {"Square3x3", new DenseMatrix(new[,] {{-1.1, -2.2, -3.3}, {0.0, 1.1, 2.2}, {-4.4, 5.5, 6.6}})},
+                {"Square3x3", DenseMatrix.OfArray(new[,] {{-1.1, -2.2, -3.3}, {0.0, 1.1, 2.2}, {-4.4, 5.5, 6.6}})},
-                {"Square4x4", new DenseMatrix(new[,] {{-1.1, -2.2, -3.3, -4.4}, {0.0, 1.1, 2.2, 3.3}, {1.0, 2.1, 6.2, 4.3}, {-4.4, 5.5, 6.6, -7.7}})},
+                {"Square4x4", DenseMatrix.OfArray(new[,] {{-1.1, -2.2, -3.3, -4.4}, {0.0, 1.1, 2.2, 3.3}, {1.0, 2.1, 6.2, 4.3}, {-4.4, 5.5, 6.6, -7.7}})},
-                {"Singular4x4", new DenseMatrix(new[,] {{-1.1, -2.2, -3.3, -4.4}, {-1.1, -2.2, -3.3, -4.4}, {-1.1, -2.2, -3.3, -4.4}, {-1.1, -2.2, -3.3, -4.4}})},
+                {"Singular4x4", DenseMatrix.OfArray(new[,] {{-1.1, -2.2, -3.3, -4.4}, {-1.1, -2.2, -3.3, -4.4}, {-1.1, -2.2, -3.3, -4.4}, {-1.1, -2.2, -3.3, -4.4}})},
-                {"Tall3x2", new DenseMatrix(new[,] {{-1.1, -2.2}, {0.0, 1.1}, {-4.4, 5.5}})},
+                {"Tall3x2", DenseMatrix.OfArray(new[,] {{-1.1, -2.2}, {0.0, 1.1}, {-4.4, 5.5}})},
-                {"Wide2x3", new DenseMatrix(new[,] {{-1.1, -2.2, -3.3}, {0.0, 1.1, 2.2}})},
+                {"Wide2x3", DenseMatrix.OfArray(new[,] {{-1.1, -2.2, -3.3}, {0.0, 1.1, 2.2}})},
                 {"Tall50000x10", DenseMatrix.CreateRandom(50000, 10, Dist)},
                 {"Wide10x50000", DenseMatrix.CreateRandom(10, 50000, Dist)},
                 {"Square1000x1000", DenseMatrix.CreateRandom(1000, 1000, Dist)}

src/UnitTests/LinearAlgebraProviderTests/Single/LinearAlgebraProviderTests.cs

@@ -62,12 +62,12 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraProviderTests.Single
         /// </summary>
         readonly IDictionary<string, DenseMatrix> _matrices = new Dictionary<string, DenseMatrix>
             {
-                {"Singular3x3", new DenseMatrix(new[,] {{1.0f, 1.0f, 2.0f}, {1.0f, 1.0f, 2.0f}, {1.0f, 1.0f, 2.0f}})},
+                {"Singular3x3", DenseMatrix.OfArray(new[,] {{1.0f, 1.0f, 2.0f}, {1.0f, 1.0f, 2.0f}, {1.0f, 1.0f, 2.0f}})},
-                {"Square3x3", new DenseMatrix(new[,] {{-1.1f, -2.2f, -3.3f}, {0.0f, 1.1f, 2.2f}, {-4.4f, 5.5f, 6.6f}})},
+                {"Square3x3", DenseMatrix.OfArray(new[,] {{-1.1f, -2.2f, -3.3f}, {0.0f, 1.1f, 2.2f}, {-4.4f, 5.5f, 6.6f}})},
-                {"Square4x4", new DenseMatrix(new[,] {{-1.1f, -2.2f, -3.3f, -4.4f}, {0.0f, 1.1f, 2.2f, 3.3f}, {1.0f, 2.1f, 6.2f, 4.3f}, {-4.4f, 5.5f, 6.6f, -7.7f}})},
+                {"Square4x4", DenseMatrix.OfArray(new[,] {{-1.1f, -2.2f, -3.3f, -4.4f}, {0.0f, 1.1f, 2.2f, 3.3f}, {1.0f, 2.1f, 6.2f, 4.3f}, {-4.4f, 5.5f, 6.6f, -7.7f}})},
-                {"Singular4x4", new DenseMatrix(new[,] {{-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}})},
+                {"Singular4x4", DenseMatrix.OfArray(new[,] {{-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}})},
-                {"Tall3x2", new DenseMatrix(new[,] {{-1.1f, -2.2f}, {0.0f, 1.1f}, {-4.4f, 5.5f}})},
+                {"Tall3x2", DenseMatrix.OfArray(new[,] {{-1.1f, -2.2f}, {0.0f, 1.1f}, {-4.4f, 5.5f}})},
-                {"Wide2x3", new DenseMatrix(new[,] {{-1.1f, -2.2f, -3.3f}, {0.0f, 1.1f, 2.2f}})},
+                {"Wide2x3", DenseMatrix.OfArray(new[,] {{-1.1f, -2.2f, -3.3f}, {0.0f, 1.1f, 2.2f}})},
                 {"Tall50000x10", DenseMatrix.CreateRandom(50000, 10, Dist)},
                 {"Wide10x50000", DenseMatrix.CreateRandom(10, 50000, Dist)},
                 {"Square1000x1000", DenseMatrix.CreateRandom(1000, 1000, Dist)}

src/UnitTests/LinearAlgebraTests/Complex/DenseMatrixTests.cs

@@ -3,7 +3,9 @@
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
-// Copyright (c) 2009-2010 Math.NET
+//
+// Copyright (c) 2009-2013 Math.NET
+//
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
 // files (the "Software"), to deal in the Software without
@@ -12,8 +14,10 @@
 // copies of the Software, and to permit persons to whom the
 // Software is furnished to do so, subject to the following
 // conditions:
+//
 // The above copyright notice and this permission notice shall be
 // included in all copies or substantial portions of the Software.
+//
 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
@@ -55,7 +59,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         /// <returns>A matrix with the given values.</returns>
         protected override Matrix CreateMatrix(Complex[,] data)
         {
-            return new DenseMatrix(data);
+            return DenseMatrix.OfArray(data);
         }
 
         /// <summary>
@@ -86,13 +90,13 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         public void CanCreateMatrixFrom1DArray()
         {
             var testData = new Dictionary<string, Matrix>
-                           {
+                {
-                               { "Singular3x3", new DenseMatrix(3, 3, new[] { new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(2.0, 1), new Complex(2.0, 1), new Complex(2.0, 1) }) },
+                    {"Singular3x3", new DenseMatrix(3, 3, new[] {new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(2.0, 1), new Complex(2.0, 1), new Complex(2.0, 1)})},
-                               { "Square3x3", new DenseMatrix(3, 3, new[] { new Complex(-1.1, 1), Complex.Zero, new Complex(-4.4, 1), new Complex(-2.2, 1), new Complex(1.1, 1), new Complex(5.5, 1), new Complex(-3.3, 1), new Complex(2.2, 1), new Complex(6.6, 1) }) },
+                    {"Square3x3", new DenseMatrix(3, 3, new[] {new Complex(-1.1, 1), Complex.Zero, new Complex(-4.4, 1), new Complex(-2.2, 1), new Complex(1.1, 1), new Complex(5.5, 1), new Complex(-3.3, 1), new Complex(2.2, 1), new Complex(6.6, 1)})},
-                               { "Square4x4", new DenseMatrix(4, 4, new[] { new Complex(-1.1, 1), Complex.Zero, new Complex(1.0, 1), new Complex(-4.4, 1), new Complex(-2.2, 1), new Complex(1.1, 1), new Complex(2.1, 1), new Complex(5.5, 1), new Complex(-3.3, 1), new Complex(2.2, 1), new Complex(6.2, 1), new Complex(6.6, 1), new Complex(-4.4, 1), new Complex(3.3, 1), new Complex(4.3, 1), new Complex(-7.7, 1) }) },
+                    {"Square4x4", new DenseMatrix(4, 4, new[] {new Complex(-1.1, 1), Complex.Zero, new Complex(1.0, 1), new Complex(-4.4, 1), new Complex(-2.2, 1), new Complex(1.1, 1), new Complex(2.1, 1), new Complex(5.5, 1), new Complex(-3.3, 1), new Complex(2.2, 1), new Complex(6.2, 1), new Complex(6.6, 1), new Complex(-4.4, 1), new Complex(3.3, 1), new Complex(4.3, 1), new Complex(-7.7, 1)})},
-                               { "Tall3x2", new DenseMatrix(3, 2, new[] { new Complex(-1.1, 1), Complex.Zero, new Complex(-4.4, 1), new Complex(-2.2, 1), new Complex(1.1, 1), new Complex(5.5, 1) }) },
+                    {"Tall3x2", new DenseMatrix(3, 2, new[] {new Complex(-1.1, 1), Complex.Zero, new Complex(-4.4, 1), new Complex(-2.2, 1), new Complex(1.1, 1), new Complex(5.5, 1)})},
-                               { "Wide2x3", new DenseMatrix(2, 3, new[] { new Complex(-1.1, 1), Complex.Zero, new Complex(-2.2, 1), new Complex(1.1, 1), new Complex(-3.3, 1), new Complex(2.2, 1) }) }
+                    {"Wide2x3", new DenseMatrix(2, 3, new[] {new Complex(-1.1, 1), Complex.Zero, new Complex(-2.2, 1), new Complex(1.1, 1), new Complex(-3.3, 1), new Complex(2.2, 1)})}
-                           };
+                };
 
             foreach (var name in testData.Keys)
             {
@@ -106,7 +110,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         [Test]
         public void MatrixFrom1DArrayIsReference()
         {
-            var data = new[] { new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(2.0, 1), new Complex(2.0, 1), new Complex(2.0, 1) };
+            var data = new[] {new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(2.0, 1), new Complex(2.0, 1), new Complex(2.0, 1)};
             var matrix = new DenseMatrix(3, 3, data);
             matrix[0, 0] = new Complex(10.0, 1);
             Assert.AreEqual(new Complex(10.0, 1), data[0]);
@@ -118,7 +122,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         [Test]
         public void MatrixFrom2DArrayIsCopy()
         {
-            var matrix = new DenseMatrix(TestData2D["Singular3x3"]);
+            var matrix = DenseMatrix.OfArray(TestData2D["Singular3x3"]);
             matrix[0, 0] = 10.0;
             Assert.AreEqual(new Complex(1.0, 1), TestData2D["Singular3x3"][0, 0]);
         }
@@ -135,7 +139,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         [TestCase("Wide2x3")]
         public void CanCreateMatrixFrom2DArray(string name)
         {
-            var matrix = new DenseMatrix(TestData2D[name]);
+            var matrix = DenseMatrix.OfArray(TestData2D[name]);
             for (var i = 0; i < TestData2D[name].GetLength(0); i++)
             {
                 for (var j = 0; j < TestData2D[name].GetLength(1); j++)

src/UnitTests/LinearAlgebraTests/Complex/DiagonalMatrixTests.cs

@@ -3,7 +3,9 @@
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
-// Copyright (c) 2009-2010 Math.NET
+//
+// Copyright (c) 2009-2013 Math.NET
+//
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
 // files (the "Software"), to deal in the Software without
@@ -12,8 +14,10 @@
 // copies of the Software, and to permit persons to whom the
 // Software is furnished to do so, subject to the following
 // conditions:
+//
 // The above copyright notice and this permission notice shall be
 // included in all copies or substantial portions of the Software.
+//
 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
@@ -28,15 +32,10 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
 {
     using System;
     using System.Collections.Generic;
-    using System.Linq;
     using System.Numerics;
     using LinearAlgebra.Complex;
     using NUnit.Framework;
 
-#if PORTABLE
-    using Threading;
-#endif
-
     /// <summary>
     /// Diagonal matrix tests.
     /// </summary>
@@ -49,14 +48,14 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         public override void SetupMatrices()
         {
             TestData2D = new Dictionary<string, Complex[,]>
-                         {
+                {
-                             { "Singular3x3", new[,] { { new Complex(1.0, 1), Complex.Zero, Complex.Zero }, { Complex.Zero, Complex.Zero, Complex.Zero }, { Complex.Zero, Complex.Zero, new Complex(3.0, 1) } } },
+                    {"Singular3x3", new[,] {{new Complex(1.0, 1), Complex.Zero, Complex.Zero}, {Complex.Zero, Complex.Zero, Complex.Zero}, {Complex.Zero, Complex.Zero, new Complex(3.0, 1)}}},
-                             { "Square3x3", new[,] { { new Complex(-1.1, 1), Complex.Zero, Complex.Zero }, { Complex.Zero, new Complex(1.1, 1), Complex.Zero }, { Complex.Zero, Complex.Zero, new Complex(6.6, 1) } } },
+                    {"Square3x3", new[,] {{new Complex(-1.1, 1), Complex.Zero, Complex.Zero}, {Complex.Zero, new Complex(1.1, 1), Complex.Zero}, {Complex.Zero, Complex.Zero, new Complex(6.6, 1)}}},
-                             { "Square4x4", new[,] { { new Complex(-1.1, 1), Complex.Zero, Complex.Zero, Complex.Zero }, { Complex.Zero, new Complex(1.1, 1), Complex.Zero, Complex.Zero }, { Complex.Zero, Complex.Zero, new Complex(6.2, 1), Complex.Zero }, { Complex.Zero, Complex.Zero, Complex.Zero, new Complex(-7.7, 1) } } },
+                    {"Square4x4", new[,] {{new Complex(-1.1, 1), Complex.Zero, Complex.Zero, Complex.Zero}, {Complex.Zero, new Complex(1.1, 1), Complex.Zero, Complex.Zero}, {Complex.Zero, Complex.Zero, new Complex(6.2, 1), Complex.Zero}, {Complex.Zero, Complex.Zero, Complex.Zero, new Complex(-7.7, 1)}}},
-                             { "Singular4x4", new[,] { { new Complex(-1.1, 1), Complex.Zero, Complex.Zero, Complex.Zero }, { Complex.Zero, new Complex(-2.2, 1), Complex.Zero, Complex.Zero }, { Complex.Zero, Complex.Zero, Complex.Zero, Complex.Zero }, { Complex.Zero, Complex.Zero, Complex.Zero, new Complex(-4.4, 1) } } },
+                    {"Singular4x4", new[,] {{new Complex(-1.1, 1), Complex.Zero, Complex.Zero, Complex.Zero}, {Complex.Zero, new Complex(-2.2, 1), Complex.Zero, Complex.Zero}, {Complex.Zero, Complex.Zero, Complex.Zero, Complex.Zero}, {Complex.Zero, Complex.Zero, Complex.Zero, new Complex(-4.4, 1)}}},
-                             { "Tall3x2", new[,] { { new Complex(-1.1, 1), Complex.Zero }, { Complex.Zero, new Complex(1.1, 1) }, { Complex.Zero, Complex.Zero } } },
+                    {"Tall3x2", new[,] {{new Complex(-1.1, 1), Complex.Zero}, {Complex.Zero, new Complex(1.1, 1)}, {Complex.Zero, Complex.Zero}}},
-                             { "Wide2x3", new[,] { { new Complex(-1.1, 1), Complex.Zero, Complex.Zero }, { Complex.Zero, new Complex(1.1, 1), Complex.Zero } } }
+                    {"Wide2x3", new[,] {{new Complex(-1.1, 1), Complex.Zero, Complex.Zero}, {Complex.Zero, new Complex(1.1, 1), Complex.Zero}}}
-                         };
+                };
 
             TestMatrices = new Dictionary<string, Matrix>();
             foreach (var name in TestData2D.Keys)
@@ -114,13 +113,13 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         public void CanCreateMatrixFromDiagonalArray()
         {
             var testData = new Dictionary<string, Matrix>
-                           {
+                {
-                               { "Singular3x3", new DiagonalMatrix(3, 3, new[] { new Complex(1.0, 1), Complex.Zero, new Complex(3.0, 1) }) },
+                    {"Singular3x3", new DiagonalMatrix(3, 3, new[] {new Complex(1.0, 1), Complex.Zero, new Complex(3.0, 1)})},
-                               { "Square3x3", new DiagonalMatrix(3, 3, new[] { new Complex(-1.1, 1), new Complex(1.1, 1), new Complex(6.6, 1) }) },
+                    {"Square3x3", new DiagonalMatrix(3, 3, new[] {new Complex(-1.1, 1), new Complex(1.1, 1), new Complex(6.6, 1)})},
-                               { "Square4x4", new DiagonalMatrix(4, 4, new[] { new Complex(-1.1, 1), new Complex(1.1, 1), new Complex(6.2, 1), new Complex(-7.7, 1) }) },
+                    {"Square4x4", new DiagonalMatrix(4, 4, new[] {new Complex(-1.1, 1), new Complex(1.1, 1), new Complex(6.2, 1), new Complex(-7.7, 1)})},
-                               { "Tall3x2", new DiagonalMatrix(3, 2, new[] { new Complex(-1.1, 1), new Complex(1.1, 1) }) },
+                    {"Tall3x2", new DiagonalMatrix(3, 2, new[] {new Complex(-1.1, 1), new Complex(1.1, 1)})},
-                               { "Wide2x3", new DiagonalMatrix(2, 3, new[] { new Complex(-1.1, 1), new Complex(1.1, 1) }) },
+                    {"Wide2x3", new DiagonalMatrix(2, 3, new[] {new Complex(-1.1, 1), new Complex(1.1, 1)})},
-                           };
+                };
 
             foreach (var name in testData.Keys)
             {
@@ -134,7 +133,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         [Test]
         public void MatrixFrom1DArrayIsReference()
         {
-            var data = new[] { new Complex(1.0, 1), new Complex(2.0, 1), new Complex(3.0, 1), new Complex(4.0, 1), new Complex(5.0, 1) };
+            var data = new[] {new Complex(1.0, 1), new Complex(2.0, 1), new Complex(3.0, 1), new Complex(4.0, 1), new Complex(5.0, 1)};
             var matrix = new DiagonalMatrix(5, 5, data);
             matrix[0, 0] = new Complex(10.0, 1);
             Assert.AreEqual(new Complex(10.0, 1), data[0]);
@@ -221,7 +220,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
             {
                 for (var j = 0; j < matrixC.ColumnCount; j++)
                 {
-                    AssertHelpers.AlmostEqual(matrixA.Row(i) * matrixB.Column(j), matrixC[i, j], 15);
+                    AssertHelpers.AlmostEqual(matrixA.Row(i)*matrixB.Column(j), matrixC[i, j], 15);
                 }
             }
         }
@@ -233,7 +232,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         public void PermuteMatrixRowsThrowsInvalidOperationException()
         {
             var matrixp = CreateMatrix(TestData2D["Singular3x3"]);
-            var permutation = new Permutation(new[] { 2, 0, 1 });
+            var permutation = new Permutation(new[] {2, 0, 1});
             Assert.Throws<InvalidOperationException>(() => matrixp.PermuteRows(permutation));
         }
 
@@ -244,7 +243,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         public void PermuteMatrixColumnsThrowsInvalidOperationException()
         {
             var matrixp = CreateMatrix(TestData2D["Singular3x3"]);
-            var permutation = new Permutation(new[] { 2, 0, 1 });
+            var permutation = new Permutation(new[] {2, 0, 1});
             Assert.Throws<InvalidOperationException>(() => matrixp.PermuteColumns(permutation));
         }
 
@@ -261,13 +260,13 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
                 var min = Math.Min(data.RowCount, data.ColumnCount);
                 for (var i = 0; i < min; i++)
                 {
-                    Assert.AreEqual(data[i, i] / other[i, i], result[i, i]);
+                    Assert.AreEqual(data[i, i]/other[i, i], result[i, i]);
                 }
 
                 result = data.PointwiseDivide(other);
                 for (var i = 0; i < min; i++)
                 {
-                    Assert.AreEqual(data[i, i] / other[i, i], result[i, i]);
+                    Assert.AreEqual(data[i, i]/other[i, i], result[i, i]);
                 }
             }
         }
@@ -278,15 +277,15 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         public override void CanComputeFrobeniusNorm()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.FrobeniusNorm(), matrix.FrobeniusNorm(), 14);
 
             matrix = TestMatrices["Wide2x3"];
-            denseMatrix = new DenseMatrix(TestData2D["Wide2x3"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Wide2x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.FrobeniusNorm(), matrix.FrobeniusNorm(), 14);
 
             matrix = TestMatrices["Tall3x2"];
-            denseMatrix = new DenseMatrix(TestData2D["Tall3x2"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Tall3x2"]);
             AssertHelpers.AlmostEqual(denseMatrix.FrobeniusNorm(), matrix.FrobeniusNorm(), 14);
         }
 
@@ -296,15 +295,15 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         public override void CanComputeInfinityNorm()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.InfinityNorm(), matrix.InfinityNorm(), 14);
 
             matrix = TestMatrices["Wide2x3"];
-            denseMatrix = new DenseMatrix(TestData2D["Wide2x3"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Wide2x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.InfinityNorm(), matrix.InfinityNorm(), 14);
 
             matrix = TestMatrices["Tall3x2"];
-            denseMatrix = new DenseMatrix(TestData2D["Tall3x2"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Tall3x2"]);
             AssertHelpers.AlmostEqual(denseMatrix.InfinityNorm(), matrix.InfinityNorm(), 14);
         }
 
@@ -314,15 +313,15 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         public override void CanComputeL1Norm()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.L1Norm(), matrix.L1Norm(), 14);
 
             matrix = TestMatrices["Wide2x3"];
-            denseMatrix = new DenseMatrix(TestData2D["Wide2x3"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Wide2x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.L1Norm(), matrix.L1Norm(), 14);
 
             matrix = TestMatrices["Tall3x2"];
-            denseMatrix = new DenseMatrix(TestData2D["Tall3x2"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Tall3x2"]);
             AssertHelpers.AlmostEqual(denseMatrix.L1Norm(), matrix.L1Norm(), 14);
         }
 
@@ -332,15 +331,15 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         public override void CanComputeL2Norm()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.L2Norm(), matrix.L2Norm(), 14);
 
             matrix = TestMatrices["Wide2x3"];
-            denseMatrix = new DenseMatrix(TestData2D["Wide2x3"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Wide2x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.L2Norm(), matrix.L2Norm(), 14);
 
             matrix = TestMatrices["Tall3x2"];
-            denseMatrix = new DenseMatrix(TestData2D["Tall3x2"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Tall3x2"]);
             AssertHelpers.AlmostEqual(denseMatrix.L2Norm(), matrix.L2Norm(), 14);
         }
 
@@ -351,11 +350,11 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         public void CanComputeDeterminant()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.Determinant(), matrix.Determinant(), 14);
 
             matrix = TestMatrices["Square4x4"];
-            denseMatrix = new DenseMatrix(TestData2D["Square4x4"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Square4x4"]);
             AssertHelpers.AlmostEqual(denseMatrix.Determinant(), matrix.Determinant(), 14);
         }
 

src/UnitTests/LinearAlgebraTests/Complex/IO/DelimitedWriterTests.cs

@@ -3,7 +3,9 @@
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
-// Copyright (c) 2009-2010 Math.NET
+//
+// Copyright (c) 2009-2013 Math.NET
+//
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
 // files (the "Software"), to deal in the Software without
@@ -12,8 +14,10 @@
 // copies of the Software, and to permit persons to whom the
 // Software is furnished to do so, subject to the following
 // conditions:
+//
 // The above copyright notice and this permission notice shall be
 // included in all copies or substantial portions of the Software.
+//
 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
@@ -26,13 +30,13 @@
 
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.IO
 {
+    using LinearAlgebra.Complex;
+    using LinearAlgebra.IO;
+    using NUnit.Framework;
     using System;
     using System.Globalization;
     using System.IO;
     using System.Numerics;
-    using LinearAlgebra.Complex;
-    using LinearAlgebra.IO;
-    using NUnit.Framework;
 
     /// <summary>
     /// Delimited writer tests.
@@ -46,19 +50,19 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.IO
         [Test]
         public void CanWriteCommaDelimitedData()
         {
-            var matrix = new DenseMatrix(new[,] { { new Complex(1.1, 1.1), new Complex(2.2, 2.2), new Complex(3.3, 3.3) }, { new Complex(4.4, 4.4), new Complex(5.5, 5.5), new Complex(6.6, 6.6) }, { new Complex(7.7, 7.7), new Complex(8.8, 8.8), new Complex(9.9, 9.9) } });
+            var matrix = DenseMatrix.OfArray(new[,] {{new Complex(1.1, 1.1), new Complex(2.2, 2.2), new Complex(3.3, 3.3)}, {new Complex(4.4, 4.4), new Complex(5.5, 5.5), new Complex(6.6, 6.6)}, {new Complex(7.7, 7.7), new Complex(8.8, 8.8), new Complex(9.9, 9.9)}});
             var writer = new DelimitedWriter(',')
-                         {
+                {
-                             CultureInfo = CultureInfo.InvariantCulture
+                    CultureInfo = CultureInfo.InvariantCulture
-                         };
+                };
             var stream = new MemoryStream();
             writer.WriteMatrix(matrix, stream);
             var data = stream.ToArray();
             var reader = new StreamReader(new MemoryStream(data));
             var text = reader.ReadToEnd();
             var expected = "(1.1, 1.1),(2.2, 2.2),(3.3, 3.3)" + Environment.NewLine
-                           + "(4.4, 4.4),(5.5, 5.5),(6.6, 6.6)" + Environment.NewLine
+                + "(4.4, 4.4),(5.5, 5.5),(6.6, 6.6)" + Environment.NewLine
-                           + "(7.7, 7.7),(8.8, 8.8),(9.9, 9.9)";
+                + "(7.7, 7.7),(8.8, 8.8),(9.9, 9.9)";
             Assert.AreEqual(expected, text);
         }
 
@@ -68,20 +72,20 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.IO
         [Test]
         public void CanWritePeriodDelimitedData()
         {
-            var matrix = new DenseMatrix(new[,] { { new Complex(1.1, 1.1), new Complex(2.2, 2.2), new Complex(3.3, 3.3) }, { new Complex(4.4, 4.4), new Complex(5.5, 5.5), new Complex(6.6, 6.6) }, { new Complex(7.7, 7.7), new Complex(8.8, 8.8), new Complex(9.9, 9.9) } });
+            var matrix = DenseMatrix.OfArray(new[,] {{new Complex(1.1, 1.1), new Complex(2.2, 2.2), new Complex(3.3, 3.3)}, {new Complex(4.4, 4.4), new Complex(5.5, 5.5), new Complex(6.6, 6.6)}, {new Complex(7.7, 7.7), new Complex(8.8, 8.8), new Complex(9.9, 9.9)}});
             var culture = new CultureInfo("tr-TR");
             var writer = new DelimitedWriter('.')
-                         {
+                {
-                             CultureInfo = culture
+                    CultureInfo = culture
-                         };
+                };
             var stream = new MemoryStream();
             writer.WriteMatrix(matrix, stream);
             var data = stream.ToArray();
             var reader = new StreamReader(new MemoryStream(data));
             var text = reader.ReadToEnd();
             var expected = "(1,1, 1,1).(2,2, 2,2).(3,3, 3,3)" + Environment.NewLine
-                           + "(4,4, 4,4).(5,5, 5,5).(6,6, 6,6)" + Environment.NewLine
+                + "(4,4, 4,4).(5,5, 5,5).(6,6, 6,6)" + Environment.NewLine
-                           + "(7,7, 7,7).(8,8, 8,8).(9,9, 9,9)";
+                + "(7,7, 7,7).(8,8, 8,8).(9,9, 9,9)";
             Assert.AreEqual(expected, text);
         }
 
@@ -91,19 +95,19 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.IO
         [Test]
         public void CanWriteSpaceDelimitedData()
         {
-            var matrix = new DenseMatrix(new[,] { { new Complex(1.1, 1.1), new Complex(2.2, 2.2), new Complex(3.3, 3.3) }, { new Complex(4.4, 4.4), new Complex(5.5, 5.5), new Complex(6.6, 6.6) }, { new Complex(7.7, 7.7), new Complex(8.8, 8.8), new Complex(9.9, 9.9) } });
+            var matrix = DenseMatrix.OfArray(new[,] {{new Complex(1.1, 1.1), new Complex(2.2, 2.2), new Complex(3.3, 3.3)}, {new Complex(4.4, 4.4), new Complex(5.5, 5.5), new Complex(6.6, 6.6)}, {new Complex(7.7, 7.7), new Complex(8.8, 8.8), new Complex(9.9, 9.9)}});
             var writer = new DelimitedWriter(' ')
-                         {
+                {
-                             CultureInfo = CultureInfo.InvariantCulture
+                    CultureInfo = CultureInfo.InvariantCulture
-                         };
+                };
             var stream = new MemoryStream();
             writer.WriteMatrix(matrix, stream);
             var data = stream.ToArray();
             var reader = new StreamReader(new MemoryStream(data));
             var text = reader.ReadToEnd();
             var expected = "(1.1, 1.1) (2.2, 2.2) (3.3, 3.3)" + Environment.NewLine
-                           + "(4.4, 4.4) (5.5, 5.5) (6.6, 6.6)" + Environment.NewLine
+                + "(4.4, 4.4) (5.5, 5.5) (6.6, 6.6)" + Environment.NewLine
-                           + "(7.7, 7.7) (8.8, 8.8) (9.9, 9.9)";
+                + "(7.7, 7.7) (8.8, 8.8) (9.9, 9.9)";
             Assert.AreEqual(expected, text);
         }
 
@@ -113,22 +117,22 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex.IO
         [Test]
         public void CanWriteTabDelimitedData()
         {
-            var matrix = new DenseMatrix(new[,] { { new Complex(1.1, 1.1), new Complex(2.2, 2.2), new Complex(3.3, 3.3) }, { new Complex(4.4, 4.4), new Complex(5.5, 5.5), new Complex(6.6, 6.6) }, { new Complex(7.7, 7.7), new Complex(8.8, 8.8), new Complex(9.9, 9.9) } });
+            var matrix = DenseMatrix.OfArray(new[,] {{new Complex(1.1, 1.1), new Complex(2.2, 2.2), new Complex(3.3, 3.3)}, {new Complex(4.4, 4.4), new Complex(5.5, 5.5), new Complex(6.6, 6.6)}, {new Complex(7.7, 7.7), new Complex(8.8, 8.8), new Complex(9.9, 9.9)}});
-            var headers = new[] { "a", "b", "c" };
+            var headers = new[] {"a", "b", "c"};
             var writer = new DelimitedWriter('\t')
-                         {
+                {
-                             ColumnHeaders = headers,
+                    ColumnHeaders = headers,
-                             CultureInfo = CultureInfo.InvariantCulture
+                    CultureInfo = CultureInfo.InvariantCulture
-                         };
+                };
             var stream = new MemoryStream();
             writer.WriteMatrix(matrix, stream);
             var data = stream.ToArray();
             var reader = new StreamReader(new MemoryStream(data));
             var text = reader.ReadToEnd();
             var expected = "a\tb\tc" + Environment.NewLine
-                           + "(1.1, 1.1)\t(2.2, 2.2)\t(3.3, 3.3)" + Environment.NewLine
+                + "(1.1, 1.1)\t(2.2, 2.2)\t(3.3, 3.3)" + Environment.NewLine
-                           + "(4.4, 4.4)\t(5.5, 5.5)\t(6.6, 6.6)" + Environment.NewLine
+                + "(4.4, 4.4)\t(5.5, 5.5)\t(6.6, 6.6)" + Environment.NewLine
-                           + "(7.7, 7.7)\t(8.8, 8.8)\t(9.9, 9.9)";
+                + "(7.7, 7.7)\t(8.8, 8.8)\t(9.9, 9.9)";
             Assert.AreEqual(expected, text);
         }
     }

src/UnitTests/LinearAlgebraTests/Complex/MatrixStructureTheory.cs

@@ -1,12 +1,41 @@
-using System.Linq;
+// <copyright file="MatrixStructureTheory.cs" company="Math.NET">
-using MathNet.Numerics.Distributions;
+// Math.NET Numerics, part of the Math.NET Project
-using MathNet.Numerics.Random;
+// http://numerics.mathdotnet.com
+// http://github.com/mathnet/mathnet-numerics
+// http://mathnetnumerics.codeplex.com
+//
+// Copyright (c) 2009-2013 Math.NET
+//
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+//
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+//
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
 
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
 {
+    using Distributions;
     using LinearAlgebra.Complex;
     using LinearAlgebra.Generic;
+    using Numerics.Random;
     using NUnit.Framework;
+    using System.Linq;
     using System.Numerics;
 
     [TestFixture]
@@ -15,17 +44,17 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         [Datapoints]
         Matrix<Complex>[] _matrices = new Matrix<Complex>[]
             {
-                new DenseMatrix(new[,] {{1d, new Complex(1.1d, -4d), 2d}, {1d, 1d, 2d}, {1d, new Complex(1d, 2d), 2d}}),
+                DenseMatrix.OfArray(new[,] {{1d, new Complex(1.1d, -4d), 2d}, {1d, 1d, 2d}, {1d, new Complex(1d, 2d), 2d}}),
-                new DenseMatrix(new[,] {{-1.1d, -2.2d, -3.3d}, {0d, 1.1d, new Complex(2.2d, -1.2d)}, {-4.4d, 5.5d, 6.6d}}),
+                DenseMatrix.OfArray(new[,] {{-1.1d, -2.2d, -3.3d}, {0d, 1.1d, new Complex(2.2d, -1.2d)}, {-4.4d, 5.5d, 6.6d}}),
-                new DenseMatrix(new[,] {{new Complex(-1.1d, -2d), -2.2d, -3.3d, -4.4d}, {0d, 1.1d, 2.2d, 3.3d}, {1d, 2.1d, 6.2d, 4.3d}, {-4.4d, 5.5d, 6.6d, -7.7d}}),
+                DenseMatrix.OfArray(new[,] {{new Complex(-1.1d, -2d), -2.2d, -3.3d, -4.4d}, {0d, 1.1d, 2.2d, 3.3d}, {1d, 2.1d, 6.2d, 4.3d}, {-4.4d, 5.5d, 6.6d, -7.7d}}),
-                new DenseMatrix(new[,] {{-1.1d, new Complex(-2.2d, 3.4d), -3.3d, -4.4d}, {-1.1d, -2.2d, -3.3d, -4.4d}, {-1.1d, -2.2d, -3.3d, -4.4d}, {-1.1d, -2.2d, -3.3d, -4.4d}}),
+                DenseMatrix.OfArray(new[,] {{-1.1d, new Complex(-2.2d, 3.4d), -3.3d, -4.4d}, {-1.1d, -2.2d, -3.3d, -4.4d}, {-1.1d, -2.2d, -3.3d, -4.4d}, {-1.1d, -2.2d, -3.3d, -4.4d}}),
-                new DenseMatrix(new[,] {{-1.1d, -2.2d}, {Complex.Zero, 1.1d}, {-4.4d, 5.5d}}),
+                DenseMatrix.OfArray(new[,] {{-1.1d, -2.2d}, {Complex.Zero, 1.1d}, {-4.4d, 5.5d}}),
-                new DenseMatrix(new[,] {{-1.1d, -2.2d, -3.3d}, {0d, new Complex(1.1d, 0.1d), 2.2d}}),
+                DenseMatrix.OfArray(new[,] {{-1.1d, -2.2d, -3.3d}, {0d, new Complex(1.1d, 0.1d), 2.2d}}),
-                new DenseMatrix(new[,] {{1d, 2d, 3d}, {2d, new Complex(2d, 2d), 0d}, {3d, Complex.Zero, 3d}}),
+                DenseMatrix.OfArray(new[,] {{1d, 2d, 3d}, {2d, new Complex(2d, 2d), 0d}, {3d, Complex.Zero, 3d}}),
 
-                new SparseMatrix(new[,] {{7d, 1d, 2d}, {1d, 1d, 2d}, {1d, 1d + Complex.ImaginaryOne, 2d}}),
+                SparseMatrix.OfArray(new[,] {{7d, 1d, 2d}, {1d, 1d, 2d}, {1d, 1d + Complex.ImaginaryOne, 2d}}),
-                new SparseMatrix(new[,] {{7d, 1d, 2d}, {new Complex(1d, 2d), 0d, Complex.Zero}, {-2d, 0d, 0d}}),
+                SparseMatrix.OfArray(new[,] {{7d, 1d, 2d}, {new Complex(1d, 2d), 0d, Complex.Zero}, {-2d, 0d, 0d}}),
-                new SparseMatrix(new[,] {{-1.1d, 0d, 0d}, {0d, new Complex(1.1d, 2d), 2.2d}}),
+                SparseMatrix.OfArray(new[,] {{-1.1d, 0d, 0d}, {0d, new Complex(1.1d, 2d), 2.2d}}),
 
                 new DiagonalMatrix(3, 3, new[] {new Complex(1d, 1d), -2d, 1.5d}),
                 new DiagonalMatrix(3, 3, new[] {new Complex(1d, 2d), 0d, -1.5d}),
@@ -68,4 +97,4 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
             get { return Complex.Zero; }
         }
     }
-}
+}

src/UnitTests/LinearAlgebraTests/Complex/SparseMatrixTests.cs

@@ -3,7 +3,9 @@
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
-// Copyright (c) 2009-2010 Math.NET
+//
+// Copyright (c) 2009-2013 Math.NET
+//
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
 // files (the "Software"), to deal in the Software without
@@ -12,8 +14,10 @@
 // copies of the Software, and to permit persons to whom the
 // Software is furnished to do so, subject to the following
 // conditions:
+//
 // The above copyright notice and this permission notice shall be
 // included in all copies or substantial portions of the Software.
+//
 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
@@ -26,11 +30,11 @@
 
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
 {
+    using LinearAlgebra.Complex;
+    using NUnit.Framework;
     using System;
     using System.Collections.Generic;
     using System.Numerics;
-    using LinearAlgebra.Complex;
-    using NUnit.Framework;
 
     /// <summary>
     /// Sparse matrix tests.
@@ -55,7 +59,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         /// <returns>A matrix with the given values.</returns>
         protected override Matrix CreateMatrix(Complex[,] data)
         {
-            return new SparseMatrix(data);
+            return SparseMatrix.OfArray(data);
         }
 
         /// <summary>
@@ -86,13 +90,13 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         public void CanCreateMatrixFrom1DArray()
         {
             var testData = new Dictionary<string, Matrix>
-                           {
+                {
-                               { "Singular3x3", new SparseMatrix(3, 3, new[] { new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(2.0, 1), new Complex(2.0, 1), new Complex(2.0, 1) }) },
+                    {"Singular3x3", SparseMatrix.OfColumnMajor(3, 3, new[] {new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(2.0, 1), new Complex(2.0, 1), new Complex(2.0, 1)})},
-                               { "Square3x3", new SparseMatrix(3, 3, new[] { new Complex(-1.1, 1), Complex.Zero, new Complex(-4.4, 1), new Complex(-2.2, 1), new Complex(1.1, 1), new Complex(5.5, 1), new Complex(-3.3, 1), new Complex(2.2, 1), new Complex(6.6, 1) }) },
+                    {"Square3x3", SparseMatrix.OfColumnMajor(3, 3, new[] {new Complex(-1.1, 1), Complex.Zero, new Complex(-4.4, 1), new Complex(-2.2, 1), new Complex(1.1, 1), new Complex(5.5, 1), new Complex(-3.3, 1), new Complex(2.2, 1), new Complex(6.6, 1)})},
-                               { "Square4x4", new SparseMatrix(4, 4, new[] { new Complex(-1.1, 1), Complex.Zero, new Complex(1.0, 1), new Complex(-4.4, 1), new Complex(-2.2, 1), new Complex(1.1, 1), new Complex(2.1, 1), new Complex(5.5, 1), new Complex(-3.3, 1), new Complex(2.2, 1), new Complex(6.2, 1), new Complex(6.6, 1), new Complex(-4.4, 1), new Complex(3.3, 1), new Complex(4.3, 1), new Complex(-7.7, 1) }) },
+                    {"Square4x4", SparseMatrix.OfColumnMajor(4, 4, new[] {new Complex(-1.1, 1), Complex.Zero, new Complex(1.0, 1), new Complex(-4.4, 1), new Complex(-2.2, 1), new Complex(1.1, 1), new Complex(2.1, 1), new Complex(5.5, 1), new Complex(-3.3, 1), new Complex(2.2, 1), new Complex(6.2, 1), new Complex(6.6, 1), new Complex(-4.4, 1), new Complex(3.3, 1), new Complex(4.3, 1), new Complex(-7.7, 1)})},
-                               { "Tall3x2", new SparseMatrix(3, 2, new[] { new Complex(-1.1, 1), Complex.Zero, new Complex(-4.4, 1), new Complex(-2.2, 1), new Complex(1.1, 1), new Complex(5.5, 1) }) },
+                    {"Tall3x2", SparseMatrix.OfColumnMajor(3, 2, new[] {new Complex(-1.1, 1), Complex.Zero, new Complex(-4.4, 1), new Complex(-2.2, 1), new Complex(1.1, 1), new Complex(5.5, 1)})},
-                               { "Wide2x3", new SparseMatrix(2, 3, new[] { new Complex(-1.1, 1), Complex.Zero, new Complex(-2.2, 1), new Complex(1.1, 1), new Complex(-3.3, 1), new Complex(2.2, 1) }) }
+                    {"Wide2x3", SparseMatrix.OfColumnMajor(2, 3, new[] {new Complex(-1.1, 1), Complex.Zero, new Complex(-2.2, 1), new Complex(1.1, 1), new Complex(-3.3, 1), new Complex(2.2, 1)})}
-                           };
+                };
 
             foreach (var name in testData.Keys)
             {
@@ -107,8 +111,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         public void MatrixFrom1DArrayIsCopy()
         {
             // Sparse Matrix copies values from Complex[], but no remember reference. 
-            var data = new[] { new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(2.0, 1), new Complex(2.0, 1), new Complex(2.0, 1) };
+            var data = new[] {new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(1.0, 1), new Complex(2.0, 1), new Complex(2.0, 1), new Complex(2.0, 1)};
-            var matrix = new SparseMatrix(3, 3, data);
+            var matrix = SparseMatrix.OfColumnMajor(3, 3, data);
             matrix[0, 0] = new Complex(10.0, 1);
             Assert.AreNotEqual(new Complex(10.0, 1), data[0]);
         }
@@ -119,7 +123,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         [Test]
         public void MatrixFrom2DArrayIsCopy()
         {
-            var matrix = new SparseMatrix(TestData2D["Singular3x3"]);
+            var matrix = SparseMatrix.OfArray(TestData2D["Singular3x3"]);
             matrix[0, 0] = new Complex(10.0, 1);
             Assert.AreEqual(new Complex(1.0, 1), TestData2D["Singular3x3"][0, 0]);
         }
@@ -136,7 +140,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         [TestCase("Wide2x3")]
         public void CanCreateMatrixFrom2DArray(string name)
         {
-            var matrix = new SparseMatrix(TestData2D[name]);
+            var matrix = SparseMatrix.OfArray(TestData2D[name]);
             for (var i = 0; i < TestData2D[name].GetLength(0); i++)
             {
                 for (var j = 0; j < TestData2D[name].GetLength(1); j++)
@@ -187,7 +191,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
             {
                 for (var j = 0; j < matrix.ColumnCount; j++)
                 {
-                    var value = rnd.Next(10) * rnd.Next(10) * rnd.Next(10) * rnd.Next(10) * rnd.Next(10);
+                    var value = rnd.Next(10)*rnd.Next(10)*rnd.Next(10)*rnd.Next(10)*rnd.Next(10);
                     if (value != 0)
                     {
                         nonzero++;
@@ -207,7 +211,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         public void CanAddSparseMatricesBothWays()
         {
             var m1 = new SparseMatrix(1, 3);
-            var m2 = new SparseMatrix(new Complex[,] { { 0, 1, 1 } });
+            var m2 = SparseMatrix.OfArray(new Complex[,] { { 0, 1, 1 } });
             var sum1 = m1 + m2;
             var sum2 = m2 + m1;
             Assert.IsTrue(sum1.Equals(m2));
@@ -217,27 +221,27 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
             sparseResult.Add(m2, sparseResult);
             Assert.IsTrue(sparseResult.Equals(sum1));
 
-            sparseResult = new SparseMatrix(new Complex[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new Complex[,] { { 0, 1, 1 } });
             sparseResult.Add(m1, sparseResult);
             Assert.IsTrue(sparseResult.Equals(sum1));
 
-            sparseResult = new SparseMatrix(new Complex[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new Complex[,] { { 0, 1, 1 } });
             m1.Add(sparseResult, sparseResult);
             Assert.IsTrue(sparseResult.Equals(sum1));
 
-            sparseResult = new SparseMatrix(new Complex[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new Complex[,] { { 0, 1, 1 } });
             sparseResult.Add(sparseResult, sparseResult);
-            Assert.IsTrue(sparseResult.Equals(2 * sum1));
+            Assert.IsTrue(sparseResult.Equals(2*sum1));
 
             var denseResult = new DenseMatrix(1, 3);
             denseResult.Add(m2, denseResult);
             Assert.IsTrue(denseResult.Equals(sum1));
 
-            denseResult = new DenseMatrix(new Complex[,] { { 0, 1, 1 } });
+            denseResult = DenseMatrix.OfArray(new Complex[,] {{0, 1, 1}});
             denseResult.Add(m1, denseResult);
             Assert.IsTrue(denseResult.Equals(sum1));
 
-            var m3 = new DenseMatrix(new Complex[,] { { 0, 1, 1 } });
+            var m3 = DenseMatrix.OfArray(new Complex[,] {{0, 1, 1}});
             var sum3 = m1 + m3;
             var sum4 = m3 + m1;
             Assert.IsTrue(sum3.Equals(m3));
@@ -251,7 +255,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
         public void CanSubtractSparseMatricesBothWays()
         {
             var m1 = new SparseMatrix(1, 3);
-            var m2 = new SparseMatrix(new Complex[,] { { 0, 1, 1 } });
+            var m2 = SparseMatrix.OfArray(new Complex[,] { { 0, 1, 1 } });
             var diff1 = m1 - m2;
             var diff2 = m2 - m1;
             Assert.IsTrue(diff1.Equals(m2.Negate()));
@@ -261,27 +265,27 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
             sparseResult.Subtract(m2, sparseResult);
             Assert.IsTrue(sparseResult.Equals(diff1));
 
-            sparseResult = new SparseMatrix(new Complex[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new Complex[,] { { 0, 1, 1 } });
             sparseResult.Subtract(m1, sparseResult);
             Assert.IsTrue(sparseResult.Equals(diff2));
 
-            sparseResult = new SparseMatrix(new Complex[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new Complex[,] { { 0, 1, 1 } });
             m1.Subtract(sparseResult, sparseResult);
             Assert.IsTrue(sparseResult.Equals(diff1));
 
-            sparseResult = new SparseMatrix(new Complex[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new Complex[,] { { 0, 1, 1 } });
             sparseResult.Subtract(sparseResult, sparseResult);
-            Assert.IsTrue(sparseResult.Equals(0 * diff1));
+            Assert.IsTrue(sparseResult.Equals(0*diff1));
 
             var denseResult = new DenseMatrix(1, 3);
             denseResult.Subtract(m2, denseResult);
             Assert.IsTrue(denseResult.Equals(diff1));
 
-            denseResult = new DenseMatrix(new Complex[,] { { 0, 1, 1 } });
+            denseResult = DenseMatrix.OfArray(new Complex[,] {{0, 1, 1}});
             denseResult.Subtract(m1, denseResult);
             Assert.IsTrue(denseResult.Equals(diff2));
 
-            var m3 = new DenseMatrix(new Complex[,] { { 0, 1, 1 } });
+            var m3 = DenseMatrix.OfArray(new Complex[,] {{0, 1, 1}});
             var diff3 = m1 - m3;
             var diff4 = m3 - m1;
             Assert.IsTrue(diff3.Equals(m3.Negate()));

src/UnitTests/LinearAlgebraTests/Complex32/DenseMatrixTests.cs

@@ -3,7 +3,9 @@
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
-// Copyright (c) 2009-2010 Math.NET
+//
+// Copyright (c) 2009-2013 Math.NET
+//
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
 // files (the "Software"), to deal in the Software without
@@ -12,8 +14,10 @@
 // copies of the Software, and to permit persons to whom the
 // Software is furnished to do so, subject to the following
 // conditions:
+//
 // The above copyright notice and this permission notice shall be
 // included in all copies or substantial portions of the Software.
+//
 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
@@ -26,10 +30,10 @@
 
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
 {
-    using System;
-    using System.Collections.Generic;
     using LinearAlgebra.Complex32;
     using NUnit.Framework;
+    using System;
+    using System.Collections.Generic;
     using Complex32 = Numerics.Complex32;
 
     /// <summary>
@@ -55,7 +59,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         /// <returns>A matrix with the given values.</returns>
         protected override Matrix CreateMatrix(Complex32[,] data)
         {
-            return new DenseMatrix(data);
+            return DenseMatrix.OfArray(data);
         }
 
         /// <summary>
@@ -86,13 +90,13 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         public void CanCreateMatrixFrom1DArray()
         {
             var testData = new Dictionary<string, Matrix>
-                           {
+                {
-                               { "Singular3x3", new DenseMatrix(3, 3, new[] { new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(2.0f, 1), new Complex32(2.0f, 1), new Complex32(2.0f, 1) }) },
+                    {"Singular3x3", new DenseMatrix(3, 3, new[] {new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(2.0f, 1), new Complex32(2.0f, 1), new Complex32(2.0f, 1)})},
-                               { "Square3x3", new DenseMatrix(3, 3, new[] { new Complex32(-1.1f, 1), Complex32.Zero, new Complex32(-4.4f, 1), new Complex32(-2.2f, 1), new Complex32(1.1f, 1), new Complex32(5.5f, 1), new Complex32(-3.3f, 1), new Complex32(2.2f, 1), new Complex32(6.6f, 1) }) },
+                    {"Square3x3", new DenseMatrix(3, 3, new[] {new Complex32(-1.1f, 1), Complex32.Zero, new Complex32(-4.4f, 1), new Complex32(-2.2f, 1), new Complex32(1.1f, 1), new Complex32(5.5f, 1), new Complex32(-3.3f, 1), new Complex32(2.2f, 1), new Complex32(6.6f, 1)})},
-                               { "Square4x4", new DenseMatrix(4, 4, new[] { new Complex32(-1.1f, 1), Complex32.Zero, new Complex32(1.0f, 1), new Complex32(-4.4f, 1), new Complex32(-2.2f, 1), new Complex32(1.1f, 1), new Complex32(2.1f, 1), new Complex32(5.5f, 1), new Complex32(-3.3f, 1), new Complex32(2.2f, 1), new Complex32(6.2f, 1), new Complex32(6.6f, 1), new Complex32(-4.4f, 1), new Complex32(3.3f, 1), new Complex32(4.3f, 1), new Complex32(-7.7f, 1) }) },
+                    {"Square4x4", new DenseMatrix(4, 4, new[] {new Complex32(-1.1f, 1), Complex32.Zero, new Complex32(1.0f, 1), new Complex32(-4.4f, 1), new Complex32(-2.2f, 1), new Complex32(1.1f, 1), new Complex32(2.1f, 1), new Complex32(5.5f, 1), new Complex32(-3.3f, 1), new Complex32(2.2f, 1), new Complex32(6.2f, 1), new Complex32(6.6f, 1), new Complex32(-4.4f, 1), new Complex32(3.3f, 1), new Complex32(4.3f, 1), new Complex32(-7.7f, 1)})},
-                               { "Tall3x2", new DenseMatrix(3, 2, new[] { new Complex32(-1.1f, 1), Complex32.Zero, new Complex32(-4.4f, 1), new Complex32(-2.2f, 1), new Complex32(1.1f, 1), new Complex32(5.5f, 1) }) },
+                    {"Tall3x2", new DenseMatrix(3, 2, new[] {new Complex32(-1.1f, 1), Complex32.Zero, new Complex32(-4.4f, 1), new Complex32(-2.2f, 1), new Complex32(1.1f, 1), new Complex32(5.5f, 1)})},
-                               { "Wide2x3", new DenseMatrix(2, 3, new[] { new Complex32(-1.1f, 1), Complex32.Zero, new Complex32(-2.2f, 1), new Complex32(1.1f, 1), new Complex32(-3.3f, 1), new Complex32(2.2f, 1) }) }
+                    {"Wide2x3", new DenseMatrix(2, 3, new[] {new Complex32(-1.1f, 1), Complex32.Zero, new Complex32(-2.2f, 1), new Complex32(1.1f, 1), new Complex32(-3.3f, 1), new Complex32(2.2f, 1)})}
-                           };
+                };
 
             foreach (var name in testData.Keys)
             {
@@ -106,7 +110,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         [Test]
         public void MatrixFrom1DArrayIsReference()
         {
-            var data = new[] { new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(2.0f, 1), new Complex32(2.0f, 1), new Complex32(2.0f, 1) };
+            var data = new[] {new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(2.0f, 1), new Complex32(2.0f, 1), new Complex32(2.0f, 1)};
             var matrix = new DenseMatrix(3, 3, data);
             matrix[0, 0] = new Complex32(10.0f, 1);
             Assert.AreEqual(new Complex32(10.0f, 1), data[0]);
@@ -118,7 +122,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         [Test]
         public void MatrixFrom2DArrayIsCopy()
         {
-            var matrix = new DenseMatrix(TestData2D["Singular3x3"]);
+            var matrix = DenseMatrix.OfArray(TestData2D["Singular3x3"]);
             matrix[0, 0] = 10.0f;
             Assert.AreEqual(new Complex32(1.0f, 1), TestData2D["Singular3x3"][0, 0]);
         }
@@ -135,7 +139,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         [TestCase("Wide2x3")]
         public void CanCreateMatrixFrom2DArray(string name)
         {
-            var matrix = new DenseMatrix(TestData2D[name]);
+            var matrix = DenseMatrix.OfArray(TestData2D[name]);
             for (var i = 0; i < TestData2D[name].GetLength(0); i++)
             {
                 for (var j = 0; j < TestData2D[name].GetLength(1); j++)

src/UnitTests/LinearAlgebraTests/Complex32/DiagonalMatrixTests.cs

@@ -3,7 +3,9 @@
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
-// Copyright (c) 2009-2010 Math.NET
+//
+// Copyright (c) 2009-2013 Math.NET
+//
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
 // files (the "Software"), to deal in the Software without
@@ -12,8 +14,10 @@
 // copies of the Software, and to permit persons to whom the
 // Software is furnished to do so, subject to the following
 // conditions:
+//
 // The above copyright notice and this permission notice shall be
 // included in all copies or substantial portions of the Software.
+//
 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
@@ -26,17 +30,12 @@
 
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
 {
-    using System;
-    using System.Collections.Generic;
-    using System.Linq;
     using LinearAlgebra.Complex32;
     using NUnit.Framework;
+    using System;
+    using System.Collections.Generic;
     using Complex32 = Numerics.Complex32;
 
-#if PORTABLE
-    using Threading;
-#endif
-
     /// <summary>
     /// Diagonal matrix tests.
     /// </summary>
@@ -49,14 +48,14 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         public override void SetupMatrices()
         {
             TestData2D = new Dictionary<string, Complex32[,]>
-                         {
+                {
-                             { "Singular3x3", new[,] { { new Complex32(1.0f, 1), Complex32.Zero, Complex32.Zero }, { Complex32.Zero, Complex32.Zero, Complex32.Zero }, { Complex32.Zero, Complex32.Zero, new Complex32(3.0f, 1) } } },
+                    {"Singular3x3", new[,] {{new Complex32(1.0f, 1), Complex32.Zero, Complex32.Zero}, {Complex32.Zero, Complex32.Zero, Complex32.Zero}, {Complex32.Zero, Complex32.Zero, new Complex32(3.0f, 1)}}},
-                             { "Square3x3", new[,] { { new Complex32(-1.1f, 1), Complex32.Zero, Complex32.Zero }, { Complex32.Zero, new Complex32(1.1f, 1), Complex32.Zero }, { Complex32.Zero, Complex32.Zero, new Complex32(6.6f, 1) } } },
+                    {"Square3x3", new[,] {{new Complex32(-1.1f, 1), Complex32.Zero, Complex32.Zero}, {Complex32.Zero, new Complex32(1.1f, 1), Complex32.Zero}, {Complex32.Zero, Complex32.Zero, new Complex32(6.6f, 1)}}},
-                             { "Square4x4", new[,] { { new Complex32(-1.1f, 1), Complex32.Zero, Complex32.Zero, Complex32.Zero }, { Complex32.Zero, new Complex32(1.1f, 1), Complex32.Zero, Complex32.Zero }, { Complex32.Zero, Complex32.Zero, new Complex32(6.2f, 1), Complex32.Zero }, { Complex32.Zero, Complex32.Zero, Complex32.Zero, new Complex32(-7.7f, 1) } } },
+                    {"Square4x4", new[,] {{new Complex32(-1.1f, 1), Complex32.Zero, Complex32.Zero, Complex32.Zero}, {Complex32.Zero, new Complex32(1.1f, 1), Complex32.Zero, Complex32.Zero}, {Complex32.Zero, Complex32.Zero, new Complex32(6.2f, 1), Complex32.Zero}, {Complex32.Zero, Complex32.Zero, Complex32.Zero, new Complex32(-7.7f, 1)}}},
-                             { "Singular4x4", new[,] { { new Complex32(-1.1f, 1), Complex32.Zero, Complex32.Zero, Complex32.Zero }, { Complex32.Zero, new Complex32(-2.2f, 1), Complex32.Zero, Complex32.Zero }, { Complex32.Zero, Complex32.Zero, Complex32.Zero, Complex32.Zero }, { Complex32.Zero, Complex32.Zero, Complex32.Zero, new Complex32(-4.4f, 1) } } },
+                    {"Singular4x4", new[,] {{new Complex32(-1.1f, 1), Complex32.Zero, Complex32.Zero, Complex32.Zero}, {Complex32.Zero, new Complex32(-2.2f, 1), Complex32.Zero, Complex32.Zero}, {Complex32.Zero, Complex32.Zero, Complex32.Zero, Complex32.Zero}, {Complex32.Zero, Complex32.Zero, Complex32.Zero, new Complex32(-4.4f, 1)}}},
-                             { "Tall3x2", new[,] { { new Complex32(-1.1f, 1), Complex32.Zero }, { Complex32.Zero, new Complex32(1.1f, 1) }, { Complex32.Zero, Complex32.Zero } } },
+                    {"Tall3x2", new[,] {{new Complex32(-1.1f, 1), Complex32.Zero}, {Complex32.Zero, new Complex32(1.1f, 1)}, {Complex32.Zero, Complex32.Zero}}},
-                             { "Wide2x3", new[,] { { new Complex32(-1.1f, 1), Complex32.Zero, Complex32.Zero }, { Complex32.Zero, new Complex32(1.1f, 1), Complex32.Zero } } }
+                    {"Wide2x3", new[,] {{new Complex32(-1.1f, 1), Complex32.Zero, Complex32.Zero}, {Complex32.Zero, new Complex32(1.1f, 1), Complex32.Zero}}}
-                         };
+                };
 
             TestMatrices = new Dictionary<string, Matrix>();
             foreach (var name in TestData2D.Keys)
@@ -114,13 +113,13 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         public void CanCreateMatrixFromDiagonalArray()
         {
             var testData = new Dictionary<string, Matrix>
-                           {
+                {
-                               { "Singular3x3", new DiagonalMatrix(3, 3, new[] { new Complex32(1.0f, 1), Complex32.Zero, new Complex32(3.0f, 1) }) },
+                    {"Singular3x3", new DiagonalMatrix(3, 3, new[] {new Complex32(1.0f, 1), Complex32.Zero, new Complex32(3.0f, 1)})},
-                               { "Square3x3", new DiagonalMatrix(3, 3, new[] { new Complex32(-1.1f, 1), new Complex32(1.1f, 1), new Complex32(6.6f, 1) }) },
+                    {"Square3x3", new DiagonalMatrix(3, 3, new[] {new Complex32(-1.1f, 1), new Complex32(1.1f, 1), new Complex32(6.6f, 1)})},
-                               { "Square4x4", new DiagonalMatrix(4, 4, new[] { new Complex32(-1.1f, 1), new Complex32(1.1f, 1), new Complex32(6.2f, 1), new Complex32(-7.7f, 1) }) },
+                    {"Square4x4", new DiagonalMatrix(4, 4, new[] {new Complex32(-1.1f, 1), new Complex32(1.1f, 1), new Complex32(6.2f, 1), new Complex32(-7.7f, 1)})},
-                               { "Tall3x2", new DiagonalMatrix(3, 2, new[] { new Complex32(-1.1f, 1), new Complex32(1.1f, 1) }) },
+                    {"Tall3x2", new DiagonalMatrix(3, 2, new[] {new Complex32(-1.1f, 1), new Complex32(1.1f, 1)})},
-                               { "Wide2x3", new DiagonalMatrix(2, 3, new[] { new Complex32(-1.1f, 1), new Complex32(1.1f, 1) }) },
+                    {"Wide2x3", new DiagonalMatrix(2, 3, new[] {new Complex32(-1.1f, 1), new Complex32(1.1f, 1)})},
-                           };
+                };
 
             foreach (var name in testData.Keys)
             {
@@ -134,7 +133,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         [Test]
         public void MatrixFrom1DArrayIsReference()
         {
-            var data = new[] { new Complex32(1.0f, 1), new Complex32(2.0f, 1), new Complex32(3.0f, 1), new Complex32(4.0f, 1), new Complex32(5.0f, 1) };
+            var data = new[] {new Complex32(1.0f, 1), new Complex32(2.0f, 1), new Complex32(3.0f, 1), new Complex32(4.0f, 1), new Complex32(5.0f, 1)};
             var matrix = new DiagonalMatrix(5, 5, data);
             matrix[0, 0] = new Complex32(10.0f, 1);
             Assert.AreEqual(new Complex32(10.0f, 1), data[0]);
@@ -221,7 +220,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
             {
                 for (var j = 0; j < matrixC.ColumnCount; j++)
                 {
-                    AssertHelpers.AlmostEqual(matrixA.Row(i) * matrixB.Column(j), matrixC[i, j], 15);
+                    AssertHelpers.AlmostEqual(matrixA.Row(i)*matrixB.Column(j), matrixC[i, j], 15);
                 }
             }
         }
@@ -233,7 +232,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         public void PermuteMatrixRowsThrowsInvalidOperationException()
         {
             var matrixp = CreateMatrix(TestData2D["Singular3x3"]);
-            var permutation = new Permutation(new[] { 2, 0, 1 });
+            var permutation = new Permutation(new[] {2, 0, 1});
             Assert.Throws<InvalidOperationException>(() => matrixp.PermuteRows(permutation));
         }
 
@@ -244,7 +243,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         public void PermuteMatrixColumnsThrowsInvalidOperationException()
         {
             var matrixp = CreateMatrix(TestData2D["Singular3x3"]);
-            var permutation = new Permutation(new[] { 2, 0, 1 });
+            var permutation = new Permutation(new[] {2, 0, 1});
             Assert.Throws<InvalidOperationException>(() => matrixp.PermuteColumns(permutation));
         }
 
@@ -261,13 +260,13 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
                 var min = Math.Min(data.RowCount, data.ColumnCount);
                 for (var i = 0; i < min; i++)
                 {
-                    Assert.AreEqual(data[i, i] / other[i, i], result[i, i]);
+                    Assert.AreEqual(data[i, i]/other[i, i], result[i, i]);
                 }
 
                 result = data.PointwiseDivide(other);
                 for (var i = 0; i < min; i++)
                 {
-                    Assert.AreEqual(data[i, i] / other[i, i], result[i, i]);
+                    Assert.AreEqual(data[i, i]/other[i, i], result[i, i]);
                 }
             }
         }
@@ -278,15 +277,15 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         public override void CanComputeFrobeniusNorm()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.FrobeniusNorm(), matrix.FrobeniusNorm(), 14);
 
             matrix = TestMatrices["Wide2x3"];
-            denseMatrix = new DenseMatrix(TestData2D["Wide2x3"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Wide2x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.FrobeniusNorm(), matrix.FrobeniusNorm(), 14);
 
             matrix = TestMatrices["Tall3x2"];
-            denseMatrix = new DenseMatrix(TestData2D["Tall3x2"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Tall3x2"]);
             AssertHelpers.AlmostEqual(denseMatrix.FrobeniusNorm(), matrix.FrobeniusNorm(), 14);
         }
 
@@ -296,15 +295,15 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         public override void CanComputeInfinityNorm()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.InfinityNorm(), matrix.InfinityNorm(), 14);
 
             matrix = TestMatrices["Wide2x3"];
-            denseMatrix = new DenseMatrix(TestData2D["Wide2x3"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Wide2x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.InfinityNorm(), matrix.InfinityNorm(), 14);
 
             matrix = TestMatrices["Tall3x2"];
-            denseMatrix = new DenseMatrix(TestData2D["Tall3x2"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Tall3x2"]);
             AssertHelpers.AlmostEqual(denseMatrix.InfinityNorm(), matrix.InfinityNorm(), 14);
         }
 
@@ -314,15 +313,15 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         public override void CanComputeL1Norm()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.L1Norm(), matrix.L1Norm(), 14);
 
             matrix = TestMatrices["Wide2x3"];
-            denseMatrix = new DenseMatrix(TestData2D["Wide2x3"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Wide2x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.L1Norm(), matrix.L1Norm(), 14);
 
             matrix = TestMatrices["Tall3x2"];
-            denseMatrix = new DenseMatrix(TestData2D["Tall3x2"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Tall3x2"]);
             AssertHelpers.AlmostEqual(denseMatrix.L1Norm(), matrix.L1Norm(), 14);
         }
 
@@ -332,15 +331,15 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         public override void CanComputeL2Norm()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.L2Norm(), matrix.L2Norm(), 14);
 
             matrix = TestMatrices["Wide2x3"];
-            denseMatrix = new DenseMatrix(TestData2D["Wide2x3"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Wide2x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.L2Norm(), matrix.L2Norm(), 14);
 
             matrix = TestMatrices["Tall3x2"];
-            denseMatrix = new DenseMatrix(TestData2D["Tall3x2"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Tall3x2"]);
             AssertHelpers.AlmostEqual(denseMatrix.L2Norm(), matrix.L2Norm(), 14);
         }
 
@@ -351,11 +350,11 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         public void CanComputeDeterminant()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.Determinant(), matrix.Determinant(), 14);
 
             matrix = TestMatrices["Square4x4"];
-            denseMatrix = new DenseMatrix(TestData2D["Square4x4"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Square4x4"]);
             AssertHelpers.AlmostEqual(denseMatrix.Determinant(), matrix.Determinant(), 14);
         }
 

src/UnitTests/LinearAlgebraTests/Complex32/IO/DelimitedWriterTests.cs

@@ -3,7 +3,9 @@
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
-// Copyright (c) 2009-2010 Math.NET
+//
+// Copyright (c) 2009-2013 Math.NET
+//
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
 // files (the "Software"), to deal in the Software without
@@ -12,8 +14,10 @@
 // copies of the Software, and to permit persons to whom the
 // Software is furnished to do so, subject to the following
 // conditions:
+//
 // The above copyright notice and this permission notice shall be
 // included in all copies or substantial portions of the Software.
+//
 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
@@ -26,12 +30,12 @@
 
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.IO
 {
-    using System;
-    using System.Globalization;
-    using System.IO;
     using LinearAlgebra.Complex32;
     using LinearAlgebra.IO;
     using NUnit.Framework;
+    using System;
+    using System.Globalization;
+    using System.IO;
     using Complex32 = Numerics.Complex32;
 
     /// <summary>
@@ -46,19 +50,19 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.IO
         [Test]
         public void CanWriteCommaDelimitedData()
         {
-            var matrix = new DenseMatrix(new[,] { { new Complex32(1.1f, 1.1f), new Complex32(2.2f, 2.2f), new Complex32(3.3f, 3.3f) }, { new Complex32(4.4f, 4.4f), new Complex32(5.5f, 5.5f), new Complex32(6.6f, 6.6f) }, { new Complex32(7.7f, 7.7f), new Complex32(8.8f, 8.8f), new Complex32(9.9f, 9.9f) } });
+            var matrix = DenseMatrix.OfArray(new[,] {{new Complex32(1.1f, 1.1f), new Complex32(2.2f, 2.2f), new Complex32(3.3f, 3.3f)}, {new Complex32(4.4f, 4.4f), new Complex32(5.5f, 5.5f), new Complex32(6.6f, 6.6f)}, {new Complex32(7.7f, 7.7f), new Complex32(8.8f, 8.8f), new Complex32(9.9f, 9.9f)}});
             var writer = new DelimitedWriter(',')
-                         {
+                {
-                             CultureInfo = CultureInfo.InvariantCulture
+                    CultureInfo = CultureInfo.InvariantCulture
-                         };
+                };
             var stream = new MemoryStream();
             writer.WriteMatrix(matrix, stream);
             var data = stream.ToArray();
             var reader = new StreamReader(new MemoryStream(data));
             var text = reader.ReadToEnd();
             var expected = "(1.1, 1.1),(2.2, 2.2),(3.3, 3.3)" + Environment.NewLine
-                           + "(4.4, 4.4),(5.5, 5.5),(6.6, 6.6)" + Environment.NewLine
+                + "(4.4, 4.4),(5.5, 5.5),(6.6, 6.6)" + Environment.NewLine
-                           + "(7.7, 7.7),(8.8, 8.8),(9.9, 9.9)";
+                + "(7.7, 7.7),(8.8, 8.8),(9.9, 9.9)";
             Assert.AreEqual(expected, text);
         }
 
@@ -68,20 +72,20 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.IO
         [Test]
         public void CanWritePeriodDelimitedData()
         {
-            var matrix = new DenseMatrix(new[,] { { new Complex32(1.1f, 1.1f), new Complex32(2.2f, 2.2f), new Complex32(3.3f, 3.3f) }, { new Complex32(4.4f, 4.4f), new Complex32(5.5f, 5.5f), new Complex32(6.6f, 6.6f) }, { new Complex32(7.7f, 7.7f), new Complex32(8.8f, 8.8f), new Complex32(9.9f, 9.9f) } });
+            var matrix = DenseMatrix.OfArray(new[,] {{new Complex32(1.1f, 1.1f), new Complex32(2.2f, 2.2f), new Complex32(3.3f, 3.3f)}, {new Complex32(4.4f, 4.4f), new Complex32(5.5f, 5.5f), new Complex32(6.6f, 6.6f)}, {new Complex32(7.7f, 7.7f), new Complex32(8.8f, 8.8f), new Complex32(9.9f, 9.9f)}});
             var culture = new CultureInfo("tr-TR");
             var writer = new DelimitedWriter('.')
-                         {
+                {
-                             CultureInfo = culture
+                    CultureInfo = culture
-                         };
+                };
             var stream = new MemoryStream();
             writer.WriteMatrix(matrix, stream);
             var data = stream.ToArray();
             var reader = new StreamReader(new MemoryStream(data));
             var text = reader.ReadToEnd();
             var expected = "(1,1, 1,1).(2,2, 2,2).(3,3, 3,3)" + Environment.NewLine
-                           + "(4,4, 4,4).(5,5, 5,5).(6,6, 6,6)" + Environment.NewLine
+                + "(4,4, 4,4).(5,5, 5,5).(6,6, 6,6)" + Environment.NewLine
-                           + "(7,7, 7,7).(8,8, 8,8).(9,9, 9,9)";
+                + "(7,7, 7,7).(8,8, 8,8).(9,9, 9,9)";
             Assert.AreEqual(expected, text);
         }
 
@@ -91,19 +95,19 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.IO
         [Test]
         public void CanWriteSpaceDelimitedData()
         {
-            var matrix = new DenseMatrix(new[,] { { new Complex32(1.1f, 1.1f), new Complex32(2.2f, 2.2f), new Complex32(3.3f, 3.3f) }, { new Complex32(4.4f, 4.4f), new Complex32(5.5f, 5.5f), new Complex32(6.6f, 6.6f) }, { new Complex32(7.7f, 7.7f), new Complex32(8.8f, 8.8f), new Complex32(9.9f, 9.9f) } });
+            var matrix = DenseMatrix.OfArray(new[,] {{new Complex32(1.1f, 1.1f), new Complex32(2.2f, 2.2f), new Complex32(3.3f, 3.3f)}, {new Complex32(4.4f, 4.4f), new Complex32(5.5f, 5.5f), new Complex32(6.6f, 6.6f)}, {new Complex32(7.7f, 7.7f), new Complex32(8.8f, 8.8f), new Complex32(9.9f, 9.9f)}});
             var writer = new DelimitedWriter(' ')
-                         {
+                {
-                             CultureInfo = CultureInfo.InvariantCulture
+                    CultureInfo = CultureInfo.InvariantCulture
-                         };
+                };
             var stream = new MemoryStream();
             writer.WriteMatrix(matrix, stream);
             var data = stream.ToArray();
             var reader = new StreamReader(new MemoryStream(data));
             var text = reader.ReadToEnd();
             var expected = "(1.1, 1.1) (2.2, 2.2) (3.3, 3.3)" + Environment.NewLine
-                           + "(4.4, 4.4) (5.5, 5.5) (6.6, 6.6)" + Environment.NewLine
+                + "(4.4, 4.4) (5.5, 5.5) (6.6, 6.6)" + Environment.NewLine
-                           + "(7.7, 7.7) (8.8, 8.8) (9.9, 9.9)";
+                + "(7.7, 7.7) (8.8, 8.8) (9.9, 9.9)";
             Assert.AreEqual(expected, text);
         }
 
@@ -113,22 +117,22 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32.IO
         [Test]
         public void CanWriteTabDelimitedData()
         {
-            var matrix = new DenseMatrix(new[,] { { new Complex32(1.1f, 1.1f), new Complex32(2.2f, 2.2f), new Complex32(3.3f, 3.3f) }, { new Complex32(4.4f, 4.4f), new Complex32(5.5f, 5.5f), new Complex32(6.6f, 6.6f) }, { new Complex32(7.7f, 7.7f), new Complex32(8.8f, 8.8f), new Complex32(9.9f, 9.9f) } });
+            var matrix = DenseMatrix.OfArray(new[,] {{new Complex32(1.1f, 1.1f), new Complex32(2.2f, 2.2f), new Complex32(3.3f, 3.3f)}, {new Complex32(4.4f, 4.4f), new Complex32(5.5f, 5.5f), new Complex32(6.6f, 6.6f)}, {new Complex32(7.7f, 7.7f), new Complex32(8.8f, 8.8f), new Complex32(9.9f, 9.9f)}});
-            var headers = new[] { "a", "b", "c" };
+            var headers = new[] {"a", "b", "c"};
             var writer = new DelimitedWriter('\t')
-                         {
+                {
-                             ColumnHeaders = headers,
+                    ColumnHeaders = headers,
-                             CultureInfo = CultureInfo.InvariantCulture
+                    CultureInfo = CultureInfo.InvariantCulture
-                         };
+                };
             var stream = new MemoryStream();
             writer.WriteMatrix(matrix, stream);
             var data = stream.ToArray();
             var reader = new StreamReader(new MemoryStream(data));
             var text = reader.ReadToEnd();
             var expected = "a\tb\tc" + Environment.NewLine
-                           + "(1.1, 1.1)\t(2.2, 2.2)\t(3.3, 3.3)" + Environment.NewLine
+                + "(1.1, 1.1)\t(2.2, 2.2)\t(3.3, 3.3)" + Environment.NewLine
-                           + "(4.4, 4.4)\t(5.5, 5.5)\t(6.6, 6.6)" + Environment.NewLine
+                + "(4.4, 4.4)\t(5.5, 5.5)\t(6.6, 6.6)" + Environment.NewLine
-                           + "(7.7, 7.7)\t(8.8, 8.8)\t(9.9, 9.9)";
+                + "(7.7, 7.7)\t(8.8, 8.8)\t(9.9, 9.9)";
             Assert.AreEqual(expected, text);
         }
     }

src/UnitTests/LinearAlgebraTests/Complex32/MatrixStructureTheory.cs

@@ -1,12 +1,41 @@
-using System.Linq;
+// <copyright file="MatrixStructureTheory.cs" company="Math.NET">
-using MathNet.Numerics.Distributions;
+// Math.NET Numerics, part of the Math.NET Project
-using MathNet.Numerics.Random;
+// http://numerics.mathdotnet.com
+// http://github.com/mathnet/mathnet-numerics
+// http://mathnetnumerics.codeplex.com
+//
+// Copyright (c) 2009-2013 Math.NET
+//
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+//
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+//
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
 
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
 {
+    using Distributions;
     using LinearAlgebra.Complex32;
     using LinearAlgebra.Generic;
+    using Numerics.Random;
     using NUnit.Framework;
+    using System.Linq;
     using Complex32 = Numerics.Complex32;
 
     [TestFixture]
@@ -15,17 +44,17 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         [Datapoints]
         Matrix<Complex32>[] _matrices = new Matrix<Complex32>[]
             {
-                new DenseMatrix(new[,] {{1f, new Complex32(1.1f, -4f), 2f}, {1f, 1f, 2f}, {1f, new Complex32(1f, 2f), 2f}}),
+                DenseMatrix.OfArray(new[,] {{1f, new Complex32(1.1f, -4f), 2f}, {1f, 1f, 2f}, {1f, new Complex32(1f, 2f), 2f}}),
-                new DenseMatrix(new[,] {{-1.1f, -2.2f, -3.3f}, {0f, 1.1f, new Complex32(2.2f, -1.2f)}, {-4.4f, 5.5f, 6.6f}}),
+                DenseMatrix.OfArray(new[,] {{-1.1f, -2.2f, -3.3f}, {0f, 1.1f, new Complex32(2.2f, -1.2f)}, {-4.4f, 5.5f, 6.6f}}),
-                new DenseMatrix(new[,] {{new Complex32(-1.1f, -2f), -2.2f, -3.3f, -4.4f}, {0f, 1.1f, 2.2f, 3.3f}, {1f, 2.1f, 6.2f, 4.3f}, {-4.4f, 5.5f, 6.6f, -7.7f}}),
+                DenseMatrix.OfArray(new[,] {{new Complex32(-1.1f, -2f), -2.2f, -3.3f, -4.4f}, {0f, 1.1f, 2.2f, 3.3f}, {1f, 2.1f, 6.2f, 4.3f}, {-4.4f, 5.5f, 6.6f, -7.7f}}),
-                new DenseMatrix(new[,] {{-1.1f, new Complex32(-2.2f, 3.4f), -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}}),
+                DenseMatrix.OfArray(new[,] {{-1.1f, new Complex32(-2.2f, 3.4f), -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}}),
-                new DenseMatrix(new[,] {{-1.1f, -2.2f}, {Complex32.Zero, 1.1f}, {-4.4f, 5.5f}}),
+                DenseMatrix.OfArray(new[,] {{-1.1f, -2.2f}, {Complex32.Zero, 1.1f}, {-4.4f, 5.5f}}),
-                new DenseMatrix(new[,] {{-1.1f, -2.2f, -3.3f}, {0f, new Complex32(1.1f, 0.1f), 2.2f}}),
+                DenseMatrix.OfArray(new[,] {{-1.1f, -2.2f, -3.3f}, {0f, new Complex32(1.1f, 0.1f), 2.2f}}),
-                new DenseMatrix(new[,] {{1f, 2f, 3f}, {2f, new Complex32(2f, 2f), 0f}, {3f, Complex32.Zero, 3f}}),
+                DenseMatrix.OfArray(new[,] {{1f, 2f, 3f}, {2f, new Complex32(2f, 2f), 0f}, {3f, Complex32.Zero, 3f}}),
 
-                new SparseMatrix(new[,] {{7f, 1f, 2f}, {1f, 1f, 2f}, {1f, 1f + Complex32.ImaginaryOne, 2f}}),
+                SparseMatrix.OfArray(new[,] {{7f, 1f, 2f}, {1f, 1f, 2f}, {1f, 1f + Complex32.ImaginaryOne, 2f}}),
-                new SparseMatrix(new[,] {{7f, 1f, 2f}, {new Complex32(1f, 2f), 0f, Complex32.Zero}, {-2f, 0f, 0f}}),
+                SparseMatrix.OfArray(new[,] {{7f, 1f, 2f}, {new Complex32(1f, 2f), 0f, Complex32.Zero}, {-2f, 0f, 0f}}),
-                new SparseMatrix(new[,] {{-1.1f, 0f, 0f}, {0f, new Complex32(1.1f, 2f), 2.2f}}),
+                SparseMatrix.OfArray(new[,] {{-1.1f, 0f, 0f}, {0f, new Complex32(1.1f, 2f), 2.2f}}),
 
                 new DiagonalMatrix(3, 3, new[] {new Complex32(1f, 1f), -2f, 1.5f}),
                 new DiagonalMatrix(3, 3, new[] {new Complex32(1f, 2f), 0f, -1.5f}),
@@ -68,4 +97,4 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
             get { return Complex32.Zero; }
         }
     }
-}
+}

src/UnitTests/LinearAlgebraTests/Complex32/SparseMatrixTests.cs

@@ -3,7 +3,9 @@
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
-// Copyright (c) 2009-2010 Math.NET
+//
+// Copyright (c) 2009-2013 Math.NET
+//
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
 // files (the "Software"), to deal in the Software without
@@ -12,8 +14,10 @@
 // copies of the Software, and to permit persons to whom the
 // Software is furnished to do so, subject to the following
 // conditions:
+//
 // The above copyright notice and this permission notice shall be
 // included in all copies or substantial portions of the Software.
+//
 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
@@ -26,10 +30,10 @@
 
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
 {
-    using System;
-    using System.Collections.Generic;
     using LinearAlgebra.Complex32;
     using NUnit.Framework;
+    using System;
+    using System.Collections.Generic;
     using Complex32 = Numerics.Complex32;
 
     /// <summary>
@@ -55,7 +59,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         /// <returns>A matrix with the given values.</returns>
         protected override Matrix CreateMatrix(Complex32[,] data)
         {
-            return new SparseMatrix(data);
+            return SparseMatrix.OfArray(data);
         }
 
         /// <summary>
@@ -86,13 +90,13 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         public void CanCreateMatrixFrom1DArray()
         {
             var testData = new Dictionary<string, Matrix>
-                           {
+                {
-                               { "Singular3x3", new SparseMatrix(3, 3, new[] { new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(2.0f, 1), new Complex32(2.0f, 1), new Complex32(2.0f, 1) }) },
+                    {"Singular3x3", SparseMatrix.OfColumnMajor(3, 3, new[] {new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(2.0f, 1), new Complex32(2.0f, 1), new Complex32(2.0f, 1)})},
-                               { "Square3x3", new SparseMatrix(3, 3, new[] { new Complex32(-1.1f, 1), Complex32.Zero, new Complex32(-4.4f, 1), new Complex32(-2.2f, 1), new Complex32(1.1f, 1), new Complex32(5.5f, 1), new Complex32(-3.3f, 1), new Complex32(2.2f, 1), new Complex32(6.6f, 1) }) },
+                    {"Square3x3", SparseMatrix.OfColumnMajor(3, 3, new[] {new Complex32(-1.1f, 1), Complex32.Zero, new Complex32(-4.4f, 1), new Complex32(-2.2f, 1), new Complex32(1.1f, 1), new Complex32(5.5f, 1), new Complex32(-3.3f, 1), new Complex32(2.2f, 1), new Complex32(6.6f, 1)})},
-                               { "Square4x4", new SparseMatrix(4, 4, new[] { new Complex32(-1.1f, 1), Complex32.Zero, new Complex32(1.0f, 1), new Complex32(-4.4f, 1), new Complex32(-2.2f, 1), new Complex32(1.1f, 1), new Complex32(2.1f, 1), new Complex32(5.5f, 1), new Complex32(-3.3f, 1), new Complex32(2.2f, 1), new Complex32(6.2f, 1), new Complex32(6.6f, 1), new Complex32(-4.4f, 1), new Complex32(3.3f, 1), new Complex32(4.3f, 1), new Complex32(-7.7f, 1) }) },
+                    {"Square4x4", SparseMatrix.OfColumnMajor(4, 4, new[] {new Complex32(-1.1f, 1), Complex32.Zero, new Complex32(1.0f, 1), new Complex32(-4.4f, 1), new Complex32(-2.2f, 1), new Complex32(1.1f, 1), new Complex32(2.1f, 1), new Complex32(5.5f, 1), new Complex32(-3.3f, 1), new Complex32(2.2f, 1), new Complex32(6.2f, 1), new Complex32(6.6f, 1), new Complex32(-4.4f, 1), new Complex32(3.3f, 1), new Complex32(4.3f, 1), new Complex32(-7.7f, 1)})},
-                               { "Tall3x2", new SparseMatrix(3, 2, new[] { new Complex32(-1.1f, 1), Complex32.Zero, new Complex32(-4.4f, 1), new Complex32(-2.2f, 1), new Complex32(1.1f, 1), new Complex32(5.5f, 1) }) },
+                    {"Tall3x2", SparseMatrix.OfColumnMajor(3, 2, new[] {new Complex32(-1.1f, 1), Complex32.Zero, new Complex32(-4.4f, 1), new Complex32(-2.2f, 1), new Complex32(1.1f, 1), new Complex32(5.5f, 1)})},
-                               { "Wide2x3", new SparseMatrix(2, 3, new[] { new Complex32(-1.1f, 1), Complex32.Zero, new Complex32(-2.2f, 1), new Complex32(1.1f, 1), new Complex32(-3.3f, 1), new Complex32(2.2f, 1) }) }
+                    {"Wide2x3", SparseMatrix.OfColumnMajor(2, 3, new[] {new Complex32(-1.1f, 1), Complex32.Zero, new Complex32(-2.2f, 1), new Complex32(1.1f, 1), new Complex32(-3.3f, 1), new Complex32(2.2f, 1)})}
-                           };
+                };
 
             foreach (var name in testData.Keys)
             {
@@ -107,8 +111,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         public void MatrixFrom1DArrayIsCopy()
         {
             // Sparse Matrix copies values from Complex32[], but no remember reference. 
-            var data = new[] { new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(2.0f, 1), new Complex32(2.0f, 1), new Complex32(2.0f, 1) };
+            var data = new[] {new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(1.0f, 1), new Complex32(2.0f, 1), new Complex32(2.0f, 1), new Complex32(2.0f, 1)};
-            var matrix = new SparseMatrix(3, 3, data);
+            var matrix = SparseMatrix.OfColumnMajor(3, 3, data);
             matrix[0, 0] = new Complex32(10.0f, 1);
             Assert.AreNotEqual(new Complex32(10.0f, 1), data[0]);
         }
@@ -119,7 +123,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         [Test]
         public void MatrixFrom2DArrayIsCopy()
         {
-            var matrix = new SparseMatrix(TestData2D["Singular3x3"]);
+            var matrix = SparseMatrix.OfArray(TestData2D["Singular3x3"]);
             matrix[0, 0] = new Complex32(10.0f, 1);
             Assert.AreEqual(new Complex32(1.0f, 1), TestData2D["Singular3x3"][0, 0]);
         }
@@ -136,7 +140,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         [TestCase("Wide2x3")]
         public void CanCreateMatrixFrom2DArray(string name)
         {
-            var matrix = new SparseMatrix(TestData2D[name]);
+            var matrix = SparseMatrix.OfArray(TestData2D[name]);
             for (var i = 0; i < TestData2D[name].GetLength(0); i++)
             {
                 for (var j = 0; j < TestData2D[name].GetLength(1); j++)
@@ -187,7 +191,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
             {
                 for (var j = 0; j < matrix.ColumnCount; j++)
                 {
-                    var value = rnd.Next(10) * rnd.Next(10) * rnd.Next(10) * rnd.Next(10) * rnd.Next(10);
+                    var value = rnd.Next(10)*rnd.Next(10)*rnd.Next(10)*rnd.Next(10)*rnd.Next(10);
                     if (value != 0)
                     {
                         nonzero++;
@@ -207,7 +211,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         public void CanAddSparseMatricesBothWays()
         {
             var m1 = new SparseMatrix(1, 3);
-            var m2 = new SparseMatrix(new Complex32[,] { { 0, 1, 1 } });
+            var m2 = SparseMatrix.OfArray(new Complex32[,] { { 0, 1, 1 } });
             var sum1 = m1 + m2;
             var sum2 = m2 + m1;
             Assert.IsTrue(sum1.Equals(m2));
@@ -217,27 +221,27 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
             sparseResult.Add(m2, sparseResult);
             Assert.IsTrue(sparseResult.Equals(sum1));
 
-            sparseResult = new SparseMatrix(new Complex32[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new Complex32[,] { { 0, 1, 1 } });
             sparseResult.Add(m1, sparseResult);
             Assert.IsTrue(sparseResult.Equals(sum1));
 
-            sparseResult = new SparseMatrix(new Complex32[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new Complex32[,] { { 0, 1, 1 } });
             m1.Add(sparseResult, sparseResult);
             Assert.IsTrue(sparseResult.Equals(sum1));
 
-            sparseResult = new SparseMatrix(new Complex32[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new Complex32[,] { { 0, 1, 1 } });
             sparseResult.Add(sparseResult, sparseResult);
-            Assert.IsTrue(sparseResult.Equals(2 * sum1));
+            Assert.IsTrue(sparseResult.Equals(2*sum1));
 
             var denseResult = new DenseMatrix(1, 3);
             denseResult.Add(m2, denseResult);
             Assert.IsTrue(denseResult.Equals(sum1));
 
-            denseResult = new DenseMatrix(new Complex32[,] { { 0, 1, 1 } });
+            denseResult = DenseMatrix.OfArray(new Complex32[,] {{0, 1, 1}});
             denseResult.Add(m1, denseResult);
             Assert.IsTrue(denseResult.Equals(sum1));
 
-            var m3 = new DenseMatrix(new Complex32[,] { { 0, 1, 1 } });
+            var m3 = DenseMatrix.OfArray(new Complex32[,] {{0, 1, 1}});
             var sum3 = m1 + m3;
             var sum4 = m3 + m1;
             Assert.IsTrue(sum3.Equals(m3));
@@ -251,7 +255,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
         public void CanSubtractSparseMatricesBothWays()
         {
             var m1 = new SparseMatrix(1, 3);
-            var m2 = new SparseMatrix(new Complex32[,] { { 0, 1, 1 } });
+            var m2 = SparseMatrix.OfArray(new Complex32[,] { { 0, 1, 1 } });
             var diff1 = m1 - m2;
             var diff2 = m2 - m1;
             Assert.IsTrue(diff1.Equals(m2.Negate()));
@@ -261,27 +265,27 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
             sparseResult.Subtract(m2, sparseResult);
             Assert.IsTrue(sparseResult.Equals(diff1));
 
-            sparseResult = new SparseMatrix(new Complex32[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new Complex32[,] { { 0, 1, 1 } });
             sparseResult.Subtract(m1, sparseResult);
             Assert.IsTrue(sparseResult.Equals(diff2));
 
-            sparseResult = new SparseMatrix(new Complex32[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new Complex32[,] { { 0, 1, 1 } });
             m1.Subtract(sparseResult, sparseResult);
             Assert.IsTrue(sparseResult.Equals(diff1));
 
-            sparseResult = new SparseMatrix(new Complex32[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new Complex32[,] { { 0, 1, 1 } });
             sparseResult.Subtract(sparseResult, sparseResult);
-            Assert.IsTrue(sparseResult.Equals(0 * diff1));
+            Assert.IsTrue(sparseResult.Equals(0*diff1));
 
             var denseResult = new DenseMatrix(1, 3);
             denseResult.Subtract(m2, denseResult);
             Assert.IsTrue(denseResult.Equals(diff1));
 
-            denseResult = new DenseMatrix(new Complex32[,] { { 0, 1, 1 } });
+            denseResult = DenseMatrix.OfArray(new Complex32[,] {{0, 1, 1}});
             denseResult.Subtract(m1, denseResult);
             Assert.IsTrue(denseResult.Equals(diff2));
 
-            var m3 = new DenseMatrix(new Complex32[,] { { 0, 1, 1 } });
+            var m3 = DenseMatrix.OfArray(new Complex32[,] {{0, 1, 1}});
             var diff3 = m1 - m3;
             var diff4 = m3 - m1;
             Assert.IsTrue(diff3.Equals(m3.Negate()));

src/UnitTests/LinearAlgebraTests/Double/DenseMatrixTests.cs

@@ -3,7 +3,9 @@
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
-// Copyright (c) 2009-2010 Math.NET
+//
+// Copyright (c) 2009-2013 Math.NET
+//
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
 // files (the "Software"), to deal in the Software without
@@ -12,8 +14,10 @@
 // copies of the Software, and to permit persons to whom the
 // Software is furnished to do so, subject to the following
 // conditions:
+//
 // The above copyright notice and this permission notice shall be
 // included in all copies or substantial portions of the Software.
+//
 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
@@ -54,7 +58,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         /// <returns>A matrix with the given values.</returns>
         protected override Matrix CreateMatrix(double[,] data)
         {
-            return new DenseMatrix(data);
+            return DenseMatrix.OfArray(data);
         }
 
         /// <summary>
@@ -85,13 +89,13 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         public void CanCreateMatrixFrom1DArray()
         {
             var testData = new Dictionary<string, Matrix>
-                           {
+                {
-                               { "Singular3x3", new DenseMatrix(3, 3, new[] { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 2.0, 2.0, 2.0 }) },
+                    {"Singular3x3", new DenseMatrix(3, 3, new[] {1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 2.0, 2.0, 2.0})},
-                               { "Square3x3", new DenseMatrix(3, 3, new[] { -1.1, 0.0, -4.4, -2.2, 1.1, 5.5, -3.3, 2.2, 6.6 }) },
+                    {"Square3x3", new DenseMatrix(3, 3, new[] {-1.1, 0.0, -4.4, -2.2, 1.1, 5.5, -3.3, 2.2, 6.6})},
-                               { "Square4x4", new DenseMatrix(4, 4, new[] { -1.1, 0.0, 1.0, -4.4, -2.2, 1.1, 2.1, 5.5, -3.3, 2.2, 6.2, 6.6, -4.4, 3.3, 4.3, -7.7 }) },
+                    {"Square4x4", new DenseMatrix(4, 4, new[] {-1.1, 0.0, 1.0, -4.4, -2.2, 1.1, 2.1, 5.5, -3.3, 2.2, 6.2, 6.6, -4.4, 3.3, 4.3, -7.7})},
-                               { "Tall3x2", new DenseMatrix(3, 2, new[] { -1.1, 0.0, -4.4, -2.2, 1.1, 5.5 }) },
+                    {"Tall3x2", new DenseMatrix(3, 2, new[] {-1.1, 0.0, -4.4, -2.2, 1.1, 5.5})},
-                               { "Wide2x3", new DenseMatrix(2, 3, new[] { -1.1, 0.0, -2.2, 1.1, -3.3, 2.2 }) }
+                    {"Wide2x3", new DenseMatrix(2, 3, new[] {-1.1, 0.0, -2.2, 1.1, -3.3, 2.2})}
-                           };
+                };
 
             foreach (var name in testData.Keys)
             {
@@ -105,7 +109,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         [Test]
         public void MatrixFrom1DArrayIsReference()
         {
-            var data = new double[] { 1, 1, 1, 1, 1, 1, 2, 2, 2 };
+            var data = new double[] {1, 1, 1, 1, 1, 1, 2, 2, 2};
             var matrix = new DenseMatrix(3, 3, data);
             matrix[0, 0] = 10.0;
             Assert.AreEqual(10.0, data[0]);
@@ -117,7 +121,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         [Test]
         public void MatrixFrom2DArrayIsCopy()
         {
-            var matrix = new DenseMatrix(TestData2D["Singular3x3"]);
+            var matrix = DenseMatrix.OfArray(TestData2D["Singular3x3"]);
             matrix[0, 0] = 10.0;
             Assert.AreEqual(1.0, TestData2D["Singular3x3"][0, 0]);
         }
@@ -134,7 +138,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         [TestCase("Wide2x3")]
         public void CanCreateMatrixFrom2DArray(string name)
         {
-            var matrix = new DenseMatrix(TestData2D[name]);
+            var matrix = DenseMatrix.OfArray(TestData2D[name]);
             for (var i = 0; i < TestData2D[name].GetLength(0); i++)
             {
                 for (var j = 0; j < TestData2D[name].GetLength(1); j++)

src/UnitTests/LinearAlgebraTests/Double/DiagonalMatrixTests.cs

@@ -3,7 +3,9 @@
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
-// Copyright (c) 2009-2010 Math.NET
+//
+// Copyright (c) 2009-2013 Math.NET
+//
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
 // files (the "Software"), to deal in the Software without
@@ -12,8 +14,10 @@
 // copies of the Software, and to permit persons to whom the
 // Software is furnished to do so, subject to the following
 // conditions:
+//
 // The above copyright notice and this permission notice shall be
 // included in all copies or substantial portions of the Software.
+//
 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
@@ -23,19 +27,13 @@
 // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
 // OTHER DEALINGS IN THE SOFTWARE.
 // </copyright>
-
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
 {
-    using System;
-    using System.Collections.Generic;
-    using System.Linq;
     using LinearAlgebra.Double;
     using LinearAlgebra.Generic;
     using NUnit.Framework;
-
+    using System;
-#if PORTABLE
+    using System.Collections.Generic;
-    using Threading;
-#endif
 
     /// <summary>
     /// Diagonal matrix tests.
@@ -49,14 +47,14 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         public override void SetupMatrices()
         {
             TestData2D = new Dictionary<string, double[,]>
-                         {
+                {
-                             { "Singular3x3", new[,] { { 1.0, 0.0, 0.0 }, { 0.0, 0.0, 0.0 }, { 0.0, 0.0, 3.0 } } },
+                    {"Singular3x3", new[,] {{1.0, 0.0, 0.0}, {0.0, 0.0, 0.0}, {0.0, 0.0, 3.0}}},
-                             { "Square3x3", new[,] { { -1.1, 0.0, 0.0 }, { 0.0, 1.1, 0.0 }, { 0.0, 0.0, 6.6 } } },
+                    {"Square3x3", new[,] {{-1.1, 0.0, 0.0}, {0.0, 1.1, 0.0}, {0.0, 0.0, 6.6}}},
-                             { "Square4x4", new[,] { { -1.1, 0.0, 0.0, 0.0 }, { 0.0, 1.1, 0.0, 0.0 }, { 0.0, 0.0, 6.2, 0.0 }, { 0.0, 0.0, 0.0, -7.7 } } },
+                    {"Square4x4", new[,] {{-1.1, 0.0, 0.0, 0.0}, {0.0, 1.1, 0.0, 0.0}, {0.0, 0.0, 6.2, 0.0}, {0.0, 0.0, 0.0, -7.7}}},
-                             { "Singular4x4", new[,] { { -1.1, 0.0, 0.0, 0.0 }, { 0.0, -2.2, 0.0, 0.0 }, { 0.0, 0.0, 0.0, 0.0 }, { 0.0, 0.0, 0.0, -4.4 } } },
+                    {"Singular4x4", new[,] {{-1.1, 0.0, 0.0, 0.0}, {0.0, -2.2, 0.0, 0.0}, {0.0, 0.0, 0.0, 0.0}, {0.0, 0.0, 0.0, -4.4}}},
-                             { "Tall3x2", new[,] { { -1.1, 0.0 }, { 0.0, 1.1 }, { 0.0, 0.0 } } },
+                    {"Tall3x2", new[,] {{-1.1, 0.0}, {0.0, 1.1}, {0.0, 0.0}}},
-                             { "Wide2x3", new[,] { { -1.1, 0.0, 0.0 }, { 0.0, 1.1, 0.0 } } }
+                    {"Wide2x3", new[,] {{-1.1, 0.0, 0.0}, {0.0, 1.1, 0.0}}}
-                         };
+                };
 
             TestMatrices = new Dictionary<string, Matrix>();
             foreach (var name in TestData2D.Keys)
@@ -114,13 +112,13 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         public void CanCreateMatrixFromDiagonalArray()
         {
             var testData = new Dictionary<string, Matrix<double>>
-                           {
+                {
-                               { "Singular3x3", new DiagonalMatrix(3, 3, new[] { 1.0, 0.0, 3.0 }) },
+                    {"Singular3x3", new DiagonalMatrix(3, 3, new[] {1.0, 0.0, 3.0})},
-                               { "Square3x3", new DiagonalMatrix(3, 3, new[] { -1.1, 1.1, 6.6 }) },
+                    {"Square3x3", new DiagonalMatrix(3, 3, new[] {-1.1, 1.1, 6.6})},
-                               { "Square4x4", new DiagonalMatrix(4, 4, new[] { -1.1, 1.1, 6.2, -7.7 }) },
+                    {"Square4x4", new DiagonalMatrix(4, 4, new[] {-1.1, 1.1, 6.2, -7.7})},
-                               { "Tall3x2", new DiagonalMatrix(3, 2, new[] { -1.1, 1.1 }) },
+                    {"Tall3x2", new DiagonalMatrix(3, 2, new[] {-1.1, 1.1})},
-                               { "Wide2x3", new DiagonalMatrix(2, 3, new[] { -1.1, 1.1 }) },
+                    {"Wide2x3", new DiagonalMatrix(2, 3, new[] {-1.1, 1.1})},
-                           };
+                };
 
             foreach (var name in testData.Keys)
             {
@@ -134,7 +132,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         [Test]
         public void MatrixFrom1DArrayIsReference()
         {
-            var data = new double[] { 1, 2, 3, 4, 5 };
+            var data = new double[] {1, 2, 3, 4, 5};
             var matrix = new DiagonalMatrix(5, 5, data);
             matrix[0, 0] = 10.0;
             Assert.AreEqual(10.0, data[0]);
@@ -221,7 +219,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
             {
                 for (var j = 0; j < matrixC.ColumnCount; j++)
                 {
-                    AssertHelpers.AlmostEqual(matrixA.Row(i) * matrixB.Column(j), matrixC[i, j], 15);
+                    AssertHelpers.AlmostEqual(matrixA.Row(i)*matrixB.Column(j), matrixC[i, j], 15);
                 }
             }
         }
@@ -233,7 +231,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         public void PermuteMatrixRowsThrowsInvalidOperationException()
         {
             var matrixp = CreateMatrix(TestData2D["Singular3x3"]);
-            var permutation = new Permutation(new[] { 2, 0, 1 });
+            var permutation = new Permutation(new[] {2, 0, 1});
             Assert.Throws<InvalidOperationException>(() => matrixp.PermuteRows(permutation));
         }
 
@@ -244,7 +242,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         public void PermuteMatrixColumnsThrowsInvalidOperationException()
         {
             var matrixp = CreateMatrix(TestData2D["Singular3x3"]);
-            var permutation = new Permutation(new[] { 2, 0, 1 });
+            var permutation = new Permutation(new[] {2, 0, 1});
             Assert.Throws<InvalidOperationException>(() => matrixp.PermuteColumns(permutation));
         }
 
@@ -261,13 +259,13 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
                 var min = Math.Min(data.RowCount, data.ColumnCount);
                 for (var i = 0; i < min; i++)
                 {
-                    Assert.AreEqual(data[i, i] / other[i, i], result[i, i]);
+                    Assert.AreEqual(data[i, i]/other[i, i], result[i, i]);
                 }
 
                 result = data.PointwiseDivide(other);
                 for (var i = 0; i < min; i++)
                 {
-                    Assert.AreEqual(data[i, i] / other[i, i], result[i, i]);
+                    Assert.AreEqual(data[i, i]/other[i, i], result[i, i]);
                 }
             }
         }
@@ -278,15 +276,15 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         public override void CanComputeFrobeniusNorm()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.FrobeniusNorm(), matrix.FrobeniusNorm(), 14);
 
             matrix = TestMatrices["Wide2x3"];
-            denseMatrix = new DenseMatrix(TestData2D["Wide2x3"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Wide2x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.FrobeniusNorm(), matrix.FrobeniusNorm(), 14);
 
             matrix = TestMatrices["Tall3x2"];
-            denseMatrix = new DenseMatrix(TestData2D["Tall3x2"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Tall3x2"]);
             AssertHelpers.AlmostEqual(denseMatrix.FrobeniusNorm(), matrix.FrobeniusNorm(), 14);
         }
 
@@ -296,15 +294,15 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         public override void CanComputeInfinityNorm()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.InfinityNorm(), matrix.InfinityNorm(), 14);
 
             matrix = TestMatrices["Wide2x3"];
-            denseMatrix = new DenseMatrix(TestData2D["Wide2x3"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Wide2x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.InfinityNorm(), matrix.InfinityNorm(), 14);
 
             matrix = TestMatrices["Tall3x2"];
-            denseMatrix = new DenseMatrix(TestData2D["Tall3x2"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Tall3x2"]);
             AssertHelpers.AlmostEqual(denseMatrix.InfinityNorm(), matrix.InfinityNorm(), 14);
         }
 
@@ -314,15 +312,15 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         public override void CanComputeL1Norm()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.L1Norm(), matrix.L1Norm(), 14);
 
             matrix = TestMatrices["Wide2x3"];
-            denseMatrix = new DenseMatrix(TestData2D["Wide2x3"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Wide2x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.L1Norm(), matrix.L1Norm(), 14);
 
             matrix = TestMatrices["Tall3x2"];
-            denseMatrix = new DenseMatrix(TestData2D["Tall3x2"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Tall3x2"]);
             AssertHelpers.AlmostEqual(denseMatrix.L1Norm(), matrix.L1Norm(), 14);
         }
 
@@ -332,15 +330,15 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         public override void CanComputeL2Norm()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.L2Norm(), matrix.L2Norm(), 14);
 
             matrix = TestMatrices["Wide2x3"];
-            denseMatrix = new DenseMatrix(TestData2D["Wide2x3"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Wide2x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.L2Norm(), matrix.L2Norm(), 14);
 
             matrix = TestMatrices["Tall3x2"];
-            denseMatrix = new DenseMatrix(TestData2D["Tall3x2"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Tall3x2"]);
             AssertHelpers.AlmostEqual(denseMatrix.L2Norm(), matrix.L2Norm(), 14);
         }
 
@@ -351,11 +349,11 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         public void CanComputeDeterminant()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.Determinant(), matrix.Determinant(), 14);
 
             matrix = TestMatrices["Square4x4"];
-            denseMatrix = new DenseMatrix(TestData2D["Square4x4"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Square4x4"]);
             AssertHelpers.AlmostEqual(denseMatrix.Determinant(), matrix.Determinant(), 14);
         }
 
@@ -400,16 +398,16 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
             // [ 2 0 ]
             // [ 0 3 ]
             var subM3 = diagMatrix.SubMatrix(0, 3, 1, 2);
-            Assert.IsTrue(subM3.Equals(new DenseMatrix(3, 2, new[] { 0d, 2d, 0d, 0d, 0d, 3d })));
+            Assert.IsTrue(subM3.Equals(new DenseMatrix(3, 2, new[] {0d, 2d, 0d, 0d, 0d, 3d})));
         }
 
         [Test]
         public void DiagonalDenseMatrixMultiplication_IssueCP5706()
         {
             Matrix<double> diagonal = DiagonalMatrix.Identity(3);
-            Matrix<double> dense = new DenseMatrix(new double[,] { { 1, 2, 3 }, { 1, 2, 3 }, { 1, 2, 3 } });
+            Matrix<double> dense = DenseMatrix.OfArray(new double[,] {{1, 2, 3}, {1, 2, 3}, {1, 2, 3}});
-            var test = diagonal * dense;
+            var test = diagonal*dense;
-            var test2 = dense * diagonal;
+            var test2 = dense*diagonal;
         }
     }
 }

src/UnitTests/LinearAlgebraTests/Double/IO/DelimitedWriterTests.cs

@@ -3,7 +3,9 @@
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
-// Copyright (c) 2009-2010 Math.NET
+//
+// Copyright (c) 2009-2013 Math.NET
+//
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
 // files (the "Software"), to deal in the Software without
@@ -12,8 +14,10 @@
 // copies of the Software, and to permit persons to whom the
 // Software is furnished to do so, subject to the following
 // conditions:
+//
 // The above copyright notice and this permission notice shall be
 // included in all copies or substantial portions of the Software.
+//
 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
@@ -26,12 +30,12 @@
 
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.IO
 {
-    using System;
-    using System.Globalization;
-    using System.IO;
     using LinearAlgebra.Double;
     using LinearAlgebra.IO;
     using NUnit.Framework;
+    using System;
+    using System.Globalization;
+    using System.IO;
 
     /// <summary>
     /// Delimited writer tests.
@@ -45,19 +49,19 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.IO
         [Test]
         public void CanWriteCommaDelimitedData()
         {
-            var matrix = new DenseMatrix(new[,] { { 1.1, 2.2, 3.3 }, { 4.4, 5.5, 6.6 }, { 7.7, 8.8, 9.9 } });
+            var matrix = DenseMatrix.OfArray(new[,] {{1.1, 2.2, 3.3}, {4.4, 5.5, 6.6}, {7.7, 8.8, 9.9}});
             var writer = new DelimitedWriter(',')
-                         {
+                {
-                             CultureInfo = CultureInfo.InvariantCulture
+                    CultureInfo = CultureInfo.InvariantCulture
-                         };
+                };
             var stream = new MemoryStream();
             writer.WriteMatrix(matrix, stream);
             var data = stream.ToArray();
             var reader = new StreamReader(new MemoryStream(data));
             var text = reader.ReadToEnd();
             var expected = @"1.1,2.2,3.3" + Environment.NewLine
-                           + "4.4,5.5,6.6" + Environment.NewLine
+                + "4.4,5.5,6.6" + Environment.NewLine
-                           + "7.7,8.8,9.9";
+                + "7.7,8.8,9.9";
             Assert.AreEqual(expected, text);
         }
 
@@ -67,20 +71,20 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.IO
         [Test]
         public void CanWritePeriodDelimitedData()
         {
-            var matrix = new DenseMatrix(new[,] { { 1.1, 2.2, 3.3 }, { 4.4, 5.5, 6.6 }, { 7.7, 8.8, 9.9 } });
+            var matrix = DenseMatrix.OfArray(new[,] {{1.1, 2.2, 3.3}, {4.4, 5.5, 6.6}, {7.7, 8.8, 9.9}});
             var culture = new CultureInfo("tr-TR");
             var writer = new DelimitedWriter('.')
-                         {
+                {
-                             CultureInfo = culture
+                    CultureInfo = culture
-                         };
+                };
             var stream = new MemoryStream();
             writer.WriteMatrix(matrix, stream);
             var data = stream.ToArray();
             var reader = new StreamReader(new MemoryStream(data));
             var text = reader.ReadToEnd();
             var expected = @"1,1.2,2.3,3" + Environment.NewLine
-                           + "4,4.5,5.6,6" + Environment.NewLine
+                + "4,4.5,5.6,6" + Environment.NewLine
-                           + "7,7.8,8.9,9";
+                + "7,7.8,8.9,9";
             Assert.AreEqual(expected, text);
         }
 
@@ -90,19 +94,19 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.IO
         [Test]
         public void CanWriteSpaceDelimitedData()
         {
-            var matrix = new SparseMatrix(new[,] { { 1.1, 0, 0 }, { 0, 5.5, 0 }, { 0, 0, 9.9 } });
+            var matrix = SparseMatrix.OfArray(new[,] {{1.1, 0, 0}, {0, 5.5, 0}, {0, 0, 9.9}});
             var writer = new DelimitedWriter(' ')
-                         {
+                {
-                             CultureInfo = CultureInfo.InvariantCulture
+                    CultureInfo = CultureInfo.InvariantCulture
-                         };
+                };
             var stream = new MemoryStream();
             writer.WriteMatrix(matrix, stream);
             var data = stream.ToArray();
             var reader = new StreamReader(new MemoryStream(data));
             var text = reader.ReadToEnd();
             var expected = @"1.1 0 0" + Environment.NewLine
-                           + "0 5.5 0" + Environment.NewLine
+                + "0 5.5 0" + Environment.NewLine
-                           + "0 0 9.9";
+                + "0 0 9.9";
             Assert.AreEqual(expected, text);
         }
 
@@ -112,22 +116,22 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double.IO
         [Test]
         public void CanWriteTabDelimitedData()
         {
-            var matrix = new UserDefinedMatrix(new[,] { { 1.1, 2.2, 3.3 }, { 4.4, 5.5, 6.6 }, { 7.7, 8.8, 9.9 } });
+            var matrix = new UserDefinedMatrix(new[,] {{1.1, 2.2, 3.3}, {4.4, 5.5, 6.6}, {7.7, 8.8, 9.9}});
-            var headers = new[] { "a", "b", "c" };
+            var headers = new[] {"a", "b", "c"};
             var writer = new DelimitedWriter('\t')
-                         {
+                {
-                             ColumnHeaders = headers,
+                    ColumnHeaders = headers,
-                             CultureInfo = CultureInfo.InvariantCulture
+                    CultureInfo = CultureInfo.InvariantCulture
-                         };
+                };
             var stream = new MemoryStream();
             writer.WriteMatrix(matrix, stream);
             var data = stream.ToArray();
             var reader = new StreamReader(new MemoryStream(data));
             var text = reader.ReadToEnd();
             var expected = "a\tb\tc" + Environment.NewLine
-                           + "1.1\t2.2\t3.3" + Environment.NewLine
+                + "1.1\t2.2\t3.3" + Environment.NewLine
-                           + "4.4\t5.5\t6.6" + Environment.NewLine
+                + "4.4\t5.5\t6.6" + Environment.NewLine
-                           + "7.7\t8.8\t9.9";
+                + "7.7\t8.8\t9.9";
             Assert.AreEqual(expected, text);
         }
     }

src/UnitTests/LinearAlgebraTests/Double/MatrixStructureTheory.cs

@@ -1,12 +1,41 @@
-using System.Linq;
+// <copyright file="MatrixStructureTheory.cs" company="Math.NET">
-using MathNet.Numerics.Distributions;
+// Math.NET Numerics, part of the Math.NET Project
-using MathNet.Numerics.Random;
+// http://numerics.mathdotnet.com
+// http://github.com/mathnet/mathnet-numerics
+// http://mathnetnumerics.codeplex.com
+//
+// Copyright (c) 2009-2013 Math.NET
+//
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+//
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+//
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
 
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
 {
+    using Distributions;
     using LinearAlgebra.Double;
     using LinearAlgebra.Generic;
+    using Numerics.Random;
     using NUnit.Framework;
+    using System.Linq;
 
     [TestFixture]
     public class MatrixStructureTheory : MatrixStructureTheory<double>
@@ -14,17 +43,17 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         [Datapoints]
         Matrix<double>[] _matrices = new Matrix<double>[]
             {
-                new DenseMatrix(new[,] {{1d, 1d, 2d}, {1d, 1d, 2d}, {1d, 1d, 2d}}),
+                DenseMatrix.OfArray(new[,] {{1d, 1d, 2d}, {1d, 1d, 2d}, {1d, 1d, 2d}}),
-                new DenseMatrix(new[,] {{-1.1d, -2.2d, -3.3d}, {0d, 1.1d, 2.2d}, {-4.4d, 5.5d, 6.6d}}),
+                DenseMatrix.OfArray(new[,] {{-1.1d, -2.2d, -3.3d}, {0d, 1.1d, 2.2d}, {-4.4d, 5.5d, 6.6d}}),
-                new DenseMatrix(new[,] {{-1.1d, -2.2d, -3.3d, -4.4d}, {0d, 1.1d, 2.2d, 3.3d}, {1d, 2.1d, 6.2d, 4.3d}, {-4.4d, 5.5d, 6.6d, -7.7d}}),
+                DenseMatrix.OfArray(new[,] {{-1.1d, -2.2d, -3.3d, -4.4d}, {0d, 1.1d, 2.2d, 3.3d}, {1d, 2.1d, 6.2d, 4.3d}, {-4.4d, 5.5d, 6.6d, -7.7d}}),
-                new DenseMatrix(new[,] {{-1.1d, -2.2d, -3.3d, -4.4d}, {-1.1d, -2.2d, -3.3d, -4.4d}, {-1.1d, -2.2d, -3.3d, -4.4d}, {-1.1d, -2.2d, -3.3d, -4.4d}}),
+                DenseMatrix.OfArray(new[,] {{-1.1d, -2.2d, -3.3d, -4.4d}, {-1.1d, -2.2d, -3.3d, -4.4d}, {-1.1d, -2.2d, -3.3d, -4.4d}, {-1.1d, -2.2d, -3.3d, -4.4d}}),
-                new DenseMatrix(new[,] {{-1.1d, -2.2d}, {0d, 1.1d}, {-4.4d, 5.5d}}),
+                DenseMatrix.OfArray(new[,] {{-1.1d, -2.2d}, {0d, 1.1d}, {-4.4d, 5.5d}}),
-                new DenseMatrix(new[,] {{-1.1d, -2.2d, -3.3d}, {0d, 1.1d, 2.2d}}),
+                DenseMatrix.OfArray(new[,] {{-1.1d, -2.2d, -3.3d}, {0d, 1.1d, 2.2d}}),
-                new DenseMatrix(new[,] {{1d, 2d, 3d}, {2d, 2d, 0d}, {3d, 0d, 3d}}),
+                DenseMatrix.OfArray(new[,] {{1d, 2d, 3d}, {2d, 2d, 0d}, {3d, 0d, 3d}}),
 
-                new SparseMatrix(new[,] {{7d, 1d, 2d}, {1d, 1d, 2d}, {1d, 1d, 2d}}),
+                SparseMatrix.OfArray(new[,] {{7d, 1d, 2d}, {1d, 1d, 2d}, {1d, 1d, 2d}}),
-                new SparseMatrix(new[,] {{7d, 1d, 2d}, {1d, 0d, 0d}, {-2d, 0d, 0d}}),
+                SparseMatrix.OfArray(new[,] {{7d, 1d, 2d}, {1d, 0d, 0d}, {-2d, 0d, 0d}}),
-                new SparseMatrix(new[,] {{-1.1d, 0d, 0d}, {0d, 1.1d, 2.2d}}),
+                SparseMatrix.OfArray(new[,] {{-1.1d, 0d, 0d}, {0d, 1.1d, 2.2d}}),
 
                 new DiagonalMatrix(3, 3, new[] {1d, -2d, 1.5d}),
                 new DiagonalMatrix(3, 3, new[] {1d, 0d, -1.5d}),
@@ -67,4 +96,4 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
             get { return 0d; }
         }
     }
-}
+}

src/UnitTests/LinearAlgebraTests/Double/SparseMatrixTests.cs

@@ -3,7 +3,9 @@
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
-// Copyright (c) 2009-2010 Math.NET
+//
+// Copyright (c) 2009-2013 Math.NET
+//
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
 // files (the "Software"), to deal in the Software without
@@ -12,8 +14,10 @@
 // copies of the Software, and to permit persons to whom the
 // Software is furnished to do so, subject to the following
 // conditions:
+//
 // The above copyright notice and this permission notice shall be
 // included in all copies or substantial portions of the Software.
+//
 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
@@ -26,11 +30,11 @@
 
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
 {
-    using System;
-    using System.Collections.Generic;
     using LinearAlgebra.Double;
     using LinearAlgebra.Double.IO;
     using NUnit.Framework;
+    using System;
+    using System.Collections.Generic;
 
     /// <summary>
     /// Sparse matrix tests.
@@ -55,7 +59,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         /// <returns>A matrix with the given values.</returns>
         protected override Matrix CreateMatrix(double[,] data)
         {
-            return new SparseMatrix(data);
+            return SparseMatrix.OfArray(data);
         }
 
         /// <summary>
@@ -86,13 +90,13 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         public void CanCreateMatrixFrom1DArray()
         {
             var testData = new Dictionary<string, Matrix>
-                           {
+                {
-                               { "Singular3x3", new SparseMatrix(3, 3, new double[] { 1, 1, 1, 1, 1, 1, 2, 2, 2 }) },
+                    {"Singular3x3", SparseMatrix.OfColumnMajor(3, 3, new double[] {1, 1, 1, 1, 1, 1, 2, 2, 2})},
-                               { "Square3x3", new SparseMatrix(3, 3, new[] { -1.1, 0.0, -4.4, -2.2, 1.1, 5.5, -3.3, 2.2, 6.6 }) },
+                    {"Square3x3", SparseMatrix.OfColumnMajor(3, 3, new[] {-1.1, 0.0, -4.4, -2.2, 1.1, 5.5, -3.3, 2.2, 6.6})},
-                               { "Square4x4", new SparseMatrix(4, 4, new[] { -1.1, 0.0, 1.0, -4.4, -2.2, 1.1, 2.1, 5.5, -3.3, 2.2, 6.2, 6.6, -4.4, 3.3, 4.3, -7.7 }) },
+                    {"Square4x4", SparseMatrix.OfColumnMajor(4, 4, new[] {-1.1, 0.0, 1.0, -4.4, -2.2, 1.1, 2.1, 5.5, -3.3, 2.2, 6.2, 6.6, -4.4, 3.3, 4.3, -7.7})},
-                               { "Tall3x2", new SparseMatrix(3, 2, new[] { -1.1, 0.0, -4.4, -2.2, 1.1, 5.5 }) },
+                    {"Tall3x2", SparseMatrix.OfColumnMajor(3, 2, new[] {-1.1, 0.0, -4.4, -2.2, 1.1, 5.5})},
-                               { "Wide2x3", new SparseMatrix(2, 3, new[] { -1.1, 0.0, -2.2, 1.1, -3.3, 2.2 }) }
+                    {"Wide2x3", SparseMatrix.OfColumnMajor(2, 3, new[] {-1.1, 0.0, -2.2, 1.1, -3.3, 2.2})}
-                           };
+                };
 
             foreach (var name in testData.Keys)
             {
@@ -107,8 +111,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         public void MatrixFrom1DArrayIsCopy()
         {
             // Sparse Matrix copies values from double[], but no remember reference. 
-            var data = new double[] { 1, 1, 1, 1, 1, 1, 2, 2, 2 };
+            var data = new double[] {1, 1, 1, 1, 1, 1, 2, 2, 2};
-            var matrix = new SparseMatrix(3, 3, data);
+            var matrix = SparseMatrix.OfColumnMajor(3, 3, data);
             matrix[0, 0] = 10.0;
             Assert.AreNotEqual(10.0, data[0]);
         }
@@ -119,7 +123,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         [Test]
         public void MatrixFrom2DArrayIsCopy()
         {
-            var matrix = new SparseMatrix(TestData2D["Singular3x3"]);
+            var matrix = SparseMatrix.OfArray(TestData2D["Singular3x3"]);
             matrix[0, 0] = 10.0;
             Assert.AreEqual(1.0, TestData2D["Singular3x3"][0, 0]);
         }
@@ -136,7 +140,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         [TestCase("Wide2x3")]
         public void CanCreateMatrixFrom2DArray(string name)
         {
-            var matrix = new SparseMatrix(TestData2D[name]);
+            var matrix = SparseMatrix.OfArray(TestData2D[name]);
             for (var i = 0; i < TestData2D[name].GetLength(0); i++)
             {
                 for (var j = 0; j < TestData2D[name].GetLength(1); j++)
@@ -187,7 +191,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
             {
                 for (var j = 0; j < matrix.ColumnCount; j++)
                 {
-                    var value = rnd.Next(10) * rnd.Next(10) * rnd.Next(10) * rnd.Next(10) * rnd.Next(10);
+                    var value = rnd.Next(10)*rnd.Next(10)*rnd.Next(10)*rnd.Next(10)*rnd.Next(10);
                     if (value != 0)
                     {
                         nonzero++;
@@ -207,7 +211,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         public void CanAddSparseMatricesBothWays()
         {
             var m1 = new SparseMatrix(1, 3);
-            var m2 = new SparseMatrix(new double[,] { { 0, 1, 1 } });
+            var m2 = SparseMatrix.OfArray(new double[,] { { 0, 1, 1 } });
             var sum1 = m1 + m2;
             var sum2 = m2 + m1;
             Assert.IsTrue(sum1.Equals(m2));
@@ -217,27 +221,27 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
             sparseResult.Add(m2, sparseResult);
             Assert.IsTrue(sparseResult.Equals(sum1));
 
-            sparseResult = new SparseMatrix(new double[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new double[,] { { 0, 1, 1 } });
             sparseResult.Add(m1, sparseResult);
             Assert.IsTrue(sparseResult.Equals(sum1));
 
-            sparseResult = new SparseMatrix(new double[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new double[,] { { 0, 1, 1 } });
             m1.Add(sparseResult, sparseResult);
             Assert.IsTrue(sparseResult.Equals(sum1));
 
-            sparseResult = new SparseMatrix(new double[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new double[,] { { 0, 1, 1 } });
             sparseResult.Add(sparseResult, sparseResult);
-            Assert.IsTrue(sparseResult.Equals(2 * sum1));
+            Assert.IsTrue(sparseResult.Equals(2*sum1));
 
             var denseResult = new DenseMatrix(1, 3);
             denseResult.Add(m2, denseResult);
             Assert.IsTrue(denseResult.Equals(sum1));
 
-            denseResult = new DenseMatrix(new double[,] { { 0, 1, 1 } });
+            denseResult = DenseMatrix.OfArray(new double[,] {{0, 1, 1}});
             denseResult.Add(m1, denseResult);
             Assert.IsTrue(denseResult.Equals(sum1));
 
-            var m3 = new DenseMatrix(new double[,] { { 0, 1, 1 } });
+            var m3 = DenseMatrix.OfArray(new double[,] {{0, 1, 1}});
             var sum3 = m1 + m3;
             var sum4 = m3 + m1;
             Assert.IsTrue(sum3.Equals(m3));
@@ -251,7 +255,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
         public void CanSubtractSparseMatricesBothWays()
         {
             var m1 = new SparseMatrix(1, 3);
-            var m2 = new SparseMatrix(new double[,] { { 0, 1, 1 } });
+            var m2 = SparseMatrix.OfArray(new double[,] { { 0, 1, 1 } });
             var diff1 = m1 - m2;
             var diff2 = m2 - m1;
             Assert.IsTrue(diff1.Equals(m2.Negate()));
@@ -261,27 +265,27 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
             sparseResult.Subtract(m2, sparseResult);
             Assert.IsTrue(sparseResult.Equals(diff1));
 
-            sparseResult = new SparseMatrix(new double[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new double[,] { { 0, 1, 1 } });
             sparseResult.Subtract(m1, sparseResult);
             Assert.IsTrue(sparseResult.Equals(diff2));
 
-            sparseResult = new SparseMatrix(new double[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new double[,] { { 0, 1, 1 } });
             m1.Subtract(sparseResult, sparseResult);
             Assert.IsTrue(sparseResult.Equals(diff1));
 
-            sparseResult = new SparseMatrix(new double[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new double[,] { { 0, 1, 1 } });
             sparseResult.Subtract(sparseResult, sparseResult);
-            Assert.IsTrue(sparseResult.Equals(0 * diff1));
+            Assert.IsTrue(sparseResult.Equals(0*diff1));
 
             var denseResult = new DenseMatrix(1, 3);
             denseResult.Subtract(m2, denseResult);
             Assert.IsTrue(denseResult.Equals(diff1));
 
-            denseResult = new DenseMatrix(new double[,] { { 0, 1, 1 } });
+            denseResult = DenseMatrix.OfArray(new double[,] {{0, 1, 1}});
             denseResult.Subtract(m1, denseResult);
             Assert.IsTrue(denseResult.Equals(diff2));
 
-            var m3 = new DenseMatrix(new double[,] { { 0, 1, 1 } });
+            var m3 = DenseMatrix.OfArray(new double[,] {{0, 1, 1}});
             var diff3 = m1 - m3;
             var diff4 = m3 - m1;
             Assert.IsTrue(diff3.Equals(m3.Negate()));

src/UnitTests/LinearAlgebraTests/Single/DenseMatrixTests.cs

@@ -3,7 +3,9 @@
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
-// Copyright (c) 2009-2010 Math.NET
+//
+// Copyright (c) 2009-2013 Math.NET
+//
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
 // files (the "Software"), to deal in the Software without
@@ -12,8 +14,10 @@
 // copies of the Software, and to permit persons to whom the
 // Software is furnished to do so, subject to the following
 // conditions:
+//
 // The above copyright notice and this permission notice shall be
 // included in all copies or substantial portions of the Software.
+//
 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
@@ -26,10 +30,10 @@
 
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
 {
-    using System;
-    using System.Collections.Generic;
     using LinearAlgebra.Single;
     using NUnit.Framework;
+    using System;
+    using System.Collections.Generic;
 
     /// <summary>
     /// Dense matrix tests.
@@ -54,7 +58,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         /// <returns>A matrix with the given values.</returns>
         protected override Matrix CreateMatrix(float[,] data)
         {
-            return new DenseMatrix(data);
+            return DenseMatrix.OfArray(data);
         }
 
         /// <summary>
@@ -85,13 +89,13 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         public void CanCreateMatrixFrom1DArray()
         {
             var testData = new Dictionary<string, Matrix>
-                           {
+                {
-                               { "Singular3x3", new DenseMatrix(3, 3, new[] { 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f }) },
+                    {"Singular3x3", new DenseMatrix(3, 3, new[] {1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 1.0f, 2.0f, 2.0f, 2.0f})},
-                               { "Square3x3", new DenseMatrix(3, 3, new[] { -1.1f, 0.0f, -4.4f, -2.2f, 1.1f, 5.5f, -3.3f, 2.2f, 6.6f }) },
+                    {"Square3x3", new DenseMatrix(3, 3, new[] {-1.1f, 0.0f, -4.4f, -2.2f, 1.1f, 5.5f, -3.3f, 2.2f, 6.6f})},
-                               { "Square4x4", new DenseMatrix(4, 4, new[] { -1.1f, 0.0f, 1.0f, -4.4f, -2.2f, 1.1f, 2.1f, 5.5f, -3.3f, 2.2f, 6.2f, 6.6f, -4.4f, 3.3f, 4.3f, -7.7f }) },
+                    {"Square4x4", new DenseMatrix(4, 4, new[] {-1.1f, 0.0f, 1.0f, -4.4f, -2.2f, 1.1f, 2.1f, 5.5f, -3.3f, 2.2f, 6.2f, 6.6f, -4.4f, 3.3f, 4.3f, -7.7f})},
-                               { "Tall3x2", new DenseMatrix(3, 2, new[] { -1.1f, 0.0f, -4.4f, -2.2f, 1.1f, 5.5f }) },
+                    {"Tall3x2", new DenseMatrix(3, 2, new[] {-1.1f, 0.0f, -4.4f, -2.2f, 1.1f, 5.5f})},
-                               { "Wide2x3", new DenseMatrix(2, 3, new[] { -1.1f, 0.0f, -2.2f, 1.1f, -3.3f, 2.2f }) }
+                    {"Wide2x3", new DenseMatrix(2, 3, new[] {-1.1f, 0.0f, -2.2f, 1.1f, -3.3f, 2.2f})}
-                           };
+                };
 
             foreach (var name in testData.Keys)
             {
@@ -105,7 +109,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         [Test]
         public void MatrixFrom1DArrayIsReference()
         {
-            var data = new float[] { 1, 1, 1, 1, 1, 1, 2, 2, 2 };
+            var data = new float[] {1, 1, 1, 1, 1, 1, 2, 2, 2};
             var matrix = new DenseMatrix(3, 3, data);
             matrix[0, 0] = 10.0f;
             Assert.AreEqual(10.0f, data[0]);
@@ -117,7 +121,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         [Test]
         public void MatrixFrom2DArrayIsCopy()
         {
-            var matrix = new DenseMatrix(TestData2D["Singular3x3"]);
+            var matrix = DenseMatrix.OfArray(TestData2D["Singular3x3"]);
             matrix[0, 0] = 10.0f;
             Assert.AreEqual(1.0f, TestData2D["Singular3x3"][0, 0]);
         }
@@ -134,7 +138,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         [TestCase("Wide2x3")]
         public void CanCreateMatrixFrom2DArray(string name)
         {
-            var matrix = new DenseMatrix(TestData2D[name]);
+            var matrix = DenseMatrix.OfArray(TestData2D[name]);
             for (var i = 0; i < TestData2D[name].GetLength(0); i++)
             {
                 for (var j = 0; j < TestData2D[name].GetLength(1); j++)

src/UnitTests/LinearAlgebraTests/Single/DiagonalMatrixTests.cs

@@ -3,7 +3,9 @@
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
-// Copyright (c) 2009-2010 Math.NET
+//
+// Copyright (c) 2009-2013 Math.NET
+//
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
 // files (the "Software"), to deal in the Software without
@@ -12,8 +14,10 @@
 // copies of the Software, and to permit persons to whom the
 // Software is furnished to do so, subject to the following
 // conditions:
+//
 // The above copyright notice and this permission notice shall be
 // included in all copies or substantial portions of the Software.
+//
 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
@@ -26,15 +30,10 @@
 
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
 {
-    using System;
-    using System.Collections.Generic;
-    using System.Linq;
     using LinearAlgebra.Single;
     using NUnit.Framework;
-
+    using System;
-#if PORTABLE
+    using System.Collections.Generic;
-    using Threading;
-#endif
 
     /// <summary>
     /// Diagonal matrix tests.
@@ -48,14 +47,14 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         public override void SetupMatrices()
         {
             TestData2D = new Dictionary<string, float[,]>
-                         {
+                {
-                             { "Singular3x3", new[,] { { 1.0f, 0.0f, 0.0f }, { 0.0f, 0.0f, 0.0f }, { 0.0f, 0.0f, 3.0f } } },
+                    {"Singular3x3", new[,] {{1.0f, 0.0f, 0.0f}, {0.0f, 0.0f, 0.0f}, {0.0f, 0.0f, 3.0f}}},
-                             { "Square3x3", new[,] { { -1.1f, 0.0f, 0.0f }, { 0.0f, 1.1f, 0.0f }, { 0.0f, 0.0f, 6.6f } } },
+                    {"Square3x3", new[,] {{-1.1f, 0.0f, 0.0f}, {0.0f, 1.1f, 0.0f}, {0.0f, 0.0f, 6.6f}}},
-                             { "Square4x4", new[,] { { -1.1f, 0.0f, 0.0f, 0.0f }, { 0.0f, 1.1f, 0.0f, 0.0f }, { 0.0f, 0.0f, 6.2f, 0.0f }, { 0.0f, 0.0f, 0.0f, -7.7f } } },
+                    {"Square4x4", new[,] {{-1.1f, 0.0f, 0.0f, 0.0f}, {0.0f, 1.1f, 0.0f, 0.0f}, {0.0f, 0.0f, 6.2f, 0.0f}, {0.0f, 0.0f, 0.0f, -7.7f}}},
-                             { "Singular4x4", new[,] { { -1.1f, 0.0f, 0.0f, 0.0f }, { 0.0f, -2.2f, 0.0f, 0.0f }, { 0.0f, 0.0f, 0.0f, 0.0f }, { 0.0f, 0.0f, 0.0f, -4.4f } } },
+                    {"Singular4x4", new[,] {{-1.1f, 0.0f, 0.0f, 0.0f}, {0.0f, -2.2f, 0.0f, 0.0f}, {0.0f, 0.0f, 0.0f, 0.0f}, {0.0f, 0.0f, 0.0f, -4.4f}}},
-                             { "Tall3x2", new[,] { { -1.1f, 0.0f }, { 0.0f, 1.1f }, { 0.0f, 0.0f } } },
+                    {"Tall3x2", new[,] {{-1.1f, 0.0f}, {0.0f, 1.1f}, {0.0f, 0.0f}}},
-                             { "Wide2x3", new[,] { { -1.1f, 0.0f, 0.0f }, { 0.0f, 1.1f, 0.0f } } }
+                    {"Wide2x3", new[,] {{-1.1f, 0.0f, 0.0f}, {0.0f, 1.1f, 0.0f}}}
-                         };
+                };
 
             TestMatrices = new Dictionary<string, Matrix>();
             foreach (var name in TestData2D.Keys)
@@ -113,13 +112,13 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         public void CanCreateMatrixFromDiagonalArray()
         {
             var testData = new Dictionary<string, Matrix>
-                           {
+                {
-                               { "Singular3x3", new DiagonalMatrix(3, 3, new[] { 1.0f, 0.0f, 3.0f }) },
+                    {"Singular3x3", new DiagonalMatrix(3, 3, new[] {1.0f, 0.0f, 3.0f})},
-                               { "Square3x3", new DiagonalMatrix(3, 3, new[] { -1.1f, 1.1f, 6.6f }) },
+                    {"Square3x3", new DiagonalMatrix(3, 3, new[] {-1.1f, 1.1f, 6.6f})},
-                               { "Square4x4", new DiagonalMatrix(4, 4, new[] { -1.1f, 1.1f, 6.2f, -7.7f }) },
+                    {"Square4x4", new DiagonalMatrix(4, 4, new[] {-1.1f, 1.1f, 6.2f, -7.7f})},
-                               { "Tall3x2", new DiagonalMatrix(3, 2, new[] { -1.1f, 1.1f }) },
+                    {"Tall3x2", new DiagonalMatrix(3, 2, new[] {-1.1f, 1.1f})},
-                               { "Wide2x3", new DiagonalMatrix(2, 3, new[] { -1.1f, 1.1f }) },
+                    {"Wide2x3", new DiagonalMatrix(2, 3, new[] {-1.1f, 1.1f})},
-                           };
+                };
 
             foreach (var name in testData.Keys)
             {
@@ -133,7 +132,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         [Test]
         public void MatrixFrom1DArrayIsReference()
         {
-            var data = new float[] { 1, 2, 3, 4, 5 };
+            var data = new float[] {1, 2, 3, 4, 5};
             var matrix = new DiagonalMatrix(5, 5, data);
             matrix[0, 0] = 10.0f;
             Assert.AreEqual(10.0f, data[0]);
@@ -220,7 +219,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
             {
                 for (var j = 0; j < matrixC.ColumnCount; j++)
                 {
-                    AssertHelpers.AlmostEqual(matrixA.Row(i) * matrixB.Column(j), matrixC[i, j], 15);
+                    AssertHelpers.AlmostEqual(matrixA.Row(i)*matrixB.Column(j), matrixC[i, j], 15);
                 }
             }
         }
@@ -232,7 +231,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         public void PermuteMatrixRowsThrowsInvalidOperationException()
         {
             var matrixp = CreateMatrix(TestData2D["Singular3x3"]);
-            var permutation = new Permutation(new[] { 2, 0, 1 });
+            var permutation = new Permutation(new[] {2, 0, 1});
             Assert.Throws<InvalidOperationException>(() => matrixp.PermuteRows(permutation));
         }
 
@@ -243,7 +242,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         public void PermuteMatrixColumnsThrowsInvalidOperationException()
         {
             var matrixp = CreateMatrix(TestData2D["Singular3x3"]);
-            var permutation = new Permutation(new[] { 2, 0, 1 });
+            var permutation = new Permutation(new[] {2, 0, 1});
             Assert.Throws<InvalidOperationException>(() => matrixp.PermuteColumns(permutation));
         }
 
@@ -260,13 +259,13 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
                 var min = Math.Min(data.RowCount, data.ColumnCount);
                 for (var i = 0; i < min; i++)
                 {
-                    Assert.AreEqual(data[i, i] / other[i, i], result[i, i]);
+                    Assert.AreEqual(data[i, i]/other[i, i], result[i, i]);
                 }
 
                 result = data.PointwiseDivide(other);
                 for (var i = 0; i < min; i++)
                 {
-                    Assert.AreEqual(data[i, i] / other[i, i], result[i, i]);
+                    Assert.AreEqual(data[i, i]/other[i, i], result[i, i]);
                 }
             }
         }
@@ -277,15 +276,15 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         public override void CanComputeFrobeniusNorm()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.FrobeniusNorm(), matrix.FrobeniusNorm(), 7);
 
             matrix = TestMatrices["Wide2x3"];
-            denseMatrix = new DenseMatrix(TestData2D["Wide2x3"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Wide2x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.FrobeniusNorm(), matrix.FrobeniusNorm(), 7);
 
             matrix = TestMatrices["Tall3x2"];
-            denseMatrix = new DenseMatrix(TestData2D["Tall3x2"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Tall3x2"]);
             AssertHelpers.AlmostEqual(denseMatrix.FrobeniusNorm(), matrix.FrobeniusNorm(), 7);
         }
 
@@ -295,15 +294,15 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         public override void CanComputeInfinityNorm()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.InfinityNorm(), matrix.InfinityNorm(), 7);
 
             matrix = TestMatrices["Wide2x3"];
-            denseMatrix = new DenseMatrix(TestData2D["Wide2x3"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Wide2x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.InfinityNorm(), matrix.InfinityNorm(), 7);
 
             matrix = TestMatrices["Tall3x2"];
-            denseMatrix = new DenseMatrix(TestData2D["Tall3x2"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Tall3x2"]);
             AssertHelpers.AlmostEqual(denseMatrix.InfinityNorm(), matrix.InfinityNorm(), 7);
         }
 
@@ -313,15 +312,15 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         public override void CanComputeL1Norm()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.L1Norm(), matrix.L1Norm(), 7);
 
             matrix = TestMatrices["Wide2x3"];
-            denseMatrix = new DenseMatrix(TestData2D["Wide2x3"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Wide2x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.L1Norm(), matrix.L1Norm(), 7);
 
             matrix = TestMatrices["Tall3x2"];
-            denseMatrix = new DenseMatrix(TestData2D["Tall3x2"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Tall3x2"]);
             AssertHelpers.AlmostEqual(denseMatrix.L1Norm(), matrix.L1Norm(), 7);
         }
 
@@ -331,15 +330,15 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         public override void CanComputeL2Norm()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.L2Norm(), matrix.L2Norm(), 7);
 
             matrix = TestMatrices["Wide2x3"];
-            denseMatrix = new DenseMatrix(TestData2D["Wide2x3"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Wide2x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.L2Norm(), matrix.L2Norm(), 7);
 
             matrix = TestMatrices["Tall3x2"];
-            denseMatrix = new DenseMatrix(TestData2D["Tall3x2"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Tall3x2"]);
             AssertHelpers.AlmostEqual(denseMatrix.L2Norm(), matrix.L2Norm(), 7);
         }
 
@@ -350,11 +349,11 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         public void CanComputeDeterminant()
         {
             var matrix = TestMatrices["Square3x3"];
-            var denseMatrix = new DenseMatrix(TestData2D["Square3x3"]);
+            var denseMatrix = DenseMatrix.OfArray(TestData2D["Square3x3"]);
             AssertHelpers.AlmostEqual(denseMatrix.Determinant(), matrix.Determinant(), 7);
 
             matrix = TestMatrices["Square4x4"];
-            denseMatrix = new DenseMatrix(TestData2D["Square4x4"]);
+            denseMatrix = DenseMatrix.OfArray(TestData2D["Square4x4"]);
             AssertHelpers.AlmostEqual(denseMatrix.Determinant(), matrix.Determinant(), 7);
         }
 

src/UnitTests/LinearAlgebraTests/Single/IO/DelimitedWriterTests.cs

@@ -3,7 +3,9 @@
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
-// Copyright (c) 2009-2010 Math.NET
+//
+// Copyright (c) 2009-2013 Math.NET
+//
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
 // files (the "Software"), to deal in the Software without
@@ -12,8 +14,10 @@
 // copies of the Software, and to permit persons to whom the
 // Software is furnished to do so, subject to the following
 // conditions:
+//
 // The above copyright notice and this permission notice shall be
 // included in all copies or substantial portions of the Software.
+//
 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
@@ -23,14 +27,15 @@
 // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
 // OTHER DEALINGS IN THE SOFTWARE.
 // </copyright>
+
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single.IO
 {
-    using System;
-    using System.Globalization;
-    using System.IO;
     using LinearAlgebra.IO;
     using LinearAlgebra.Single;
     using NUnit.Framework;
+    using System;
+    using System.Globalization;
+    using System.IO;
 
     /// <summary>
     /// Delimited writer tests.
@@ -44,19 +49,19 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single.IO
         [Test]
         public void CanWriteCommaDelimitedData()
         {
-            var matrix = new DenseMatrix(new[,] { { 1.1f, 2.2f, 3.3f }, { 4.4f, 5.5f, 6.6f }, { 7.7f, 8.8f, 9.9f } });
+            var matrix = DenseMatrix.OfArray(new[,] {{1.1f, 2.2f, 3.3f}, {4.4f, 5.5f, 6.6f}, {7.7f, 8.8f, 9.9f}});
             var writer = new DelimitedWriter(',')
-                         {
+                {
-                             CultureInfo = CultureInfo.InvariantCulture
+                    CultureInfo = CultureInfo.InvariantCulture
-                         };
+                };
             var stream = new MemoryStream();
             writer.WriteMatrix(matrix, stream);
             var data = stream.ToArray();
             var reader = new StreamReader(new MemoryStream(data));
             var text = reader.ReadToEnd();
             var expected = @"1.1,2.2,3.3" + Environment.NewLine
-                           + "4.4,5.5,6.6" + Environment.NewLine
+                + "4.4,5.5,6.6" + Environment.NewLine
-                           + "7.7,8.8,9.9";
+                + "7.7,8.8,9.9";
             Assert.AreEqual(expected, text);
         }
 
@@ -66,20 +71,20 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single.IO
         [Test]
         public void CanWritePeriodDelimitedData()
         {
-            var matrix = new DenseMatrix(new[,] { { 1.1f, 2.2f, 3.3f }, { 4.4f, 5.5f, 6.6f }, { 7.7f, 8.8f, 9.9f } });
+            var matrix = DenseMatrix.OfArray(new[,] {{1.1f, 2.2f, 3.3f}, {4.4f, 5.5f, 6.6f}, {7.7f, 8.8f, 9.9f}});
             var culture = new CultureInfo("tr-TR");
             var writer = new DelimitedWriter('.')
-                         {
+                {
-                             CultureInfo = culture
+                    CultureInfo = culture
-                         };
+                };
             var stream = new MemoryStream();
             writer.WriteMatrix(matrix, stream);
             var data = stream.ToArray();
             var reader = new StreamReader(new MemoryStream(data));
             var text = reader.ReadToEnd();
             var expected = @"1,1.2,2.3,3" + Environment.NewLine
-                           + "4,4.5,5.6,6" + Environment.NewLine
+                + "4,4.5,5.6,6" + Environment.NewLine
-                           + "7,7.8,8.9,9";
+                + "7,7.8,8.9,9";
             Assert.AreEqual(expected, text);
         }
 
@@ -89,19 +94,19 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single.IO
         [Test]
         public void CanWriteSpaceDelimitedData()
         {
-            var matrix = new SparseMatrix(new[,] { { 1.1f, 0, 0 }, { 0, 5.5f, 0 }, { 0, 0, 9.9f } });
+            var matrix = SparseMatrix.OfArray(new[,] {{1.1f, 0, 0}, {0, 5.5f, 0}, {0, 0, 9.9f}});
             var writer = new DelimitedWriter(' ')
-                         {
+                {
-                             CultureInfo = CultureInfo.InvariantCulture
+                    CultureInfo = CultureInfo.InvariantCulture
-                         };
+                };
             var stream = new MemoryStream();
             writer.WriteMatrix(matrix, stream);
             var data = stream.ToArray();
             var reader = new StreamReader(new MemoryStream(data));
             var text = reader.ReadToEnd();
             var expected = @"1.1 0 0" + Environment.NewLine
-                           + "0 5.5 0" + Environment.NewLine
+                + "0 5.5 0" + Environment.NewLine
-                           + "0 0 9.9";
+                + "0 0 9.9";
             Assert.AreEqual(expected, text);
         }
 
@@ -111,22 +116,22 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single.IO
         [Test]
         public void CanWriteTabDelimitedData()
         {
-            var matrix = new UserDefinedMatrix(new[,] { { 1.1f, 2.2f, 3.3f }, { 4.4f, 5.5f, 6.6f }, { 7.7f, 8.8f, 9.9f } });
+            var matrix = new UserDefinedMatrix(new[,] {{1.1f, 2.2f, 3.3f}, {4.4f, 5.5f, 6.6f}, {7.7f, 8.8f, 9.9f}});
-            var headers = new[] { "a", "b", "c" };
+            var headers = new[] {"a", "b", "c"};
             var writer = new DelimitedWriter('\t')
-                         {
+                {
-                             ColumnHeaders = headers,
+                    ColumnHeaders = headers,
-                             CultureInfo = CultureInfo.InvariantCulture
+                    CultureInfo = CultureInfo.InvariantCulture
-                         };
+                };
             var stream = new MemoryStream();
             writer.WriteMatrix(matrix, stream);
             var data = stream.ToArray();
             var reader = new StreamReader(new MemoryStream(data));
             var text = reader.ReadToEnd();
             var expected = "a\tb\tc" + Environment.NewLine
-                           + "1.1\t2.2\t3.3" + Environment.NewLine
+                + "1.1\t2.2\t3.3" + Environment.NewLine
-                           + "4.4\t5.5\t6.6" + Environment.NewLine
+                + "4.4\t5.5\t6.6" + Environment.NewLine
-                           + "7.7\t8.8\t9.9";
+                + "7.7\t8.8\t9.9";
             Assert.AreEqual(expected, text);
         }
     }

src/UnitTests/LinearAlgebraTests/Single/MatrixStructureTheory.cs

@@ -1,12 +1,41 @@
-using System.Linq;
+// <copyright file="MatrixStructureTheory.cs" company="Math.NET">
-using MathNet.Numerics.Distributions;
+// Math.NET Numerics, part of the Math.NET Project
-using MathNet.Numerics.Random;
+// http://numerics.mathdotnet.com
+// http://github.com/mathnet/mathnet-numerics
+// http://mathnetnumerics.codeplex.com
+//
+// Copyright (c) 2009-2013 Math.NET
+//
+// Permission is hereby granted, free of charge, to any person
+// obtaining a copy of this software and associated documentation
+// files (the "Software"), to deal in the Software without
+// restriction, including without limitation the rights to use,
+// copy, modify, merge, publish, distribute, sublicense, and/or sell
+// copies of the Software, and to permit persons to whom the
+// Software is furnished to do so, subject to the following
+// conditions:
+//
+// The above copyright notice and this permission notice shall be
+// included in all copies or substantial portions of the Software.
+//
+// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
+// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
+// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
+// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
+// OTHER DEALINGS IN THE SOFTWARE.
+// </copyright>
 
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
 {
-    using LinearAlgebra.Single;
+    using Distributions;
     using LinearAlgebra.Generic;
+    using LinearAlgebra.Single;
+    using Numerics.Random;
     using NUnit.Framework;
+    using System.Linq;
 
     [TestFixture]
     public class MatrixStructureTheory : MatrixStructureTheory<float>
@@ -14,17 +43,17 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         [Datapoints]
         Matrix<float>[] _matrices = new Matrix<float>[]
             {
-                new DenseMatrix(new[,] {{1f, 1f, 2f}, {1f, 1f, 2f}, {1f, 1f, 2f}}),
+                DenseMatrix.OfArray(new[,] {{1f, 1f, 2f}, {1f, 1f, 2f}, {1f, 1f, 2f}}),
-                new DenseMatrix(new[,] {{-1.1f, -2.2f, -3.3f}, {0f, 1.1f, 2.2f}, {-4.4f, 5.5f, 6.6f}}),
+                DenseMatrix.OfArray(new[,] {{-1.1f, -2.2f, -3.3f}, {0f, 1.1f, 2.2f}, {-4.4f, 5.5f, 6.6f}}),
-                new DenseMatrix(new[,] {{-1.1f, -2.2f, -3.3f, -4.4f}, {0f, 1.1f, 2.2f, 3.3f}, {1f, 2.1f, 6.2f, 4.3f}, {-4.4f, 5.5f, 6.6f, -7.7f}}),
+                DenseMatrix.OfArray(new[,] {{-1.1f, -2.2f, -3.3f, -4.4f}, {0f, 1.1f, 2.2f, 3.3f}, {1f, 2.1f, 6.2f, 4.3f}, {-4.4f, 5.5f, 6.6f, -7.7f}}),
-                new DenseMatrix(new[,] {{-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}}),
+                DenseMatrix.OfArray(new[,] {{-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}, {-1.1f, -2.2f, -3.3f, -4.4f}}),
-                new DenseMatrix(new[,] {{-1.1f, -2.2f}, {0f, 1.1f}, {-4.4f, 5.5f}}),
+                DenseMatrix.OfArray(new[,] {{-1.1f, -2.2f}, {0f, 1.1f}, {-4.4f, 5.5f}}),
-                new DenseMatrix(new[,] {{-1.1f, -2.2f, -3.3f}, {0f, 1.1f, 2.2f}}),
+                DenseMatrix.OfArray(new[,] {{-1.1f, -2.2f, -3.3f}, {0f, 1.1f, 2.2f}}),
-                new DenseMatrix(new[,] {{1f, 2f, 3f}, {2f, 2f, 0f}, {3f, 0f, 3f}}),
+                DenseMatrix.OfArray(new[,] {{1f, 2f, 3f}, {2f, 2f, 0f}, {3f, 0f, 3f}}),
 
-                new SparseMatrix(new[,] {{7f, 1f, 2f}, {1f, 1f, 2f}, {1f, 1f, 2f}}),
+                SparseMatrix.OfArray(new[,] {{7f, 1f, 2f}, {1f, 1f, 2f}, {1f, 1f, 2f}}),
-                new SparseMatrix(new[,] {{7f, 1f, 2f}, {1f, 0f, 0f}, {-2f, 0f, 0f}}),
+                SparseMatrix.OfArray(new[,] {{7f, 1f, 2f}, {1f, 0f, 0f}, {-2f, 0f, 0f}}),
-                new SparseMatrix(new[,] {{-1.1f, 0f, 0f}, {0f, 1.1f, 2.2f}}),
+                SparseMatrix.OfArray(new[,] {{-1.1f, 0f, 0f}, {0f, 1.1f, 2.2f}}),
 
                 new DiagonalMatrix(3, 3, new[] {1f, -2f, 1.5f}),
                 new DiagonalMatrix(3, 3, new[] {1f, 0f, -1.5f}),

src/UnitTests/LinearAlgebraTests/Single/SparseMatrixTests.cs

@@ -3,7 +3,9 @@
 // http://numerics.mathdotnet.com
 // http://github.com/mathnet/mathnet-numerics
 // http://mathnetnumerics.codeplex.com
-// Copyright (c) 2009-2010 Math.NET
+//
+// Copyright (c) 2009-2013 Math.NET
+//
 // Permission is hereby granted, free of charge, to any person
 // obtaining a copy of this software and associated documentation
 // files (the "Software"), to deal in the Software without
@@ -12,8 +14,10 @@
 // copies of the Software, and to permit persons to whom the
 // Software is furnished to do so, subject to the following
 // conditions:
+//
 // The above copyright notice and this permission notice shall be
 // included in all copies or substantial portions of the Software.
+//
 // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
 // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
 // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
@@ -26,10 +30,10 @@
 
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
 {
-    using System;
-    using System.Collections.Generic;
     using LinearAlgebra.Single;
     using NUnit.Framework;
+    using System;
+    using System.Collections.Generic;
 
     /// <summary>
     /// Sparse matrix tests.
@@ -54,7 +58,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         /// <returns>A matrix with the given values.</returns>
         protected override Matrix CreateMatrix(float[,] data)
         {
-            return new SparseMatrix(data);
+            return SparseMatrix.OfArray(data);
         }
 
         /// <summary>
@@ -85,13 +89,13 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         public void CanCreateMatrixFrom1DArray()
         {
             var testData = new Dictionary<string, Matrix>
-                           {
+                {
-                               { "Singular3x3", new SparseMatrix(3, 3, new float[] { 1, 1, 1, 1, 1, 1, 2, 2, 2 }) },
+                    {"Singular3x3", SparseMatrix.OfColumnMajor(3, 3, new float[] {1, 1, 1, 1, 1, 1, 2, 2, 2})},
-                               { "Square3x3", new SparseMatrix(3, 3, new[] { -1.1f, 0.0f, -4.4f, -2.2f, 1.1f, 5.5f, -3.3f, 2.2f, 6.6f }) },
+                    {"Square3x3", SparseMatrix.OfColumnMajor(3, 3, new[] {-1.1f, 0.0f, -4.4f, -2.2f, 1.1f, 5.5f, -3.3f, 2.2f, 6.6f})},
-                               { "Square4x4", new SparseMatrix(4, 4, new[] { -1.1f, 0.0f, 1.0f, -4.4f, -2.2f, 1.1f, 2.1f, 5.5f, -3.3f, 2.2f, 6.2f, 6.6f, -4.4f, 3.3f, 4.3f, -7.7f }) },
+                    {"Square4x4", SparseMatrix.OfColumnMajor(4, 4, new[] {-1.1f, 0.0f, 1.0f, -4.4f, -2.2f, 1.1f, 2.1f, 5.5f, -3.3f, 2.2f, 6.2f, 6.6f, -4.4f, 3.3f, 4.3f, -7.7f})},
-                               { "Tall3x2", new SparseMatrix(3, 2, new[] { -1.1f, 0.0f, -4.4f, -2.2f, 1.1f, 5.5f }) },
+                    {"Tall3x2", SparseMatrix.OfColumnMajor(3, 2, new[] {-1.1f, 0.0f, -4.4f, -2.2f, 1.1f, 5.5f})},
-                               { "Wide2x3", new SparseMatrix(2, 3, new[] { -1.1f, 0.0f, -2.2f, 1.1f, -3.3f, 2.2f }) }
+                    {"Wide2x3", SparseMatrix.OfColumnMajor(2, 3, new[] {-1.1f, 0.0f, -2.2f, 1.1f, -3.3f, 2.2f})}
-                           };
+                };
 
             foreach (var name in testData.Keys)
             {
@@ -106,8 +110,8 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         public void MatrixFrom1DArrayIsCopy()
         {
             // Sparse Matrix copies values from float[], but no remember reference. 
-            var data = new float[] { 1, 1, 1, 1, 1, 1, 2, 2, 2 };
+            var data = new float[] {1, 1, 1, 1, 1, 1, 2, 2, 2};
-            var matrix = new SparseMatrix(3, 3, data);
+            var matrix = SparseMatrix.OfColumnMajor(3, 3, data);
             matrix[0, 0] = 10.0f;
             Assert.AreNotEqual(10.0f, data[0]);
         }
@@ -118,7 +122,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         [Test]
         public void MatrixFrom2DArrayIsCopy()
         {
-            var matrix = new SparseMatrix(TestData2D["Singular3x3"]);
+            var matrix = SparseMatrix.OfArray(TestData2D["Singular3x3"]);
             matrix[0, 0] = 10.0f;
             Assert.AreEqual(1.0f, TestData2D["Singular3x3"][0, 0]);
         }
@@ -135,7 +139,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         [TestCase("Wide2x3")]
         public void CanCreateMatrixFrom2DArray(string name)
         {
-            var matrix = new SparseMatrix(TestData2D[name]);
+            var matrix = SparseMatrix.OfArray(TestData2D[name]);
             for (var i = 0; i < TestData2D[name].GetLength(0); i++)
             {
                 for (var j = 0; j < TestData2D[name].GetLength(1); j++)
@@ -186,7 +190,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
             {
                 for (var j = 0; j < matrix.ColumnCount; j++)
                 {
-                    var value = rnd.Next(10) * rnd.Next(10) * rnd.Next(10) * rnd.Next(10) * rnd.Next(10);
+                    var value = rnd.Next(10)*rnd.Next(10)*rnd.Next(10)*rnd.Next(10)*rnd.Next(10);
                     if (value != 0)
                     {
                         nonzero++;
@@ -206,7 +210,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         public void CanAddSparseMatricesBothWays()
         {
             var m1 = new SparseMatrix(1, 3);
-            var m2 = new SparseMatrix(new float[,] { { 0, 1, 1 } });
+            var m2 = SparseMatrix.OfArray(new float[,] { { 0, 1, 1 } });
             var sum1 = m1 + m2;
             var sum2 = m2 + m1;
             Assert.IsTrue(sum1.Equals(m2));
@@ -216,27 +220,27 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
             sparseResult.Add(m2, sparseResult);
             Assert.IsTrue(sparseResult.Equals(sum1));
 
-            sparseResult = new SparseMatrix(new float[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new float[,] { { 0, 1, 1 } });
             sparseResult.Add(m1, sparseResult);
             Assert.IsTrue(sparseResult.Equals(sum1));
 
-            sparseResult = new SparseMatrix(new float[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new float[,] { { 0, 1, 1 } });
             m1.Add(sparseResult, sparseResult);
             Assert.IsTrue(sparseResult.Equals(sum1));
 
-            sparseResult = new SparseMatrix(new float[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new float[,] { { 0, 1, 1 } });
             sparseResult.Add(sparseResult, sparseResult);
-            Assert.IsTrue(sparseResult.Equals(2 * sum1));
+            Assert.IsTrue(sparseResult.Equals(2*sum1));
 
             var denseResult = new DenseMatrix(1, 3);
             denseResult.Add(m2, denseResult);
             Assert.IsTrue(denseResult.Equals(sum1));
 
-            denseResult = new DenseMatrix(new float[,] { { 0, 1, 1 } });
+            denseResult = DenseMatrix.OfArray(new float[,] {{0, 1, 1}});
             denseResult.Add(m1, denseResult);
             Assert.IsTrue(denseResult.Equals(sum1));
 
-            var m3 = new DenseMatrix(new float[,] { { 0, 1, 1 } });
+            var m3 = DenseMatrix.OfArray(new float[,] {{0, 1, 1}});
             var sum3 = m1 + m3;
             var sum4 = m3 + m1;
             Assert.IsTrue(sum3.Equals(m3));
@@ -250,7 +254,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
         public void CanSubtractSparseMatricesBothWays()
         {
             var m1 = new SparseMatrix(1, 3);
-            var m2 = new SparseMatrix(new float[,] { { 0, 1, 1 } });
+            var m2 = SparseMatrix.OfArray(new float[,] { { 0, 1, 1 } });
             var diff1 = m1 - m2;
             var diff2 = m2 - m1;
             Assert.IsTrue(diff1.Equals(m2.Negate()));
@@ -260,27 +264,27 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
             sparseResult.Subtract(m2, sparseResult);
             Assert.IsTrue(sparseResult.Equals(diff1));
 
-            sparseResult = new SparseMatrix(new float[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new float[,] { { 0, 1, 1 } });
             sparseResult.Subtract(m1, sparseResult);
             Assert.IsTrue(sparseResult.Equals(diff2));
 
-            sparseResult = new SparseMatrix(new float[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new float[,] { { 0, 1, 1 } });
             m1.Subtract(sparseResult, sparseResult);
             Assert.IsTrue(sparseResult.Equals(diff1));
 
-            sparseResult = new SparseMatrix(new float[,] { { 0, 1, 1 } });
+            sparseResult = SparseMatrix.OfArray(new float[,] { { 0, 1, 1 } });
             sparseResult.Subtract(sparseResult, sparseResult);
-            Assert.IsTrue(sparseResult.Equals(0 * diff1));
+            Assert.IsTrue(sparseResult.Equals(0*diff1));
 
             var denseResult = new DenseMatrix(1, 3);
             denseResult.Subtract(m2, denseResult);
             Assert.IsTrue(denseResult.Equals(diff1));
 
-            denseResult = new DenseMatrix(new float[,] { { 0, 1, 1 } });
+            denseResult = DenseMatrix.OfArray(new float[,] {{0, 1, 1}});
             denseResult.Subtract(m1, denseResult);
             Assert.IsTrue(denseResult.Equals(diff2));
 
-            var m3 = new DenseMatrix(new float[,] { { 0, 1, 1 } });
+            var m3 = DenseMatrix.OfArray(new float[,] {{0, 1, 1}});
             var diff3 = m1 - m3;
             var diff4 = m3 - m1;
             Assert.IsTrue(diff3.Equals(m3.Negate()));