LA: matrix OfColumns/OfRows more usable, basic tests

src/FSharp/LinearAlgebra.Double.Matrix.fs

@@ -269,26 +269,26 @@ module DenseMatrix =
     let inline ofSeq (fss: #seq<#seq<float>>) =
         let n = Seq.length fss
         let m = Seq.length (Seq.head fss)
-        DenseMatrix.OfRows(n, m, fss)
+        DenseMatrix.OfRowsCovariant(n, m, fss)
 
     /// Create a matrix from a list of float lists. Every list in the master list specifies a row.
     /// If the dimensions are known, consider to use ofRowList instead to avoid multiple enumeration.
     let inline ofList (fll: float list list) =
         let n = List.length fll
         let m = List.length (List.head fll)
-        DenseMatrix.OfRows(n, m, fll)
+        DenseMatrix.OfRowsCovariant(n, m, fll)
 
     /// Create a matrix from a list of sequences. Every sequence in the master sequence specifies a row.
-    let inline ofRowSeq (rows: int) (cols: int) (fss: #seq<#seq<float>>) = DenseMatrix.OfRows(rows, cols, fss)
+    let inline ofRowSeq (rows: int) (cols: int) (fss: #seq<#seq<float>>) = DenseMatrix.OfRowsCovariant(rows, cols, fss)
 
     /// Create a matrix from a list of float lists. Every list in the master list specifies a row.
-    let inline ofRowList (rows: int) (cols: int) (fll: float list list) = DenseMatrix.OfRows(rows, cols, fll)
+    let inline ofRowList (rows: int) (cols: int) (fll: float list list) = DenseMatrix.OfRowsCovariant(rows, cols, fll)
 
     /// Create a matrix from a list of sequences. Every sequence in the master sequence specifies a column.
-    let inline ofColumnSeq (rows: int) (cols: int) (fss: #seq<#seq<float>>) = DenseMatrix.OfColumns(rows, cols, fss)
+    let inline ofColumnSeq (rows: int) (cols: int) (fss: #seq<#seq<float>>) = DenseMatrix.OfColumnsCovariant(rows, cols, fss)
 
     /// Create a matrix from a list of float lists. Every list in the master list specifies a column.
-    let inline ofColumnList (rows: int) (cols: int) (fll: float list list) = DenseMatrix.OfColumns(rows, cols, fll)
+    let inline ofColumnList (rows: int) (cols: int) (fll: float list list) = DenseMatrix.OfColumnsCovariant(rows, cols, fll)
 
     /// Create a matrix with a given dimension from an indexed sequences of row, column, value tuples.
     let inline ofSeqi (rows: int) (cols: int) (fs: #seq<int * int * float>) = DenseMatrix.OfIndexed(rows, cols, fs)
@@ -351,16 +351,16 @@ module SparseMatrix =
     let inline ofList (rows: int) (cols: int) (fl: list<int * int * float>) = SparseMatrix.OfIndexed(rows, cols, Seq.ofList fl)
 
     /// Create a matrix from a list of sequences. Every sequence in the master sequence specifies a row.
-    let inline ofRowSeq (rows: int) (cols: int) (fss: #seq<#seq<float>>) = SparseMatrix.OfRows(rows, cols, fss)
+    let inline ofRowSeq (rows: int) (cols: int) (fss: #seq<#seq<float>>) = SparseMatrix.OfRowsCovariant(rows, cols, fss)
 
     /// Create a matrix from a list of float lists. Every list in the master list specifies a row.
-    let inline ofRowList (rows: int) (cols: int) (fll: float list list) = SparseMatrix.OfRows(rows, cols, fll)
+    let inline ofRowList (rows: int) (cols: int) (fll: float list list) = SparseMatrix.OfRowsCovariant(rows, cols, fll)
 
     /// Create a matrix from a list of sequences. Every sequence in the master sequence specifies a column.
-    let inline ofColumnSeq (rows: int) (cols: int) (fss: #seq<#seq<float>>) = SparseMatrix.OfColumns(rows, cols, fss)
+    let inline ofColumnSeq (rows: int) (cols: int) (fss: #seq<#seq<float>>) = SparseMatrix.OfColumnsCovariant(rows, cols, fss)
 
     /// Create a matrix from a list of float lists. Every list in the master list specifies a column.
-    let inline ofColumnList (rows: int) (cols: int) (fll: float list list) = SparseMatrix.OfColumns(rows, cols, fll)
+    let inline ofColumnList (rows: int) (cols: int) (fll: float list list) = SparseMatrix.OfColumnsCovariant(rows, cols, fll)
 
     /// Create a matrix with a given dimension from an indexed sequences of row, column, value tuples.
     let inline ofSeqi (rows: int) (cols: int) (fs: #seq<int * int * float>) = SparseMatrix.OfIndexed(rows, cols, fs)

src/Numerics/LinearAlgebra/Complex/DenseMatrix.cs

@@ -162,8 +162,18 @@ namespace MathNet.Numerics.LinearAlgebra.Complex
         /// This new matrix will be independent from the enumerables.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        public static DenseMatrix OfColumns<TColumn>(int rows, int columns, IEnumerable<TColumn> data)
+        public static DenseMatrix OfColumns(int rows, int columns, IEnumerable<IEnumerable<Complex>> data)
-            // NOTE: flexible typing to 'backport' generic covariance.
+        {
+            return new DenseMatrix(DenseColumnMajorMatrixStorage<Complex>.OfColumnEnumerables(rows, columns, data));
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given enumerable of enumerable columns.
+        /// Each enumerable in the master enumerable specifies a column.
+        /// This new matrix will be independent from the enumerables.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static DenseMatrix OfColumnsCovariant<TColumn>(int rows, int columns, IEnumerable<TColumn> data)
             where TColumn : IEnumerable<Complex>
         {
             return new DenseMatrix(DenseColumnMajorMatrixStorage<Complex>.OfColumnEnumerables(rows, columns, data));
@@ -175,8 +185,18 @@ namespace MathNet.Numerics.LinearAlgebra.Complex
         /// This new matrix will be independent from the enumerables.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        public static DenseMatrix OfRows<TRow>(int rows, int columns, IEnumerable<TRow> data)
+        public static DenseMatrix OfRows(int rows, int columns, IEnumerable<IEnumerable<Complex>> data)
-            // NOTE: flexible typing to 'backport' generic covariance.
+        {
+            return new DenseMatrix(DenseColumnMajorMatrixStorage<Complex>.OfRowEnumerables(rows, columns, data));
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given enumerable of enumerable rows.
+        /// Each enumerable in the master enumerable specifies a row.
+        /// This new matrix will be independent from the enumerables.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static DenseMatrix OfRowsCovariant<TRow>(int rows, int columns, IEnumerable<TRow> data)
             where TRow : IEnumerable<Complex>
         {
             return new DenseMatrix(DenseColumnMajorMatrixStorage<Complex>.OfRowEnumerables(rows, columns, data));

src/Numerics/LinearAlgebra/Complex/SparseMatrix.cs

@@ -152,7 +152,18 @@ namespace MathNet.Numerics.LinearAlgebra.Complex
         /// This new matrix will be independent from the enumerables.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        public static SparseMatrix OfColumns<TColumn>(int rows, int columns, IEnumerable<TColumn> data)
+        public static SparseMatrix OfColumns(int rows, int columns, IEnumerable<IEnumerable<Complex>> data)
+        {
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<Complex>.OfColumnEnumerables(rows, columns, data));
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given enumerable of enumerable columns.
+        /// Each enumerable in the master enumerable specifies a column.
+        /// This new matrix will be independent from the enumerables.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfColumnsCovariant<TColumn>(int rows, int columns, IEnumerable<TColumn> data)
             // NOTE: flexible typing to 'backport' generic covariance.
             where TColumn : IEnumerable<Complex>
         {
@@ -165,7 +176,18 @@ namespace MathNet.Numerics.LinearAlgebra.Complex
         /// This new matrix will be independent from the enumerables.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        public static SparseMatrix OfRows<TRow>(int rows, int columns, IEnumerable<TRow> data)
+        public static SparseMatrix OfRows(int rows, int columns, IEnumerable<IEnumerable<Complex>> data)
+        {
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<Complex>.OfRowEnumerables(rows, columns, data));
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given enumerable of enumerable rows.
+        /// Each enumerable in the master enumerable specifies a row.
+        /// This new matrix will be independent from the enumerables.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfRowsCovariant<TRow>(int rows, int columns, IEnumerable<TRow> data)
             // NOTE: flexible typing to 'backport' generic covariance.
             where TRow : IEnumerable<Complex>
         {

src/Numerics/LinearAlgebra/Complex32/DenseMatrix.cs

@@ -162,8 +162,18 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32
         /// This new matrix will be independent from the enumerables.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        public static DenseMatrix OfColumns<TColumn>(int rows, int columns, IEnumerable<TColumn> data)
+        public static DenseMatrix OfColumns(int rows, int columns, IEnumerable<IEnumerable<Complex32>> data)
-            // NOTE: flexible typing to 'backport' generic covariance.
+        {
+            return new DenseMatrix(DenseColumnMajorMatrixStorage<Complex32>.OfColumnEnumerables(rows, columns, data));
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given enumerable of enumerable columns.
+        /// Each enumerable in the master enumerable specifies a column.
+        /// This new matrix will be independent from the enumerables.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static DenseMatrix OfColumnsCovariant<TColumn>(int rows, int columns, IEnumerable<TColumn> data)
             where TColumn : IEnumerable<Complex32>
         {
             return new DenseMatrix(DenseColumnMajorMatrixStorage<Complex32>.OfColumnEnumerables(rows, columns, data));
@@ -175,8 +185,18 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32
         /// This new matrix will be independent from the enumerables.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        public static DenseMatrix OfRows<TRow>(int rows, int columns, IEnumerable<TRow> data)
+        public static DenseMatrix OfRows(int rows, int columns, IEnumerable<IEnumerable<Complex32>> data)
-            // NOTE: flexible typing to 'backport' generic covariance.
+        {
+            return new DenseMatrix(DenseColumnMajorMatrixStorage<Complex32>.OfRowEnumerables(rows, columns, data));
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given enumerable of enumerable rows.
+        /// Each enumerable in the master enumerable specifies a row.
+        /// This new matrix will be independent from the enumerables.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static DenseMatrix OfRowsCovariant<TRow>(int rows, int columns, IEnumerable<TRow> data)
             where TRow : IEnumerable<Complex32>
         {
             return new DenseMatrix(DenseColumnMajorMatrixStorage<Complex32>.OfRowEnumerables(rows, columns, data));

src/Numerics/LinearAlgebra/Complex32/SparseMatrix.cs

@@ -152,7 +152,18 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32
         /// This new matrix will be independent from the enumerables.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        public static SparseMatrix OfColumns<TColumn>(int rows, int columns, IEnumerable<TColumn> data)
+        public static SparseMatrix OfColumns(int rows, int columns, IEnumerable<IEnumerable<Complex32>> data)
+        {
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<Complex32>.OfColumnEnumerables(rows, columns, data));
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given enumerable of enumerable columns.
+        /// Each enumerable in the master enumerable specifies a column.
+        /// This new matrix will be independent from the enumerables.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfColumnsCovariant<TColumn>(int rows, int columns, IEnumerable<TColumn> data)
             // NOTE: flexible typing to 'backport' generic covariance.
             where TColumn : IEnumerable<Complex32>
         {
@@ -165,7 +176,18 @@ namespace MathNet.Numerics.LinearAlgebra.Complex32
         /// This new matrix will be independent from the enumerables.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        public static SparseMatrix OfRows<TRow>(int rows, int columns, IEnumerable<TRow> data)
+        public static SparseMatrix OfRows(int rows, int columns, IEnumerable<IEnumerable<Complex32>> data)
+        {
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<Complex32>.OfRowEnumerables(rows, columns, data));
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given enumerable of enumerable rows.
+        /// Each enumerable in the master enumerable specifies a row.
+        /// This new matrix will be independent from the enumerables.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfRowsCovariant<TRow>(int rows, int columns, IEnumerable<TRow> data)
             // NOTE: flexible typing to 'backport' generic covariance.
             where TRow : IEnumerable<Complex32>
         {

src/Numerics/LinearAlgebra/Double/DenseMatrix.cs

@@ -164,8 +164,18 @@ namespace MathNet.Numerics.LinearAlgebra.Double
         /// This new matrix will be independent from the enumerables.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        public static DenseMatrix OfColumns<TColumn>(int rows, int columns, IEnumerable<TColumn> data)
+        public static DenseMatrix OfColumns(int rows, int columns, IEnumerable<IEnumerable<double>> data)
-            // NOTE: flexible typing to 'backport' generic covariance.
+        {
+            return new DenseMatrix(DenseColumnMajorMatrixStorage<double>.OfColumnEnumerables(rows, columns, data));
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given enumerable of enumerable columns.
+        /// Each enumerable in the master enumerable specifies a column.
+        /// This new matrix will be independent from the enumerables.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static DenseMatrix OfColumnsCovariant<TColumn>(int rows, int columns, IEnumerable<TColumn> data)
             where TColumn : IEnumerable<double>
         {
             return new DenseMatrix(DenseColumnMajorMatrixStorage<double>.OfColumnEnumerables(rows, columns, data));
@@ -177,8 +187,18 @@ namespace MathNet.Numerics.LinearAlgebra.Double
         /// This new matrix will be independent from the enumerables.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        public static DenseMatrix OfRows<TRow>(int rows, int columns, IEnumerable<TRow> data)
+        public static DenseMatrix OfRows(int rows, int columns, IEnumerable<IEnumerable<double>> data)
-            // NOTE: flexible typing to 'backport' generic covariance.
+        {
+            return new DenseMatrix(DenseColumnMajorMatrixStorage<double>.OfRowEnumerables(rows, columns, data));
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given enumerable of enumerable rows.
+        /// Each enumerable in the master enumerable specifies a row.
+        /// This new matrix will be independent from the enumerables.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static DenseMatrix OfRowsCovariant<TRow>(int rows, int columns, IEnumerable<TRow> data)
             where TRow : IEnumerable<double>
         {
             return new DenseMatrix(DenseColumnMajorMatrixStorage<double>.OfRowEnumerables(rows, columns, data));

src/Numerics/LinearAlgebra/Double/SparseMatrix.cs

@@ -151,7 +151,18 @@ namespace MathNet.Numerics.LinearAlgebra.Double
         /// This new matrix will be independent from the enumerables.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        public static SparseMatrix OfColumns<TColumn>(int rows, int columns, IEnumerable<TColumn> data)
+        public static SparseMatrix OfColumns(int rows, int columns, IEnumerable<IEnumerable<double>> data)
+        {
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<double>.OfColumnEnumerables(rows, columns, data));
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given enumerable of enumerable columns.
+        /// Each enumerable in the master enumerable specifies a column.
+        /// This new matrix will be independent from the enumerables.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfColumnsCovariant<TColumn>(int rows, int columns, IEnumerable<TColumn> data)
             // NOTE: flexible typing to 'backport' generic covariance.
             where TColumn : IEnumerable<double>
         {
@@ -164,7 +175,18 @@ namespace MathNet.Numerics.LinearAlgebra.Double
         /// This new matrix will be independent from the enumerables.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        public static SparseMatrix OfRows<TRow>(int rows, int columns, IEnumerable<TRow> data)
+        public static SparseMatrix OfRows(int rows, int columns, IEnumerable<IEnumerable<double>> data)
+        {
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<double>.OfRowEnumerables(rows, columns, data));
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given enumerable of enumerable rows.
+        /// Each enumerable in the master enumerable specifies a row.
+        /// This new matrix will be independent from the enumerables.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfRowsCovariant<TRow>(int rows, int columns, IEnumerable<TRow> data)
             // NOTE: flexible typing to 'backport' generic covariance.
             where TRow : IEnumerable<double>
         {

src/Numerics/LinearAlgebra/Generic/Matrix.cs

@@ -84,6 +84,7 @@ namespace MathNet.Numerics.LinearAlgebra.Generic
         /// <param name="columnVectors">The vectors to construct the matrix from.</param>
         /// <returns>The matrix constructed from the list of column vectors.</returns>
         /// <remarks>Creates a matrix of size Max(<paramref name="columnVectors"/>[i].Count) x <paramref name="columnVectors"/>.Count</remarks>
+        [Obsolete("Use DenseMatrix.OfColumns or SparseMatrix.OfColumns instead. Scheduled for removal in v3.0.")]
         public static Matrix<T> CreateFromColumns(IList<Vector<T>> columnVectors)
         {
             if (columnVectors == null)
@@ -122,6 +123,7 @@ namespace MathNet.Numerics.LinearAlgebra.Generic
         /// <param name="rowVectors">The vectors to construct the matrix from.</param>
         /// <returns>The matrix constructed from the list of row vectors.</returns>
         /// <remarks>Creates a matrix of size Max(<paramref name="rowVectors"/>.Count) x <paramref name="rowVectors"/>[i].Count</remarks>
+        [Obsolete("Use DenseMatrix.OfRows or SparseMatrix.OfRows instead. Scheduled for removal in v3.0.")]
         public static Matrix<T> CreateFromRows(IList<Vector<T>> rowVectors)
         {
             if (rowVectors == null)

src/Numerics/LinearAlgebra/Single/DenseMatrix.cs

@@ -162,8 +162,18 @@ namespace MathNet.Numerics.LinearAlgebra.Single
         /// This new matrix will be independent from the enumerables.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        public static DenseMatrix OfColumns<TColumn>(int rows, int columns, IEnumerable<TColumn> data)
+        public static DenseMatrix OfColumns(int rows, int columns, IEnumerable<IEnumerable<float>> data)
-            // NOTE: flexible typing to 'backport' generic covariance.
+        {
+            return new DenseMatrix(DenseColumnMajorMatrixStorage<float>.OfColumnEnumerables(rows, columns, data));
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given enumerable of enumerable columns.
+        /// Each enumerable in the master enumerable specifies a column.
+        /// This new matrix will be independent from the enumerables.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static DenseMatrix OfColumnsCovariant<TColumn>(int rows, int columns, IEnumerable<TColumn> data)
             where TColumn : IEnumerable<float>
         {
             return new DenseMatrix(DenseColumnMajorMatrixStorage<float>.OfColumnEnumerables(rows, columns, data));
@@ -175,8 +185,18 @@ namespace MathNet.Numerics.LinearAlgebra.Single
         /// This new matrix will be independent from the enumerables.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        public static DenseMatrix OfRows<TRow>(int rows, int columns, IEnumerable<TRow> data)
+        public static DenseMatrix OfRows(int rows, int columns, IEnumerable<IEnumerable<float>> data)
-            // NOTE: flexible typing to 'backport' generic covariance.
+        {
+            return new DenseMatrix(DenseColumnMajorMatrixStorage<float>.OfRowEnumerables(rows, columns, data));
+        }
+
+        /// <summary>
+        /// Create a new dense matrix as a copy of the given enumerable of enumerable rows.
+        /// Each enumerable in the master enumerable specifies a row.
+        /// This new matrix will be independent from the enumerables.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static DenseMatrix OfRowsCovariant<TRow>(int rows, int columns, IEnumerable<TRow> data)
             where TRow : IEnumerable<float>
         {
             return new DenseMatrix(DenseColumnMajorMatrixStorage<float>.OfRowEnumerables(rows, columns, data));

src/Numerics/LinearAlgebra/Single/SparseMatrix.cs

@@ -144,6 +144,17 @@ namespace MathNet.Numerics.LinearAlgebra.Single
         {
             return new SparseMatrix(SparseCompressedRowMatrixStorage<float>.OfColumnMajorList(rows, columns, columnMajor));
         }
+        
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given enumerable of enumerable columns.
+        /// Each enumerable in the master enumerable specifies a column.
+        /// This new matrix will be independent from the enumerables.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfColumns(int rows, int columns, IEnumerable<IEnumerable<float>> data)
+        {
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<float>.OfColumnEnumerables(rows, columns, data));
+        }
 
         /// <summary>
         /// Create a new sparse matrix as a copy of the given enumerable of enumerable columns.
@@ -151,7 +162,7 @@ namespace MathNet.Numerics.LinearAlgebra.Single
         /// This new matrix will be independent from the enumerables.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        public static SparseMatrix OfColumns<TColumn>(int rows, int columns, IEnumerable<TColumn> data)
+        public static SparseMatrix OfColumnsCovariant<TColumn>(int rows, int columns, IEnumerable<TColumn> data)
             // NOTE: flexible typing to 'backport' generic covariance.
             where TColumn : IEnumerable<float>
         {
@@ -164,7 +175,18 @@ namespace MathNet.Numerics.LinearAlgebra.Single
         /// This new matrix will be independent from the enumerables.
         /// A new memory block will be allocated for storing the matrix.
         /// </summary>
-        public static SparseMatrix OfRows<TRow>(int rows, int columns, IEnumerable<TRow> data)
+        public static SparseMatrix OfRows(int rows, int columns, IEnumerable<IEnumerable<float>> data)
+        {
+            return new SparseMatrix(SparseCompressedRowMatrixStorage<float>.OfRowEnumerables(rows, columns, data));
+        }
+
+        /// <summary>
+        /// Create a new sparse matrix as a copy of the given enumerable of enumerable rows.
+        /// Each enumerable in the master enumerable specifies a row.
+        /// This new matrix will be independent from the enumerables.
+        /// A new memory block will be allocated for storing the matrix.
+        /// </summary>
+        public static SparseMatrix OfRowsCovariant<TRow>(int rows, int columns, IEnumerable<TRow> data)
             // NOTE: flexible typing to 'backport' generic covariance.
             where TRow : IEnumerable<float>
         {

src/UnitTests/LinearAlgebraTests/Complex/MatrixStructureTheory.cs

@@ -41,6 +41,11 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
     [TestFixture]
     public class MatrixStructureTheory : MatrixStructureTheory<Complex>
     {
+        public MatrixStructureTheory()
+            : base(Complex.Zero, typeof(DenseMatrix), typeof(SparseMatrix), typeof(DiagonalMatrix), typeof(DenseVector), typeof(SparseVector))
+        {
+        }
+
         [Datapoints]
         Matrix<Complex>[] _matrices = new Matrix<Complex>[]
             {
@@ -91,10 +96,5 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex
             var dist = new Normal {RandomSource = new MersenneTwister(seed)};
             return new DenseVector(Enumerable.Range(0, size).Select(k => new Complex(dist.Sample(), dist.Sample())).ToArray());
         }
-
-        protected override Complex Zero
-        {
-            get { return Complex.Zero; }
-        }
     }
 }

src/UnitTests/LinearAlgebraTests/Complex32/MatrixStructureTheory.cs

@@ -41,6 +41,11 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
     [TestFixture]
     public class MatrixStructureTheory : MatrixStructureTheory<Complex32>
     {
+        public MatrixStructureTheory()
+            : base(Complex32.Zero, typeof(DenseMatrix), typeof(SparseMatrix), typeof(DiagonalMatrix), typeof(DenseVector), typeof(SparseVector))
+        {
+        }
+
         [Datapoints]
         Matrix<Complex32>[] _matrices = new Matrix<Complex32>[]
             {
@@ -91,10 +96,5 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Complex32
             var dist = new Normal {RandomSource = new MersenneTwister(seed)};
             return new DenseVector(Enumerable.Range(0, size).Select(k => new Complex32((float) dist.Sample(), (float) dist.Sample())).ToArray());
         }
-
-        protected override Complex32 Zero
-        {
-            get { return Complex32.Zero; }
-        }
     }
 }

src/UnitTests/LinearAlgebraTests/Double/MatrixStructureTheory.cs

@@ -40,6 +40,11 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
     [TestFixture]
     public class MatrixStructureTheory : MatrixStructureTheory<double>
     {
+        public MatrixStructureTheory()
+            : base(0d, typeof (DenseMatrix), typeof (SparseMatrix), typeof (DiagonalMatrix), typeof (DenseVector), typeof (SparseVector))
+        {
+        }
+
         [Datapoints]
         Matrix<double>[] _matrices = new Matrix<double>[]
             {
@@ -90,10 +95,5 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Double
             var dist = new Normal {RandomSource = new MersenneTwister(seed)};
             return new DenseVector(dist.Samples().Take(size).ToArray());
         }
-
-        protected override double Zero
-        {
-            get { return 0d; }
-        }
     }
 }

src/UnitTests/LinearAlgebraTests/MatrixStructureTheory.Access.cs

@@ -6,7 +6,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
 {
     partial class MatrixStructureTheory<T>
     {
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetFieldsByIndex(Matrix<T> matrix)
         {
             Assert.That(() => matrix[0, 0], Throws.Nothing);
@@ -18,7 +18,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix[0, matrix.ColumnCount], Throws.InstanceOf<ArgumentOutOfRangeException>());
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetRow(Matrix<T> matrix)
         {
             // First Row
@@ -42,7 +42,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.Row(matrix.RowCount), Throws.InstanceOf<ArgumentOutOfRangeException>());
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetRowIntoResult(Matrix<T> matrix)
         {
             var row = CreateVectorZero(matrix.ColumnCount);
@@ -58,7 +58,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.Row(matrix.RowCount, row), Throws.InstanceOf<ArgumentOutOfRangeException>());
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetRowWithRange(Matrix<T> matrix)
         {
             // First Row, Columns 0..1
@@ -93,7 +93,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.Row(0, 0, matrix.ColumnCount + 1), Throws.InstanceOf<ArgumentOutOfRangeException>());
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetRowWithRangeIntoResult(Matrix<T> matrix)
         {
             var row = CreateVectorZero(matrix.ColumnCount - 1);
@@ -110,7 +110,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.Row(0, 0, matrix.ColumnCount, row), Throws.InstanceOf<ArgumentOutOfRangeException>());
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetColumn(Matrix<T> matrix)
         {
             // First Column
@@ -134,7 +134,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.Column(matrix.ColumnCount), Throws.InstanceOf<ArgumentOutOfRangeException>());
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetColumnIntoResult(Matrix<T> matrix)
         {
             var col = CreateVectorZero(matrix.RowCount);
@@ -150,7 +150,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.Column(matrix.ColumnCount, col), Throws.InstanceOf<ArgumentOutOfRangeException>());
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetColumnWithRange(Matrix<T> matrix)
         {
             // First Column, Rows 0..1
@@ -185,7 +185,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.Column(0, 0, matrix.RowCount + 1), Throws.InstanceOf<ArgumentOutOfRangeException>());
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetColumnWithRangeIntoResult(Matrix<T> matrix)
         {
             var col = CreateVectorZero(matrix.RowCount - 1);
@@ -202,7 +202,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.Column(0, 0, matrix.RowCount, col), Throws.InstanceOf<ArgumentOutOfRangeException>());
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanSetRow(Matrix<T> matrix)
         {
             // First Row
@@ -237,7 +237,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.SetRow(0, CreateVectorZero(matrix.ColumnCount + 1)), Throws.ArgumentException);
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanSetRowArray(Matrix<T> matrix)
         {
             // First Row
@@ -270,7 +270,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.SetRow(0, new T[matrix.ColumnCount + 1]), Throws.ArgumentException);
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanSetColumn(Matrix<T> matrix)
         {
             // First Column
@@ -305,7 +305,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.SetColumn(0, CreateVectorZero(matrix.RowCount + 1)), Throws.ArgumentException);
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanSetColumnArray(Matrix<T> matrix)
         {
             // First Column
@@ -338,7 +338,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.SetColumn(0, new T[matrix.RowCount + 1]), Throws.ArgumentException);
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetUpperTriangle(Matrix<T> matrix)
         {
             var upper = matrix.UpperTriangle();
@@ -351,7 +351,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             }
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetUpperTriangleIntoResult(Matrix<T> matrix)
         {
             var dense = CreateDenseZero(matrix.RowCount, matrix.ColumnCount);
@@ -379,7 +379,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.UpperTriangle(CreateDenseZero(matrix.RowCount, matrix.ColumnCount + 1)), Throws.ArgumentException);
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetLowerTriangle(Matrix<T> matrix)
         {
             var upper = matrix.LowerTriangle();
@@ -392,7 +392,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             }
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetLowerTriangleIntoResult(Matrix<T> matrix)
         {
             var dense = CreateDenseZero(matrix.RowCount, matrix.ColumnCount);
@@ -420,7 +420,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.LowerTriangle(CreateDenseZero(matrix.RowCount, matrix.ColumnCount + 1)), Throws.ArgumentException);
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetStrictlyUpperTriangle(Matrix<T> matrix)
         {
             var upper = matrix.StrictlyUpperTriangle();
@@ -433,7 +433,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             }
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetStrictlyUpperTriangleIntoResult(Matrix<T> matrix)
         {
             var dense = CreateDenseZero(matrix.RowCount, matrix.ColumnCount);
@@ -461,7 +461,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.StrictlyUpperTriangle(CreateDenseZero(matrix.RowCount, matrix.ColumnCount + 1)), Throws.ArgumentException);
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetStrictlyLowerTriangle(Matrix<T> matrix)
         {
             var upper = matrix.StrictlyLowerTriangle();
@@ -474,7 +474,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             }
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetStrictlyLowerTriangleIntoResult(Matrix<T> matrix)
         {
             var dense = CreateDenseZero(matrix.RowCount, matrix.ColumnCount);
@@ -502,7 +502,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.StrictlyLowerTriangle(CreateDenseZero(matrix.RowCount, matrix.ColumnCount + 1)), Throws.ArgumentException);
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetDiagonal(Matrix<T> matrix)
         {
             var diag = matrix.Diagonal();
@@ -513,7 +513,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             }
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanSetDiagonal(Matrix<T> matrix)
         {
             var m = matrix.Clone();
@@ -533,7 +533,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.SetDiagonal(CreateVectorZero(Math.Min(matrix.RowCount, matrix.ColumnCount) + 1)), Throws.ArgumentException);
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanSetDiagonalArray(Matrix<T> matrix)
         {
             var m = matrix.Clone();
@@ -552,7 +552,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.SetDiagonal(new T[Math.Min(matrix.RowCount, matrix.ColumnCount) + 1]), Throws.ArgumentException);
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanGetSubmatrix(Matrix<T> matrix)
         {
             // Top Left Corner 2x2
@@ -594,7 +594,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.SubMatrix(0, 1, 0, 0), Throws.InstanceOf<ArgumentOutOfRangeException>());
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanSetSubmatrix(Matrix<T> matrix)
         {
             // Top Left Corner 2x2

src/UnitTests/LinearAlgebraTests/MatrixStructureTheory.Reform.cs

@@ -7,7 +7,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
 {
     partial class MatrixStructureTheory<T>
     {
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanPermuteRows(Matrix<T> matrix)
         {
             var m = matrix.Clone();
@@ -36,7 +36,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             }
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanPermuteColumns(Matrix<T> matrix)
         {
             var m = matrix.Clone();
@@ -65,7 +65,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             }
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanInsertRow(Matrix<T> matrix)
         {
             var row = CreateVectorRandom(matrix.ColumnCount, 0);
@@ -101,7 +101,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.InsertRow(0, CreateVectorZero(matrix.ColumnCount + 1)), Throws.ArgumentException);
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanInsertColumn(Matrix<T> matrix)
         {
             var column = CreateVectorRandom(matrix.RowCount, 0);
@@ -137,7 +137,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.InsertColumn(0, CreateVectorZero(matrix.RowCount + 1)), Throws.ArgumentException);
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanAppend(Matrix<T> left, Matrix<T> right)
         {
             // IF
@@ -159,7 +159,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => left.Append(default(Matrix<T>)), Throws.InstanceOf<ArgumentNullException>());
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanAppendIntoResult(Matrix<T> left, Matrix<T> right)
         {
             // IF
@@ -186,7 +186,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => left.Append(right, CreateDenseZero(left.RowCount, left.ColumnCount + right.ColumnCount - 1)), Throws.ArgumentException);
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanStack(Matrix<T> top, Matrix<T> bottom)
         {
             // IF
@@ -208,7 +208,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => top.Stack(default(Matrix<T>)), Throws.InstanceOf<ArgumentNullException>());
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanStackIntoResult(Matrix<T> top, Matrix<T> bottom)
         {
             // IF
@@ -235,7 +235,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => top.Stack(bottom, CreateDenseZero(top.RowCount + bottom.RowCount, top.ColumnCount - 1)), Throws.ArgumentException);
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanDiagonalStack(Matrix<T> left, Matrix<T> right)
         {
             var result = left.DiagonalStack(right);
@@ -261,7 +261,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => left.DiagonalStack(default(Matrix<T>)), Throws.InstanceOf<ArgumentNullException>(), "{0}+{1}->{2}", left.GetType(), right.GetType(), result.GetType());
         }
 
-        [Theory, Timeout(500)]
+        [Theory]
         public void CanDiagonalStackIntoResult(Matrix<T> left, Matrix<T> right)
         {
             var result = CreateDenseZero(left.RowCount + right.RowCount, left.ColumnCount + right.ColumnCount);

src/UnitTests/LinearAlgebraTests/MatrixStructureTheory.cs

@@ -1,4 +1,34 @@
-using System.Collections.Generic;
+// <copyright file="MatrixStructureTheory.cs" company="Math.NET">
+// Math.NET Numerics, part of the Math.NET Project
+// 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>
+
+using System.Collections.Generic;
 
 namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
 {
@@ -15,7 +45,23 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
         protected abstract Matrix<T> CreateSparseZero(int rows, int columns);
         protected abstract Vector<T> CreateVectorZero(int size);
         protected abstract Vector<T> CreateVectorRandom(int size, int seed);
-        protected abstract T Zero { get; }
+
+        protected readonly T Zero;
+        protected readonly dynamic Dense;
+        protected readonly dynamic Sparse;
+        protected readonly dynamic Diagonal;
+        protected readonly dynamic DenseVector;
+        protected readonly dynamic SparseVector;
+
+        protected MatrixStructureTheory(T zero, Type dense, Type sparse, Type diagonal, Type denseVector, Type sparseVector)
+        {
+            Zero = zero;
+            Dense = new StaticDynamicWrapper(dense);
+            Sparse = new StaticDynamicWrapper(sparse);
+            Diagonal = new StaticDynamicWrapper(diagonal);
+            DenseVector = new StaticDynamicWrapper(denseVector);
+            SparseVector = new StaticDynamicWrapper(sparseVector);
+        }
 
         protected Matrix<T> CreateDenseFor(Matrix<T> m, int rows = -1, int columns = -1, int seed = 1)
         {
@@ -31,7 +77,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
                 : CreateVectorZero(size);
         }
 
-        [Theory, Timeout(200)]
+        [Theory]
         public void IsEqualToItself(Matrix<T> matrix)
         {
             Assert.That(matrix, Is.EqualTo(matrix));
@@ -42,7 +88,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.IsTrue((object) matrix == matrix);
         }
 
-        [Theory, Timeout(200)]
+        [Theory]
         public void IsNotEqualToOthers(Matrix<T> left, Matrix<T> right)
         {
             // IF (assuming we don't have duplicate data points)
@@ -57,7 +103,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.IsFalse((object) left == right);
         }
 
-        [Theory, Timeout(200)]
+        [Theory]
         public void IsNotEqualToNonMatrixType(Matrix<T> matrix)
         {
             Assert.That(matrix, Is.Not.EqualTo(2));
@@ -67,7 +113,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.IsFalse(matrix == (object) 2);
         }
 
-        [Theory, Timeout(200)]
+        [Theory]
         public void CanClone(Matrix<T> matrix)
         {
             var clone = matrix.Clone();
@@ -77,7 +123,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(clone.ColumnCount, Is.EqualTo(matrix.ColumnCount));
         }
 
-        [Theory, Timeout(200)]
+        [Theory]
         public void CanCloneUsingICloneable(Matrix<T> matrix)
         {
             var clone = (Matrix<T>) ((ICloneable) matrix).Clone();
@@ -87,7 +133,7 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(clone.ColumnCount, Is.EqualTo(matrix.ColumnCount));
         }
 
-        [Theory, Timeout(200)]
+        [Theory]
         public void CanCopyTo(Matrix<T> matrix)
         {
             var dense = CreateDenseZero(matrix.RowCount, matrix.ColumnCount);
@@ -106,13 +152,13 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.CopyTo(CreateDenseZero(matrix.RowCount, matrix.ColumnCount + 1)), Throws.ArgumentException);
         }
 
-        [Theory, Timeout(200)]
+        [Theory]
         public void CanGetHashCode(Matrix<T> matrix)
         {
             Assert.That(matrix.GetHashCode(), Is.Not.EqualTo(matrix.CreateMatrix(matrix.RowCount, matrix.ColumnCount).GetHashCode()));
         }
 
-        [Theory, Timeout(200)]
+        [Theory]
         public void CanClear(Matrix<T> matrix)
         {
             var cleared = matrix.Clone();
@@ -120,21 +166,21 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(cleared, Is.EqualTo(matrix.CreateMatrix(matrix.RowCount, matrix.ColumnCount)));
         }
 
-        [Theory, Timeout(200)]
+        [Theory]
         public void CanClearSubMatrix(Matrix<T> matrix)
         {
             var cleared = matrix.Clone();
             Assume.That(cleared.RowCount, Is.GreaterThanOrEqualTo(2));
             Assume.That(cleared.ColumnCount, Is.GreaterThanOrEqualTo(2));
 
-            cleared.Storage.Clear(0,2,1,1);
+            cleared.Storage.Clear(0, 2, 1, 1);
             Assert.That(cleared.At(0, 0), Is.EqualTo(matrix.At(0, 0)));
             Assert.That(cleared.At(1, 0), Is.EqualTo(matrix.At(1, 0)));
             Assert.That(cleared.At(0, 1), Is.EqualTo(Zero));
             Assert.That(cleared.At(1, 1), Is.EqualTo(Zero));
         }
 
-        [Theory, Timeout(200)]
+        [Theory]
         public void CanToArray(Matrix<T> matrix)
         {
             var array = matrix.ToArray();
@@ -149,29 +195,29 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             }
         }
 
-        [Theory, Timeout(200)]
+        [Theory]
         public void CanToColumnWiseArray(Matrix<T> matrix)
         {
             var array = matrix.ToColumnWiseArray();
-            Assert.That(array.Length, Is.EqualTo(matrix.RowCount * matrix.ColumnCount));
+            Assert.That(array.Length, Is.EqualTo(matrix.RowCount*matrix.ColumnCount));
             for (int i = 0; i < array.Length; i++)
             {
-                Assert.That(array[i], Is.EqualTo(matrix[i % matrix.RowCount, i / matrix.RowCount]));
+                Assert.That(array[i], Is.EqualTo(matrix[i%matrix.RowCount, i/matrix.RowCount]));
             }
         }
 
-        [Theory, Timeout(200)]
+        [Theory]
         public void CanToRowWiseArray(Matrix<T> matrix)
         {
             var array = matrix.ToRowWiseArray();
-            Assert.That(array.Length, Is.EqualTo(matrix.RowCount * matrix.ColumnCount));
+            Assert.That(array.Length, Is.EqualTo(matrix.RowCount*matrix.ColumnCount));
             for (int i = 0; i < array.Length; i++)
             {
-                Assert.That(array[i], Is.EqualTo(matrix[i / matrix.ColumnCount, i % matrix.ColumnCount]));
+                Assert.That(array[i], Is.EqualTo(matrix[i/matrix.ColumnCount, i%matrix.ColumnCount]));
             }
         }
 
-        [Theory, Timeout(200)]
+        [Theory]
         public void CanCreateSameType(Matrix<T> matrix)
         {
             var empty = matrix.CreateMatrix(5, 6);
@@ -183,85 +229,155 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
             Assert.That(() => matrix.CreateMatrix(-1, -1), Throws.InstanceOf<ArgumentOutOfRangeException>());
         }
 
-        [Test, Timeout(200)]
+        [Test]
-        public void CanCreateFromColumns()
+        public void CanCreateDenseFromMultiDimArray()
         {
-            var column1 = CreateVectorRandom(1, 0);
+            T[,] array = CreateDenseRandom(4, 3, 0).ToArray();
-            var column2 = CreateVectorRandom(4, 1);
+            var matrix = Dense.OfArray(array);
-            var column3 = CreateVectorRandom(2, 3);
+            Assert.That(matrix.GetType().Name, Is.EqualTo("DenseMatrix"));
-
+            Assert.That(matrix.RowCount, Is.EqualTo(4));
-            var matrix = Matrix<T>.CreateFromColumns(new List<Vector<T>>
+            Assert.That(matrix.ColumnCount, Is.EqualTo(3));
-                {
+            for (int i = 0; i < 4; i++)
-                    column1,
+                for (int j = 0; j < 3; j++)
-                    column2,
+                    Assert.That(matrix[i, j], Is.EqualTo(array[i, j]));
-                    column3
+        }
-                });
 
+        [Test]
+        public void CanCreateSparseFromMultiDimArray()
+        {
+            T[,] array = CreateDenseRandom(4, 3, 0).ToArray();
+            var matrix = Sparse.OfArray(array);
+            Assert.That(matrix.GetType().Name, Is.EqualTo("SparseMatrix"));
             Assert.That(matrix.RowCount, Is.EqualTo(4));
             Assert.That(matrix.ColumnCount, Is.EqualTo(3));
+            for (int i = 0; i < 4; i++)
+                for (int j = 0; j < 3; j++)
+                    Assert.That(matrix[i, j], Is.EqualTo(array[i, j]));
+        }
 
-            Assert.That(matrix[0, 0], Is.EqualTo(column1[0]));
+        [Test]
-            Assert.That(matrix[0, 1], Is.EqualTo(column2[0]));
+        public void CanCreateDenseFromJaggedArray()
-            Assert.That(matrix[1, 1], Is.EqualTo(column2[1]));
+        {
-            Assert.That(matrix[2, 1], Is.EqualTo(column2[2]));
+            T[][] array = new[]
-            Assert.That(matrix[3, 1], Is.EqualTo(column2[3]));
+                {
-            Assert.That(matrix[0, 2], Is.EqualTo(column3[0]));
+                    CreateVectorRandom(4, 0).ToArray(),
-            Assert.That(matrix[1, 2], Is.EqualTo(column3[1]));
+                    CreateVectorRandom(4, 1).ToArray(),
-
+                    CreateVectorRandom(4, 3).ToArray()
-            Assert.That(matrix[1, 0], Is.EqualTo(Zero));
+                };
-            Assert.That(matrix[2, 0], Is.EqualTo(Zero));
+            var matrix = Dense.OfRows(3, 4, array);
-            Assert.That(matrix[3, 0], Is.EqualTo(Zero));
+            Assert.That(matrix.GetType().Name, Is.EqualTo("DenseMatrix"));
-            Assert.That(matrix[2, 2], Is.EqualTo(Zero));
+            Assert.That(matrix.RowCount, Is.EqualTo(3));
-            Assert.That(matrix[3, 2], Is.EqualTo(Zero));
+            Assert.That(matrix.ColumnCount, Is.EqualTo(4));
+            for (int i = 0; i < 3; i++)
+                for (int j = 0; j < 4; j++)
+                    Assert.That(matrix[i, j], Is.EqualTo(array[i][j]));
         }
 
-        [Test, Timeout(200)]
+        [Test]
-        public void CanCreateFromRows()
+        public void CanCreateSparseFromJaggedArray()
         {
-            var row1 = CreateVectorRandom(1, 0);
+            T[][] array = new[]
-            var row2 = CreateVectorRandom(4, 1);
+                {
-            var row3 = CreateVectorRandom(2, 3);
+                    CreateVectorRandom(4, 0).ToArray(),
+                    CreateVectorRandom(4, 1).ToArray(),
+                    CreateVectorRandom(4, 3).ToArray()
+                };
+            var matrix = Sparse.OfRows(3, 4, array);
+            Assert.That(matrix.GetType().Name, Is.EqualTo("SparseMatrix"));
+            Assert.That(matrix.RowCount, Is.EqualTo(3));
+            Assert.That(matrix.ColumnCount, Is.EqualTo(4));
+            for (int i = 0; i < 3; i++)
+                for (int j = 0; j < 4; j++)
+                    Assert.That(matrix[i, j], Is.EqualTo(array[i][j]));
+        }
 
-            var matrix = Matrix<T>.CreateFromRows(new List<Vector<T>>
+        [Test]
+        public void CanCreateDenseFromColumnVectors()
+        {
+            var columns = new[]
                 {
-                    row1,
+                    CreateVectorRandom(4, 0),
-                    row2,
+                    CreateVectorRandom(4, 1),
-                    row3
+                    CreateVectorRandom(4, 3)
-                });
+                };
+            var matrix = Dense.OfColumns(4, 3, columns);
+            Assert.That(matrix.GetType().Name, Is.EqualTo("DenseMatrix"));
+            Assert.That(matrix.RowCount, Is.EqualTo(4));
+            Assert.That(matrix.ColumnCount, Is.EqualTo(3));
+            for (int i = 0; i < 4; i++)
+                for (int j = 0; j < 3; j++)
+                    Assert.That(matrix[i, j], Is.EqualTo(columns[j][i]));
+        }
+
+        [Test]
+        public void CanCreateSparseFromColumnVectors()
+        {
+            var columns = new[]
+                {
+                    CreateVectorRandom(4, 0),
+                    CreateVectorRandom(4, 1),
+                    CreateVectorRandom(4, 3)
+                };
+            var matrix = Sparse.OfColumns(4, 3, columns);
+            Assert.That(matrix.GetType().Name, Is.EqualTo("SparseMatrix"));
+            Assert.That(matrix.RowCount, Is.EqualTo(4));
+            Assert.That(matrix.ColumnCount, Is.EqualTo(3));
+            for (int i = 0; i < 4; i++)
+                for (int j = 0; j < 3; j++)
+                    Assert.That(matrix[i, j], Is.EqualTo(columns[j][i]));
+        }
 
+        [Test]
+        public void CanCreateDenseFromRowVectors()
+        {
+            var rows = new[]
+                {
+                    CreateVectorRandom(4, 0),
+                    CreateVectorRandom(4, 1),
+                    CreateVectorRandom(4, 3)
+                };
+            var matrix = Dense.OfRows(3, 4, rows);
+            Assert.That(matrix.GetType().Name, Is.EqualTo("DenseMatrix"));
             Assert.That(matrix.RowCount, Is.EqualTo(3));
             Assert.That(matrix.ColumnCount, Is.EqualTo(4));
+            for (int j = 0; j < 4; j++)
+                for (int i = 0; i < 3; i++)
+                    Assert.That(matrix[i, j], Is.EqualTo(rows[i][j]));
+        }
 
-            Assert.That(matrix[0, 0], Is.EqualTo(row1[0]));
+        [Test]
-            Assert.That(matrix[1, 0], Is.EqualTo(row2[0]));
+        public void CanCreateSparseFromRowVectors()
-            Assert.That(matrix[1, 1], Is.EqualTo(row2[1]));
+        {
-            Assert.That(matrix[1, 2], Is.EqualTo(row2[2]));
+            var rows = new[]
-            Assert.That(matrix[1, 3], Is.EqualTo(row2[3]));
+                {
-            Assert.That(matrix[2, 0], Is.EqualTo(row3[0]));
+                    CreateVectorRandom(4, 0),
-            Assert.That(matrix[2, 1], Is.EqualTo(row3[1]));
+                    CreateVectorRandom(4, 1),
-
+                    CreateVectorRandom(4, 3)
-            Assert.That(matrix[0, 1], Is.EqualTo(Zero));
+                };
-            Assert.That(matrix[0, 2], Is.EqualTo(Zero));
+            var matrix = Sparse.OfRows(3, 4, rows);
-            Assert.That(matrix[0, 3], Is.EqualTo(Zero));
+            Assert.That(matrix.GetType().Name, Is.EqualTo("SparseMatrix"));
-            Assert.That(matrix[2, 2], Is.EqualTo(Zero));
+            Assert.That(matrix.RowCount, Is.EqualTo(3));
-            Assert.That(matrix[2, 3], Is.EqualTo(Zero));
+            Assert.That(matrix.ColumnCount, Is.EqualTo(4));
+            for (int j = 0; j < 4; j++)
+                for (int i = 0; i < 3; i++)
+                    Assert.That(matrix[i, j], Is.EqualTo(rows[i][j]));
         }
 
-        [Test, Timeout(200)]
+        [Test]
         public void CanEnumerateWithIndex()
         {
             var dense = CreateDenseRandom(2, 3, 0);
-            using(var enumerator = dense.IndexedEnumerator().GetEnumerator())
+            using (var enumerator = dense.IndexedEnumerator().GetEnumerator())
-            for (int i = 0; i < 2; i++)
+                for (int i = 0; i < 2; i++)
-            {
-                for (int j = 0; j < 3; j++)
                 {
-                    enumerator.MoveNext();
+                    for (int j = 0; j < 3; j++)
-                    Assert.AreEqual(i, enumerator.Current.Item1);
+                    {
-                    Assert.AreEqual(j, enumerator.Current.Item2);
+                        enumerator.MoveNext();
-                    Assert.AreEqual(dense[i, j], enumerator.Current.Item3);
+                        Assert.AreEqual(i, enumerator.Current.Item1);
+                        Assert.AreEqual(j, enumerator.Current.Item2);
+                        Assert.AreEqual(dense[i, j], enumerator.Current.Item3);
+                    }
                 }
-            }
         }
     }
 }

src/UnitTests/LinearAlgebraTests/Single/MatrixStructureTheory.cs

@@ -40,6 +40,11 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
     [TestFixture]
     public class MatrixStructureTheory : MatrixStructureTheory<float>
     {
+        public MatrixStructureTheory()
+            : base(0f, typeof(DenseMatrix), typeof(SparseMatrix), typeof(DiagonalMatrix), typeof(DenseVector), typeof(SparseVector))
+        {
+        }
+
         [Datapoints]
         Matrix<float>[] _matrices = new Matrix<float>[]
             {
@@ -90,10 +95,5 @@ namespace MathNet.Numerics.UnitTests.LinearAlgebraTests.Single
             var dist = new Normal {RandomSource = new MersenneTwister(seed)};
             return new DenseVector(dist.Samples().Select(d => (float) d).Take(size).ToArray());
         }
-
-        protected override float Zero
-        {
-            get { return 0f; }
-        }
     }
 }

src/UnitTests/LinearAlgebraTests/StaticDynamicWrapper.cs

@@ -0,0 +1,78 @@
+// <copyright file="StaticDynamicWrapper.cs" company="Math.NET">
+// Math.NET Numerics, part of the Math.NET Project
+// 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>
+
+using System;
+using System.Dynamic;
+using System.Reflection;
+
+namespace MathNet.Numerics.UnitTests.LinearAlgebraTests
+{
+    /// <summary>
+    /// Helper to allow calling static members of dynamic types.
+    /// Usefull to test static methods of e.g. all dense matrix types.
+    /// </summary>
+    public class StaticDynamicWrapper : DynamicObject
+    {
+        readonly Type _type;
+
+        public StaticDynamicWrapper(Type type)
+        {
+            _type = type;
+        }
+
+        // Handle static properties
+        public override bool TryGetMember(GetMemberBinder binder, out object result)
+        {
+            PropertyInfo prop = _type.GetProperty(binder.Name, BindingFlags.FlattenHierarchy | BindingFlags.Static | BindingFlags.Public);
+            if (prop == null)
+            {
+                result = null;
+                return false;
+            }
+
+            result = prop.GetValue(null, null);
+            return true;
+        }
+
+        // Handle static methods
+        public override bool TryInvokeMember(InvokeMemberBinder binder, object[] args, out object result)
+        {
+            MethodInfo method = _type.GetMethod(binder.Name, BindingFlags.FlattenHierarchy | BindingFlags.Static | BindingFlags.Public);
+            if (method == null)
+            {
+                result = null;
+                return false;
+            }
+
+            result = method.Invoke(null, args);
+            return true;
+        }
+    }
+}

src/UnitTests/UnitTests.csproj

@@ -745,6 +745,7 @@
       <SubType>Code</SubType>
     </Compile>
     <Compile Include="LinearAlgebraTests\Double\VectorArithmeticTheory.cs" />
+    <Compile Include="LinearAlgebraTests\StaticDynamicWrapper.cs" />
     <Compile Include="LinearAlgebraTests\VectorArithmeticTheory.cs" />
     <Compile Include="MatrixHelpers.cs" />
     <Compile Include="NumberTheoryTests\GcdRelatedTest.cs" />