namespace Mapack { using System; using System.IO; using System.Globalization; /// Matrix provides the fundamental operations of numerical linear algebra. public class Matrix { private double[][] data; private int rows; private int columns; private static Random random = new Random(); /// Constructs an empty matrix of the given size. /// Number of rows. /// Number of columns. public Matrix(int rows, int columns) { this.rows = rows; this.columns = columns; this.data = new double[rows][]; for (int i = 0; i < rows; i++) { this.data[i] = new double[columns]; } } /// Constructs a matrix of the given size and assigns a given value to all diagonal elements. /// Number of rows. /// Number of columns. /// Value to assign to the diagnoal elements. public Matrix(int rows, int columns, double value) { this.rows = rows; this.columns = columns; this.data = new double[rows][]; for (int i = 0; i < rows; i++) { data[i] = new double[columns]; } for (int i = 0; i < rows; i++) { data[i][i] = value; } } /// Constructs a matrix from the given array. /// The array the matrix gets constructed from. [CLSCompliant(false)] public Matrix(double[][] value) { this.rows = value.Length; this.columns = value[0].Length; for (int i = 0; i < rows; i++) { if (value[i].Length != columns) { throw new ArgumentException("Argument out of range."); } } this.data = value; } /// Determines weather two instances are equal. public override bool Equals(object obj) { return Equals(this, (Matrix) obj); } /// Determines weather two instances are equal. public static bool Equals(Matrix left, Matrix right) { if (((object) left) == ((object) right)) { return true; } if ((((object) left) == null) || (((object) right) == null)) { return false; } if ((left.Rows != right.Rows) || (left.Columns != right.Columns)) { return false; } for (int i = 0; i < left.Rows; i++) { for (int j = 0; j < left.Columns; j++) { if (left[i, j] != right[i, j]) { return false; } } } return true; } /// Serves as a hash function for a particular type, suitable for use in hashing algorithms and data structures like a hash table. public override int GetHashCode() { return (this.Rows + this.Columns); } internal double[][] Array { get { return this.data; } } /// Returns the number of columns. public int Rows { get { return this.rows; } } /// Returns the number of columns. public int Columns { get { return this.columns; } } /// Return if the matrix is a square matrix. public bool Square { get { return (rows == columns); } } /// Returns if the matrix is symmetric. public bool Symmetric { get { if (this.Square) { for (int i = 0; i < rows; i++) { for (int j = 0; j <= i; j++) { if (data[i][j] != data[j][i]) { return false; } } } return true; } return false; } } /// Access the value at the given location. public double this[int row, int column] { set { this.data[row][column] = value; } get { return this.data[row][column]; } } /// Returns a sub matrix extracted from the current matrix. /// Start row index /// End row index /// Start column index /// End column index public Matrix Submatrix(int startRow, int endRow, int startColumn, int endColumn) { if ((startRow > endRow) || (startColumn > endColumn) || (startRow < 0) || (startRow >= this.rows) || (endRow < 0) || (endRow >= this.rows) || (startColumn < 0) || (startColumn >= this.columns) || (endColumn < 0) || (endColumn >= this.columns)) { throw new ArgumentException("Argument out of range."); } Matrix X = new Matrix(endRow - startRow + 1, endColumn - startColumn + 1); double[][] x = X.Array; for (int i = startRow; i <= endRow; i++) { for (int j = startColumn; j <= endColumn; j++) { x[i - startRow][j - startColumn] = data[i][j]; } } return X; } /// Returns a sub matrix extracted from the current matrix. /// Array of row indices /// Array of column indices public Matrix Submatrix(int[] rowIndexes, int[] columnIndexes) { Matrix X = new Matrix(rowIndexes.Length, columnIndexes.Length); double[][] x = X.Array; for (int i = 0; i < rowIndexes.Length; i++) { for (int j = 0; j < columnIndexes.Length; j++) { if ((rowIndexes[i] < 0) || (rowIndexes[i] >= rows) || (columnIndexes[j] < 0) || (columnIndexes[j] >= columns)) { throw new ArgumentException("Argument out of range."); } x[i][j] = data[rowIndexes[i]][columnIndexes[j]]; } } return X; } /// Returns a sub matrix extracted from the current matrix. /// Starttial row index /// End row index /// Array of row indices public Matrix Submatrix(int i0, int i1, int[] c) { if ((i0 > i1) || (i0 < 0) || (i0 >= this.rows) || (i1 < 0) || (i1 >= this.rows)) { throw new ArgumentException("Argument out of range."); } Matrix X = new Matrix(i1 - i0 + 1, c.Length); double[][] x = X.Array; for (int i = i0; i <= i1; i++) { for (int j = 0; j < c.Length; j++) { if ((c[j] < 0) || (c[j] >= columns)) { throw new ArgumentException("Argument out of range."); } x[i - i0][j] = data[i][c[j]]; } } return X; } /// Returns a sub matrix extracted from the current matrix. /// Array of row indices /// Start column index /// End column index public Matrix Submatrix(int[] r, int j0, int j1) { if ((j0 > j1) || (j0 < 0) || (j0 >= columns) || (j1 < 0) || (j1 >= columns)) { throw new ArgumentException("Argument out of range."); } Matrix X = new Matrix(r.Length, j1-j0+1); double[][] x = X.Array; for (int i = 0; i < r.Length; i++) { for (int j = j0; j <= j1; j++) { if ((r[i] < 0) || (r[i] >= this.rows)) { throw new ArgumentException("Argument out of range."); } x[i][j - j0] = data[r[i]][j]; } } return X; } /// Creates a copy of the matrix. public Matrix Clone() { Matrix X = new Matrix(rows, columns); double[][] x = X.Array; for (int i = 0; i < rows; i++) { for (int j = 0; j < columns; j++) { x[i][j] = data[i][j]; } } return X; } /// Returns the transposed matrix. public Matrix Transpose() { Matrix X = new Matrix(columns, rows); double[][] x = X.Array; for (int i = 0; i < rows; i++) { for (int j = 0; j < columns; j++) { x[j][i] = data[i][j]; } } return X; } /// Returns the One Norm for the matrix. /// The maximum column sum. public double Norm1 { get { double f = 0; for (int j = 0; j < columns; j++) { double s = 0; for (int i = 0; i < rows; i++) { s += Math.Abs(data[i][j]); } f = Math.Max(f, s); } return f; } } /// Returns the Infinity Norm for the matrix. /// The maximum row sum. public double InfinityNorm { get { double f = 0; for (int i = 0; i < rows; i++) { double s = 0; for (int j = 0; j < columns; j++) s += Math.Abs(data[i][j]); f = Math.Max(f, s); } return f; } } /// Returns the Frobenius Norm for the matrix. /// The square root of sum of squares of all elements. public double FrobeniusNorm { get { double f = 0; for (int i = 0; i < rows; i++) { for (int j = 0; j < columns; j++) { f = Hypotenuse(f, data[i][j]); } } return f; } } /// Unary minus. public static Matrix Negate(Matrix value) { if (value == null) { throw new ArgumentNullException("value"); } int rows = value.Rows; int columns = value.Columns; double[][] data = value.Array; Matrix X = new Matrix(rows, columns); double[][] x = X.Array; for (int i = 0; i < rows; i++) { for (int j = 0; j < columns; j++) { x[i][j] = -data[i][j]; } } return X; } /// Unary minus. public static Matrix operator-(Matrix value) { if (value == null) { throw new ArgumentNullException("value"); } return Negate(value); } /// Matrix equality. public static bool operator==(Matrix left, Matrix right) { return Equals(left, right); } /// Matrix inequality. public static bool operator!=(Matrix left, Matrix right) { return !Equals(left, right); } /// Matrix addition. public static Matrix Add(Matrix left, Matrix right) { if (left == null) { throw new ArgumentNullException("left"); } if (right == null) { throw new ArgumentNullException("right"); } int rows = left.Rows; int columns = left.Columns; double[][] data = left.Array; if ((rows != right.Rows) || (columns != right.Columns)) { throw new ArgumentException("Matrix dimension do not match."); } Matrix X = new Matrix(rows, columns); double[][] x = X.Array; for (int i = 0; i < rows; i++) { for (int j = 0; j < columns; j++) { x[i][j] = data[i][j] + right[i,j]; } } return X; } /// Matrix addition. public static Matrix operator+(Matrix left, Matrix right) { if (left == null) { throw new ArgumentNullException("left"); } if (right == null) { throw new ArgumentNullException("right"); } return Add(left, right); } /// Matrix subtraction. public static Matrix Subtract(Matrix left, Matrix right) { if (left == null) { throw new ArgumentNullException("left"); } if (right == null) { throw new ArgumentNullException("right"); } int rows = left.Rows; int columns = left.Columns; double[][] data = left.Array; if ((rows != right.Rows) || (columns != right.Columns)) { throw new ArgumentException("Matrix dimension do not match."); } Matrix X = new Matrix(rows, columns); double[][] x = X.Array; for (int i = 0; i < rows; i++) { for (int j = 0; j < columns; j++) { x[i][j] = data[i][j] - right[i,j]; } } return X; } /// Matrix subtraction. public static Matrix operator-(Matrix left, Matrix right) { if (left == null) { throw new ArgumentNullException("left"); } if (right == null) { throw new ArgumentNullException("right"); } return Subtract(left, right); } /// Matrix-scalar multiplication. public static Matrix Multiply(Matrix left, double right) { if (left == null) { throw new ArgumentNullException("left"); } int rows = left.Rows; int columns = left.Columns; double[][] data = left.Array; Matrix X = new Matrix(rows, columns); double[][] x = X.Array; for (int i = 0; i < rows; i++) { for (int j = 0; j < columns; j++) { x[i][j] = data[i][j] * right; } } return X; } /// Matrix-scalar multiplication. public static Matrix operator*(Matrix left, double right) { if (left == null) { throw new ArgumentNullException("left"); } return Multiply(left, right); } /// Matrix-matrix multiplication. public static Matrix Multiply(Matrix left, Matrix right) { if (left == null) { throw new ArgumentNullException("left"); } if (right == null) { throw new ArgumentNullException("right"); } int rows = left.Rows; double[][] data = left.Array; if (right.Rows != left.columns) { throw new ArgumentException("Matrix dimensions are not valid."); } int columns = right.Columns; Matrix X = new Matrix(rows, columns); double[][] x = X.Array; int size = left.columns; double[] column = new double[size]; for (int j = 0; j < columns; j++) { for (int k = 0; k < size; k++) { column[k] = right[k,j]; } for (int i = 0; i < rows; i++) { double[] row = data[i]; double s = 0; for (int k = 0; k < size; k++) { s += row[k] * column[k]; } x[i][j] = s; } } return X; } /// Matrix-matrix multiplication. public static Matrix operator*(Matrix left, Matrix right) { if (left == null) { throw new ArgumentNullException("left"); } if (right == null) { throw new ArgumentNullException("right"); } return Multiply(left, right); } /// Returns the LHS solution vetor if the matrix is square or the least squares solution otherwise. public Matrix Solve(Matrix rightHandSide) { return (rows == columns) ? new LuDecomposition(this).Solve(rightHandSide) : new QrDecomposition(this).Solve(rightHandSide); } /// Inverse of the matrix if matrix is square, pseudoinverse otherwise. public Matrix Inverse { get { return this.Solve(Diagonal(rows, rows, 1.0)); } } /// Determinant if matrix is square. public double Determinant { get { return new LuDecomposition(this).Determinant; } } /// Returns the trace of the matrix. /// Sum of the diagonal elements. public double Trace { get { double trace = 0; for (int i = 0; i < Math.Min(rows, columns); i++) { trace += data[i][i]; } return trace; } } /// Returns a matrix filled with random values. public static Matrix Random(int rows, int columns) { Matrix X = new Matrix(rows, columns); double[][] x = X.Array; for (int i = 0; i < rows; i++) { for (int j = 0; j < columns; j++) { x[i][j] = random.NextDouble(); } } return X; } /// Returns a diagonal matrix of the given size. public static Matrix Diagonal(int rows, int columns, double value) { Matrix X = new Matrix(rows, columns); double[][] x = X.Array; for (int i = 0; i < rows; i++) { for (int j = 0; j < columns; j++) { x[i][j] = ((i == j) ? value : 0.0); } } return X; } /// Returns the matrix in a textual form. public override string ToString() { using (StringWriter writer = new StringWriter(CultureInfo.InvariantCulture)) { for (int i = 0; i < rows; i++) { for (int j = 0; j < columns; j++) { writer.Write(this.data[i][j] + " "); } writer.WriteLine(); } return writer.ToString(); } } private static double Hypotenuse(double a, double b) { if (Math.Abs(a) > Math.Abs(b)) { double r = b / a; return Math.Abs(a) * Math.Sqrt(1 + r * r); } if (b != 0) { double r = a / b; return Math.Abs(b) * Math.Sqrt(1 + r * r); } return 0.0; } } }