/// <summary>
/// Solves A x = b.
/// </summary>
/// <param name="rhs">The right-hand side vector b.</param>
/// <returns>The solution vector x.</returns>
/// <exception cref="ArgumentNullException"><paramref name="rhs"/> is <c>null</c>.</exception>
/// <exception cref="DimensionMismatchException">The dimension of <paramref name="rhs"/> is not the same as the dimension of the matrix.</exception>
public ColumnVector Solve(IReadOnlyList <double> rhs)
{
if (rhs == null)
{
throw new ArgumentNullException(nameof(rhs));
}
if (rhs.Count != dimension)
{
throw new DimensionMismatchException();
}
// copy rhs into an array, reshuffling according to permutations
double[] x = new double[dimension];
for (int i = 0; i < x.Length; i++)
{
x[i] = rhs[permutation[i]];
}
// solve Ly=b and Ux=y
Blas2.dTrsv(false, true, luStore, 0, 1, dimension, x, 0, 1, dimension);
//SquareMatrixAlgorithms.SolveLowerLeftTriangular(luStore, x, 0, dimension);
Blas2.dTrsv(true, false, luStore, 0, 1, dimension, x, 0, 1, dimension);
//SquareMatrixAlgorithms.SolveUpperRightTriangular(luStore, x, 0, dimension);
return(new ColumnVector(x, dimension));
}
/// <summary>
/// Solve the system A x = b.
/// </summary>
/// <param name="rhs">The right-hand-side b.</param>
/// <returns>The column vector x for which A x is closest to b.</returns>
public ColumnVector Solve(IReadOnlyList <double> rhs)
{
if (rhs == null)
{
throw new ArgumentNullException(nameof(rhs));
}
if (rhs.Count != rows)
{
throw new DimensionMismatchException();
}
// BLAS requires an array, but doesn't modify it, so if given one, use it directly
double[] x = rhs as double[];
if (x == null)
{
x = new double[rows];
rhs.CopyTo(x, 0);
}
// Q^T x is a row-length vector, but we only need the first cols entries
// so truncate Q^T to cols X rows, so that Q^T x is only of length cols
double[] y = new double[cols];
Blas2.dGemv(qtStore, 0, 1, rows, x, 0, 1, y, 0, 1, cols, rows);
MatrixAlgorithms.SolveUpperRightTriangular(rStore, rows, cols, y, 0);
return(new ColumnVector(y, cols));
}
/// <summary>
/// Solve the system A x = b.
/// </summary>
/// <param name="rhs">The right-hand-side b.</param>
/// <returns>The column vector x for which A x is closest to b.</returns>
public ColumnVector Solve(IList <double> rhs)
{
if (rhs == null)
{
throw new ArgumentNullException(nameof(rhs));
}
if (rhs.Count != rows)
{
throw new DimensionMismatchException();
}
// copy rhs into an array, if necessary
double[] x;
if (rhs is double[])
{
x = (double[])rhs;
}
else
{
x = new double[rows];
rhs.CopyTo(x, 0);
}
// Q^T x is a row-length vector, but we only need the first cols entries
// so truncate Q^T to cols X rows, so that Q^T x is only of length cols
double[] y = new double[cols];
Blas2.dGemv(qtStore, 0, 1, rows, x, 0, 1, y, 0, 1, cols, rows);
MatrixAlgorithms.SolveUpperRightTriangular(rStore, rows, cols, y, 0);
return(new ColumnVector(y, cols));
}
/// <summary>
/// Computes the product of a rectangular matrix and a column vector.
/// </summary>
/// <param name="A">The matrix.</param>
/// <param name="v">The column vector.</param>
/// <returns>The column vector Av.</returns>
/// <exception cref="ArgumentNullException"><paramref name="A"/> or <paramref name="v"/> is null.</exception>
/// <exception cref="DimensionMismatchException">The column count of <paramref name="A"/> is not the same as the dimension of <paramref name="v"/>.</exception>
public static ColumnVector operator *(RectangularMatrix A, ColumnVector v)
{
if (A == null)
{
throw new ArgumentNullException(nameof(A));
}
if (v == null)
{
throw new ArgumentNullException(nameof(v));
}
if (A.cols != v.dimension)
{
throw new DimensionMismatchException();
}
double[] avStore = new double[A.rows];
Blas2.dGemv(A.store, A.offset, A.rowStride, A.colStride, v.store, v.offset, v.stride, avStore, 0, 1, A.rows, A.cols);
return(new ColumnVector(avStore, A.rows));
}
// mixed arithmetic
/// <summary>
/// Computes the product of a square matrix and a column vector.
/// </summary>
/// <param name="A">The matrix.</param>
/// <param name="v">The column vector.</param>
/// <returns>The column vector Av.</returns>
/// <exception cref="ArgumentNullException"><paramref name="A"/> or <paramref name="v"/> is null.</exception>
/// <exception cref="DimensionMismatchException">The dimension of <paramref name="A"/> is not the same as the dimension of <paramref name="v"/>.</exception>
public static ColumnVector operator *(SquareMatrix A, ColumnVector v)
{
if (A == null)
{
throw new ArgumentNullException("A");
}
if (v == null)
{
throw new ArgumentNullException("v");
}
if (A.dimension != v.dimension)
{
throw new DimensionMismatchException();
}
double[] avStore = new double[A.dimension];
Blas2.dGemv(A.store, 0, 1, A.dimension, v.store, v.offset, v.stride, avStore, 0, 1, A.dimension, A.dimension);
return(new ColumnVector(avStore, A.dimension));
}
/// <summary>
/// Solves the system of equations Ax = b, where A is the original, square matrix.
/// </summary>
/// <param name="rhs">The right-hand-side vector b.</param>
/// <returns>The solution vector x.</returns>
/// <exception cref="ArgumentNullException"><paramref name="rhs"/> is null.</exception>
/// <exception cref="DimensionMismatchException"><paramref name="rhs"/> does not have the same dimension as the original matrix.</exception>
/// <exception cref="InvalidOperationException">The original matrix is not square.</exception>
/// <remarks>
/// <para>For singular and nearly-singular matrices, this method operates differently than other solution methods like
/// <see cref="SquareQRDecomposition.Solve(IReadOnlyList{double})"/> and <see cref="LUDecomposition.Solve(IReadOnlyList{double})"/>.
/// For singular and nearly-singular matrices, those methods
/// tend to produce very large or even infinite solution components that delicately cancel to produce the required right-hand-side,
/// but have little significance to the problem being modeled because they arise from inverting very small singular values
/// of the original matrix that are dominated by floating point rounding errors. The SVD solution discards those singular
/// values to obtain a solution vector driven by the dominant, non-singular parts of A. While this solution does not have
/// the minimum achievable |Ax - b|, it is often more representative of the desired solution to the problem being modeled.
/// </para>
/// <para>For original matrices that are not singular or nearly-singular, this method will compute the same solution
/// as other methods.</para>
/// <para>This method is only available for square original matrices.</para>
/// </remarks>
public ColumnVector Solve(IReadOnlyList <double> rhs)
{
if (rows != cols)
{
throw new InvalidOperationException();
}
if (rhs == null)
{
throw new ArgumentNullException(nameof(rhs));
}
if (rhs.Count != cols)
{
throw new DimensionMismatchException();
}
double[] x = new double[rows];
double[] y = new double[rows];
rhs.CopyTo(x, 0);
Blas2.dGemv(utStore, 0, 1, rows, x, 0, 1, y, 0, 1, rows, rows);
double minValue = tolerance * wStore[0];
for (int i = 0; i < wStore.Length; i++)
{
double w = wStore[i];
if (w > minValue)
{
y[i] /= w;
}
else
{
y[i] = 0.0;
}
}
Array.Clear(x, 0, rows);
Blas2.dGemv(vStore, 0, 1, rows, y, 0, 1, x, 0, 1, rows, rows);
return(new ColumnVector(x, rows));
}
