public static DoubleMatrix2D Solve(DoubleMatrix2D A, DoubleMatrix2D B)
{
LUDecomposition lu = new LUDecomposition(A);
QRDecomposition qr = new QRDecomposition(B);
return(A.Rows == A.Columns ? (lu.Solve(B)) : (qr.Solve(B)));
}
/// <summary>
/// Returns the results of <i>ToString(A)</i> and additionally the results of all sorts of decompositions applied to the given matrix.
/// Useful for debugging or to quickly get the rough picture.
/// </summary>
/// <param name="matrix"></param>
/// <returns></returns>
/// <example>
/// <pre>
/// A = 3 x 3 matrix
/// 249 66 68
/// 104 214 108
/// 144 146 293
///
/// cond : 3.931600417472078
/// det : 9638870.0
/// norm1 : 497.0
/// norm2 : 473.34508217011404
/// normF : 516.873292016525
/// normInfinity : 583.0
/// rank : 3
/// trace : 756.0
///
/// density : 1.0
/// isDiagonal : false
/// isDiagonallyDominantByColumn : true
/// isDiagonallyDominantByRow : true
/// isIdentity : false
/// isLowerBidiagonal : false
/// isLowerTriangular : false
/// isNonNegative : true
/// isOrthogonal : false
/// isPositive : true
/// isSingular : false
/// isSkewSymmetric : false
/// isSquare : true
/// isStrictlyLowerTriangular : false
/// isStrictlyTriangular : false
/// isStrictlyUpperTriangular : false
/// isSymmetric : false
/// isTriangular : false
/// isTridiagonal : false
/// isUnitTriangular : false
/// isUpperBidiagonal : false
/// isUpperTriangular : false
/// isZero : false
/// lowerBandwidth : 2
/// semiBandwidth : 3
/// upperBandwidth : 2
///
/// -----------------------------------------------------------------------------
/// LUDecompositionQuick(A) --> isNonSingular(A), det(A), pivot, L, U, inverse(A)
/// -----------------------------------------------------------------------------
/// isNonSingular = true
/// det = 9638870.0
/// pivot = [0, 1, 2]
///
/// L = 3 x 3 matrix
/// 1 0 0
/// 0.417671 1 0
/// 0.578313 0.57839 1
///
/// U = 3 x 3 matrix
/// 249 66 68
/// 0 186.433735 79.598394
/// 0 0 207.635819
///
/// inverse(A) = 3 x 3 matrix
/// 0.004869 -0.000976 -0.00077
/// -0.001548 0.006553 -0.002056
/// -0.001622 -0.002786 0.004816
///
/// -----------------------------------------------------------------
/// QRDecomposition(A) --> hasFullRank(A), H, Q, R, pseudo inverse(A)
/// -----------------------------------------------------------------
/// hasFullRank = true
///
/// H = 3 x 3 matrix
/// 1.814086 0 0
/// 0.34002 1.903675 0
/// 0.470797 0.428218 2
///
/// Q = 3 x 3 matrix
/// -0.814086 0.508871 0.279845
/// -0.34002 -0.808296 0.48067
/// -0.470797 -0.296154 -0.831049
///
/// R = 3 x 3 matrix
/// -305.864349 -195.230337 -230.023539
/// 0 -182.628353 467.703164
/// 0 0 -309.13388
///
/// pseudo inverse(A) = 3 x 3 matrix
/// 0.006601 0.001998 -0.005912
/// -0.005105 0.000444 0.008506
/// -0.000905 -0.001555 0.002688
///
/// --------------------------------------------------------------------------
/// CholeskyDecomposition(A) --> isSymmetricPositiveDefinite(A), L, inverse(A)
/// --------------------------------------------------------------------------
/// isSymmetricPositiveDefinite = false
///
/// L = 3 x 3 matrix
/// 15.779734 0 0
/// 6.590732 13.059948 0
/// 9.125629 6.573948 12.903724
///
/// inverse(A) = Illegal operation or error: Matrix is not symmetric positive definite.
///
/// ---------------------------------------------------------------------
/// EigenvalueDecomposition(A) --> D, V, realEigenvalues, imagEigenvalues
/// ---------------------------------------------------------------------
/// realEigenvalues = 1 x 3 matrix
/// 462.796507 172.382058 120.821435
/// imagEigenvalues = 1 x 3 matrix
/// 0 0 0
///
/// D = 3 x 3 matrix
/// 462.796507 0 0
/// 0 172.382058 0
/// 0 0 120.821435
///
/// V = 3 x 3 matrix
/// -0.398877 -0.778282 0.094294
/// -0.500327 0.217793 -0.806319
/// -0.768485 0.66553 0.604862
///
/// ---------------------------------------------------------------------
/// SingularValueDecomposition(A) --> cond(A), rank(A), norm2(A), U, S, V
/// ---------------------------------------------------------------------
/// cond = 3.931600417472078
/// rank = 3
/// norm2 = 473.34508217011404
///
/// U = 3 x 3 matrix
/// 0.46657 -0.877519 0.110777
/// 0.50486 0.161382 -0.847982
/// 0.726243 0.45157 0.51832
///
/// S = 3 x 3 matrix
/// 473.345082 0 0
/// 0 169.137441 0
/// 0 0 120.395013
///
/// V = 3 x 3 matrix
/// 0.577296 -0.808174 0.116546
/// 0.517308 0.251562 -0.817991
/// 0.631761 0.532513 0.563301
/// </pre>
///</example>
public static String ToVerboseString(DoubleMatrix2D matrix)
{
/*
* StringBuilder buf = new StringBuilder();
* String unknown = "Illegal operation or error: ";
* String constructionException = "Illegal operation or error upon construction: ";
*
* buf.Append("------------------------------------------------------------------\n");
* buf.Append("LUDecomposition(A) --> isNonSingular, det, pivot, L, U, inverse(A)\n");
* buf.Append("------------------------------------------------------------------\n");
*/
String constructionException = "Illegal operation or error upon construction of ";
StringBuilder buf = new StringBuilder();
buf.Append("A = ");
buf.Append(matrix);
buf.Append("\n\n" + ToString(matrix));
buf.Append("\n\n" + Property.DEFAULT.ToString(matrix));
LUDecomposition lu = null;
try { lu = new LUDecomposition(matrix); }
catch (ArgumentException exc)
{
buf.Append("\n\n" + constructionException + " LUDecomposition: " + exc.Message);
}
if (lu != null)
{
buf.Append("\n\n" + lu.ToString());
}
QRDecomposition qr = null;
try { qr = new QRDecomposition(matrix); }
catch (ArgumentException exc)
{
buf.Append("\n\n" + constructionException + " QRDecomposition: " + exc.Message);
}
if (qr != null)
{
buf.Append("\n\n" + qr.ToString());
}
CholeskyDecomposition chol = null;
try { chol = new CholeskyDecomposition(matrix); }
catch (ArgumentException exc)
{
buf.Append("\n\n" + constructionException + " CholeskyDecomposition: " + exc.Message);
}
if (chol != null)
{
buf.Append("\n\n" + chol.ToString());
}
EigenvalueDecomposition eig = null;
try { eig = new EigenvalueDecomposition(matrix); }
catch (ArgumentException exc)
{
buf.Append("\n\n" + constructionException + " EigenvalueDecomposition: " + exc.Message);
}
if (eig != null)
{
buf.Append("\n\n" + eig.ToString());
}
SingularValueDecomposition svd = null;
try { svd = new SingularValueDecomposition(matrix); }
catch (ArgumentException exc)
{
buf.Append("\n\n" + constructionException + " SingularValueDecomposition: " + exc.Message);
}
if (svd != null)
{
buf.Append("\n\n" + svd.ToString());
}
return(buf.ToString());
}
