Implement and document MatrixBase::sqrt().

This commit is contained in:
Jitse Niesen
2011-05-09 22:20:20 +01:00
parent dac4bb640a
commit d7e3c949be
5 changed files with 134 additions and 4 deletions

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@@ -53,6 +53,7 @@ namespace Eigen {
* - \ref matrixbase_matrixfunction "MatrixBase::matrixFunction()", for computing general matrix functions
* - \ref matrixbase_sin "MatrixBase::sin()", for computing the matrix sine
* - \ref matrixbase_sinh "MatrixBase::sinh()", for computing the matrix hyperbolic sine
* - \ref matrixbase_sqrt "MatrixBase::sqrt()", for computing the matrix square root
*
* These methods are the main entry points to this module.
*
@@ -246,7 +247,7 @@ Output: \verbinclude MatrixSine.out
\section matrixbase_sinh const MatrixBase::sinh()
\section matrixbase_sinh MatrixBase::sinh()
Compute the matrix hyperbolic sine.
@@ -262,6 +263,74 @@ This function calls \ref matrixbase_matrixfunction "matrixFunction()" with StdSt
Example: \include MatrixSinh.cpp
Output: \verbinclude MatrixSinh.out
\section matrixbase_sqrt MatrixBase::sqrt()
Compute the matrix square root.
\code
const MatrixSquareRootReturnValue<Derived> MatrixBase<Derived>::sqrt() const
\endcode
\param[in] M invertible matrix whose square root is to be computed.
\returns expression representing the matrix square root of \p M.
The matrix square root of \f$ M \f$ is the matrix \f$ M^{1/2} \f$
whose square is the original matrix; so if \f$ S = M^{1/2} \f$ then
\f$ S^2 = M \f$.
In the <b>real case</b>, the matrix \f$ M \f$ should be invertible and
it should have no eigenvalues which are real and negative (pairs of
complex conjugate eigenvalues are allowed). In that case, the matrix
has a square root which is also real, and this is the square root
computed by this function.
The matrix square root is computed by first reducing the matrix to
quasi-triangular form with the real Schur decomposition. The square
root of the quasi-triangular matrix can then be computed directly. The
cost is approximately \f$ 25 n^3 \f$ real flops for the real Schur
decomposition and \f$ 3\frac13 n^3 \f$ real flops for the remainder
(though the computation time in practice is likely more than this
indicates).
Details of the algorithm can be found in: Nicholas J. Highan,
"Computing real square roots of a real matrix", <em>Linear Algebra
Appl.</em>, 88/89:405&ndash;430, 1987.
If the matrix is <b>positive-definite symmetric</b>, then the square
root is also positive-definite symmetric. In this case, it is best to
use SelfAdjointEigenSolver::operatorSqrt() to compute it.
In the <b>complex case</b>, the matrix \f$ M \f$ should be invertible;
this is a restriction of the algorithm. The square root computed by
this algorithm is the one whose eigenvalues have an argument in the
interval \f$ (-\frac12\pi, \frac12\pi] \f$. This is the usual branch
cut.
The computation is the same as in the real case, except that the
complex Schur decomposition is used to reduce the matrix to a
triangular matrix. The theoretical cost is the same. Details are in:
&Aring;ke Bj&ouml;rck and Scen Hammarling, "A Schur method for the
square root of a matrix", <em>Linear Algebra Appl.</em>,
52/53:127&ndash;140, 1983.
Example: The following program checks that the square root of
\f[ \left[ \begin{array}{cc}
\cos(\frac13\pi) & -\sin(\frac13\pi) \\
\sin(\frac13\pi) & \cos(\frac13\pi)
\end{array} \right], \f]
corresponding to a rotation over 60 degrees, is a rotation over 30 degrees:
\f[ \left[ \begin{array}{cc}
\cos(\frac16\pi) & -\sin(\frac16\pi) \\
\sin(\frac16\pi) & \cos(\frac16\pi)
\end{array} \right]. \f]
\include MatrixSquareRoot.cpp
Output: \verbinclude MatrixSquareRoot.out
\sa class RealSchur, class ComplexSchur, class MatrixSquareRoot,
SelfAdjointEigenSolver::operatorSqrt().
*/
}