19 template <
class T,
unsigned M,
unsigned N>
21 Matrix<T,M,N>
const& a,
31 template <
class T,
unsigned M,
unsigned N>
33 Matrix<T,M,N>
const& r,
45 template <
class T,
unsigned M,
unsigned N>
47 Matrix<T,M,N>
const& r,
48 Vector<T,M>
const& b, Vector<T,N>& x);
57 template <
class T,
unsigned M,
unsigned N>
58 bool solveQR(Matrix<T,M,N>
const& a,
59 Vector<T,M>
const& b, Vector<T,N>& x);
61 template <
class T,
unsigned M>
62 void reduceToHessenberg(Matrix<T,M,M>
const& a, Matrix<T,M,M>& q,
75 template <
class T,
unsigned M>
76 bool eigenQR(Matrix<T,M,M>
const& a,
void backsubUT(Matrix< T, M, N > const &r, Vector< T, M > const &b, Vector< T, N > &x)
solves Rx = b for upper triangular R
bool solveQR(Matrix< T, M, N > const &a, Vector< T, M > const &b, Vector< T, N > &x)
solves Ax = b using A's QR factorization
unsigned decomposeQR(Matrix< T, M, N > const &a, Matrix< T, M, M > &q, Matrix< T, M, N > &r)
finds the QR decomposition of A
Small compile-time and run-time linear algebra matrices.
void solveFromQR(Matrix< T, M, M > const &q, Matrix< T, M, N > const &r, Vector< T, M > const &b, Vector< T, N > &x)
solves Ax = b given A's QR factorization
bool eigenQR(Matrix< T, M, M > const &a, Matrix< T, M, M > &l, Matrix< T, M, M > &q, unsigned max_iters)
computes the eigendecomposition of A