7 #ifndef UPPER_HESSENBERG_QR_H 8 #define UPPER_HESSENBERG_QR_H 42 template <
typename Scalar =
double>
76 const Scalar xabs = x * xsign;
77 const Scalar yabs = y * ysign;
156 if (m_n != mat.cols())
157 throw std::invalid_argument(
"UpperHessenbergQR: matrix must be square");
161 m_rot_cos.
resize(m_n - 1);
162 m_rot_sin.
resize(m_n - 1);
165 std::copy(mat.data(), mat.data() + mat.size(), m_mat_T.
data());
166 m_mat_T.diagonal().array() -=
m_shift;
170 const Index
n1 = m_n - 1;
171 for (Index
i = 0;
i <
n1;
i++)
177 std::fill(Tii + 2, Tii + m_n -
i,
Scalar(0));
196 for (Index
j =
i + 1;
j <
m_n;
j++, ptr +=
m_n)
199 ptr[0] = c * tmp - s * ptr[1];
200 ptr[1] = s * tmp + c * ptr[1];
223 throw std::logic_error(
"UpperHessenbergQR: need to call compute() first");
238 throw std::logic_error(
"UpperHessenbergQR: need to call compute() first");
242 std::copy(m_mat_T.
data(), m_mat_T.
data() + m_mat_T.size(), dest.
data());
245 const Index
n1 = m_n - 1;
246 for (Index
i = 0;
i <
n1;
i++)
256 const Index i2 =
i + 2;
257 for (Index
j = 0;
j < i2;
j++)
260 Yi[
j] = c * tmp - s * Yi1[
j];
261 Yi1[
j] = s * tmp + c * Yi1[
j];
270 dest.diagonal().array() +=
m_shift;
285 throw std::logic_error(
"UpperHessenbergQR: need to call compute() first");
287 for (Index
i = m_n - 2;
i >= 0;
i--)
295 Y[
i] = c * tmp + s * Y[
i + 1];
296 Y[
i + 1] = -s * tmp + c * Y[
i + 1];
312 throw std::logic_error(
"UpperHessenbergQR: need to call compute() first");
314 const Index
n1 = m_n - 1;
315 for (Index
i = 0;
i <
n1;
i++)
323 Y[
i] = c * tmp - s * Y[
i + 1];
324 Y[
i + 1] = s * tmp + c * Y[
i + 1];
341 throw std::logic_error(
"UpperHessenbergQR: need to call compute() first");
343 RowVector Yi(Y.cols()), Yi1(Y.cols());
344 for (Index
i = m_n - 2;
i >= 0;
i--)
351 Yi.noalias() = Y.row(
i);
352 Yi1.noalias() = Y.row(
i + 1);
353 Y.row(
i) = c * Yi + s * Yi1;
354 Y.row(
i + 1) = -s * Yi + c * Yi1;
371 throw std::logic_error(
"UpperHessenbergQR: need to call compute() first");
373 RowVector Yi(Y.cols()), Yi1(Y.cols());
374 const Index
n1 = m_n - 1;
375 for (Index
i = 0;
i <
n1;
i++)
382 Yi.noalias() = Y.row(
i);
383 Yi1.noalias() = Y.row(
i + 1);
384 Y.row(
i) = c * Yi - s * Yi1;
385 Y.row(
i + 1) = s * Yi + c * Yi1;
402 throw std::logic_error(
"UpperHessenbergQR: need to call compute() first");
416 Scalar *Y_col_i, *Y_col_i1;
417 const Index
n1 = m_n - 1;
418 const Index nrow = Y.rows();
419 for (Index
i = 0;
i <
n1;
i++)
424 Y_col_i = &Y.coeffRef(0,
i);
425 Y_col_i1 = &Y.coeffRef(0,
i + 1);
426 for (Index
j = 0;
j < nrow;
j++)
429 Y_col_i[
j] = c * tmp - s * Y_col_i1[
j];
430 Y_col_i1[
j] = s * tmp + c * Y_col_i1[
j];
448 throw std::logic_error(
"UpperHessenbergQR: need to call compute() first");
451 for (Index
i = m_n - 2;
i >= 0;
i--)
458 Yi.noalias() = Y.col(
i);
459 Y.col(
i) = c * Yi + s * Y.col(
i + 1);
460 Y.col(
i + 1) = -s * Yi + c * Y.col(
i + 1);
474 template <
typename Scalar =
double>
528 this->m_n = mat.rows();
529 if (this->m_n != mat.cols())
530 throw std::invalid_argument(
"TridiagQR: matrix must be square");
532 this->m_shift = shift;
533 m_T_diag.
resize(this->m_n);
534 m_T_lsub.
resize(this->m_n - 1);
535 m_T_usub.
resize(this->m_n - 1);
536 m_T_usub2.
resize(this->m_n - 2);
537 this->m_rot_cos.
resize(this->m_n - 1);
538 this->m_rot_sin.
resize(this->m_n - 1);
540 m_T_diag.array() = mat.diagonal().array() - this->
m_shift;
541 m_T_lsub.noalias() = mat.diagonal(-1);
542 m_T_usub.noalias() = m_T_lsub;
546 *
s = this->m_rot_sin.
data(),
548 const Index
n1 = this->m_n - 1;
549 for (Index
i = 0;
i <
n1;
i++)
593 this->m_computed =
true;
605 if (!this->m_computed)
606 throw std::logic_error(
"TridiagQR: need to call compute() first");
608 Matrix
R = Matrix::Zero(this->m_n, this->m_n);
609 R.diagonal().noalias() = m_T_diag;
610 R.diagonal(1).noalias() = m_T_usub;
611 R.diagonal(2).noalias() = m_T_usub2;
625 if (!this->m_computed)
626 throw std::logic_error(
"TridiagQR: need to call compute() first");
629 dest.
resize(this->m_n, this->m_n);
631 dest.diagonal().noalias() = m_T_diag;
641 const Index
n1 = this->m_n - 1;
642 for (Index
i = 0;
i <
n1;
i++)
648 m22 = m_T_diag.
coeff(
i + 1);
657 dest.diagonal(1).noalias() = dest.diagonal(-1);
660 dest.diagonal().array() += this->
m_shift;
670 #endif // UPPER_HESSENBERG_QR_H void apply_YQ(GenericMatrix Y) const
virtual void compute(ConstGenericMatrix &mat, const Scalar &shift=Scalar(0))
void apply_QY(Vector &Y) const
EIGEN_DEVICE_FUNC Derived & setZero(Index size)
void compute(ConstGenericMatrix &mat, const Scalar &shift=Scalar(0))
void apply_QY(GenericMatrix Y) const
UpperHessenbergQR(Index size)
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar * data() const
Rot2 R(Rot2::fromAngle(0.1))
EIGEN_DEVICE_FUNC const SqrtReturnType sqrt() const
const Eigen::Ref< const Matrix > ConstGenericMatrix
UpperHessenbergQR(ConstGenericMatrix &mat, const Scalar &shift=Scalar(0))
Eigen::Array< Scalar, Eigen::Dynamic, 1 > Array
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar & coeffRef(Index rowId, Index colId)
Eigen::Ref< Matrix > GenericMatrix
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void resize(Index rows, Index cols)
EIGEN_DEFAULT_DENSE_INDEX_TYPE Index
The Index type as used for the API.
void apply_QtY(GenericMatrix Y) const
virtual ~UpperHessenbergQR()
Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > Matrix
virtual void matrix_QtHQ(Matrix &dest) const
Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > Vector
A matrix or vector expression mapping an existing expression.
void matrix_QtHQ(Matrix &dest) const
const Eigen::Ref< const Matrix > ConstGenericMatrix
void apply_QtY(Vector &Y) const
void apply_YQt(GenericMatrix Y) const
Eigen::Matrix< Scalar, 1, Eigen::Dynamic > RowVector
Eigen::Matrix< Scalar, Eigen::Dynamic, Eigen::Dynamic > Matrix
TridiagQR(ConstGenericMatrix &mat, const Scalar &shift=Scalar(0))
virtual Matrix matrix_R() const
Eigen::Matrix< Scalar, Eigen::Dynamic, 1 > Vector
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar & coeff(Index rowId, Index colId) const
static void compute_rotation(const Scalar &x, const Scalar &y, Scalar &r, Scalar &c, Scalar &s)