HouseholderQR.h
1// This file is part of Eigen, a lightweight C++ template library
2// for linear algebra.
3//
4// Copyright (C) 2008-2010 Gael Guennebaud <gael.guennebaud@inria.fr>
5// Copyright (C) 2009 Benoit Jacob <jacob.benoit.1@gmail.com>
6// Copyright (C) 2010 Vincent Lejeune
7//
8// This Source Code Form is subject to the terms of the Mozilla
9// Public License v. 2.0. If a copy of the MPL was not distributed
10// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
11
12#ifndef EIGEN_QR_H
13#define EIGEN_QR_H
14
15namespace Eigen {
16
42template<typename _MatrixType> class HouseholderQR
43{
44 public:
45
46 typedef _MatrixType MatrixType;
47 enum {
48 RowsAtCompileTime = MatrixType::RowsAtCompileTime,
49 ColsAtCompileTime = MatrixType::ColsAtCompileTime,
50 Options = MatrixType::Options,
51 MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
52 MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
53 };
54 typedef typename MatrixType::Scalar Scalar;
55 typedef typename MatrixType::RealScalar RealScalar;
56 typedef typename MatrixType::Index Index;
57 typedef Matrix<Scalar, RowsAtCompileTime, RowsAtCompileTime, (MatrixType::Flags&RowMajorBit) ? RowMajor : ColMajor, MaxRowsAtCompileTime, MaxRowsAtCompileTime> MatrixQType;
58 typedef typename internal::plain_diag_type<MatrixType>::type HCoeffsType;
59 typedef typename internal::plain_row_type<MatrixType>::type RowVectorType;
60 typedef typename HouseholderSequence<MatrixType,HCoeffsType>::ConjugateReturnType HouseholderSequenceType;
61
68 HouseholderQR() : m_qr(), m_hCoeffs(), m_temp(), m_isInitialized(false) {}
69
76 HouseholderQR(Index rows, Index cols)
77 : m_qr(rows, cols),
78 m_hCoeffs((std::min)(rows,cols)),
79 m_temp(cols),
80 m_isInitialized(false) {}
81
82 HouseholderQR(const MatrixType& matrix)
83 : m_qr(matrix.rows(), matrix.cols()),
84 m_hCoeffs((std::min)(matrix.rows(),matrix.cols())),
85 m_temp(matrix.cols()),
86 m_isInitialized(false)
87 {
88 compute(matrix);
89 }
90
108 template<typename Rhs>
109 inline const internal::solve_retval<HouseholderQR, Rhs>
110 solve(const MatrixBase<Rhs>& b) const
111 {
112 eigen_assert(m_isInitialized && "HouseholderQR is not initialized.");
113 return internal::solve_retval<HouseholderQR, Rhs>(*this, b.derived());
114 }
115
116 HouseholderSequenceType householderQ() const
117 {
118 eigen_assert(m_isInitialized && "HouseholderQR is not initialized.");
119 return HouseholderSequenceType(m_qr, m_hCoeffs.conjugate());
120 }
121
125 const MatrixType& matrixQR() const
126 {
127 eigen_assert(m_isInitialized && "HouseholderQR is not initialized.");
128 return m_qr;
129 }
130
131 HouseholderQR& compute(const MatrixType& matrix);
132
146 typename MatrixType::RealScalar absDeterminant() const;
147
160 typename MatrixType::RealScalar logAbsDeterminant() const;
161
162 inline Index rows() const { return m_qr.rows(); }
163 inline Index cols() const { return m_qr.cols(); }
164 const HCoeffsType& hCoeffs() const { return m_hCoeffs; }
165
166 protected:
167 MatrixType m_qr;
168 HCoeffsType m_hCoeffs;
169 RowVectorType m_temp;
170 bool m_isInitialized;
171};
172
173template<typename MatrixType>
174typename MatrixType::RealScalar HouseholderQR<MatrixType>::absDeterminant() const
175{
176 eigen_assert(m_isInitialized && "HouseholderQR is not initialized.");
177 eigen_assert(m_qr.rows() == m_qr.cols() && "You can't take the determinant of a non-square matrix!");
178 return internal::abs(m_qr.diagonal().prod());
179}
180
181template<typename MatrixType>
182typename MatrixType::RealScalar HouseholderQR<MatrixType>::logAbsDeterminant() const
183{
184 eigen_assert(m_isInitialized && "HouseholderQR is not initialized.");
185 eigen_assert(m_qr.rows() == m_qr.cols() && "You can't take the determinant of a non-square matrix!");
186 return m_qr.diagonal().cwiseAbs().array().log().sum();
187}
188
189namespace internal {
190
192template<typename MatrixQR, typename HCoeffs>
193void householder_qr_inplace_unblocked(MatrixQR& mat, HCoeffs& hCoeffs, typename MatrixQR::Scalar* tempData = 0)
194{
195 typedef typename MatrixQR::Index Index;
196 typedef typename MatrixQR::Scalar Scalar;
197 typedef typename MatrixQR::RealScalar RealScalar;
198 Index rows = mat.rows();
199 Index cols = mat.cols();
200 Index size = (std::min)(rows,cols);
201
202 eigen_assert(hCoeffs.size() == size);
203
205 TempType tempVector;
206 if(tempData==0)
207 {
208 tempVector.resize(cols);
209 tempData = tempVector.data();
210 }
211
212 for(Index k = 0; k < size; ++k)
213 {
214 Index remainingRows = rows - k;
215 Index remainingCols = cols - k - 1;
216
217 RealScalar beta;
218 mat.col(k).tail(remainingRows).makeHouseholderInPlace(hCoeffs.coeffRef(k), beta);
219 mat.coeffRef(k,k) = beta;
220
221 // apply H to remaining part of m_qr from the left
222 mat.bottomRightCorner(remainingRows, remainingCols)
223 .applyHouseholderOnTheLeft(mat.col(k).tail(remainingRows-1), hCoeffs.coeffRef(k), tempData+k+1);
224 }
225}
226
228template<typename MatrixQR, typename HCoeffs>
229void householder_qr_inplace_blocked(MatrixQR& mat, HCoeffs& hCoeffs,
230 typename MatrixQR::Index maxBlockSize=32,
231 typename MatrixQR::Scalar* tempData = 0)
232{
233 typedef typename MatrixQR::Index Index;
234 typedef typename MatrixQR::Scalar Scalar;
235 typedef typename MatrixQR::RealScalar RealScalar;
236 typedef Block<MatrixQR,Dynamic,Dynamic> BlockType;
237
238 Index rows = mat.rows();
239 Index cols = mat.cols();
240 Index size = (std::min)(rows, cols);
241
242 typedef Matrix<Scalar,Dynamic,1,ColMajor,MatrixQR::MaxColsAtCompileTime,1> TempType;
243 TempType tempVector;
244 if(tempData==0)
245 {
246 tempVector.resize(cols);
247 tempData = tempVector.data();
248 }
249
250 Index blockSize = (std::min)(maxBlockSize,size);
251
252 Index k = 0;
253 for (k = 0; k < size; k += blockSize)
254 {
255 Index bs = (std::min)(size-k,blockSize); // actual size of the block
256 Index tcols = cols - k - bs; // trailing columns
257 Index brows = rows-k; // rows of the block
258
259 // partition the matrix:
260 // A00 | A01 | A02
261 // mat = A10 | A11 | A12
262 // A20 | A21 | A22
263 // and performs the qr dec of [A11^T A12^T]^T
264 // and update [A21^T A22^T]^T using level 3 operations.
265 // Finally, the algorithm continue on A22
266
267 BlockType A11_21 = mat.block(k,k,brows,bs);
268 Block<HCoeffs,Dynamic,1> hCoeffsSegment = hCoeffs.segment(k,bs);
269
270 householder_qr_inplace_unblocked(A11_21, hCoeffsSegment, tempData);
271
272 if(tcols)
273 {
274 BlockType A21_22 = mat.block(k,k+bs,brows,tcols);
275 apply_block_householder_on_the_left(A21_22,A11_21,hCoeffsSegment.adjoint());
276 }
277 }
278}
279
280template<typename _MatrixType, typename Rhs>
281struct solve_retval<HouseholderQR<_MatrixType>, Rhs>
282 : solve_retval_base<HouseholderQR<_MatrixType>, Rhs>
283{
284 EIGEN_MAKE_SOLVE_HELPERS(HouseholderQR<_MatrixType>,Rhs)
285
286 template<typename Dest> void evalTo(Dest& dst) const
287 {
288 const Index rows = dec().rows(), cols = dec().cols();
289 const Index rank = (std::min)(rows, cols);
290 eigen_assert(rhs().rows() == rows);
291
292 typename Rhs::PlainObject c(rhs());
293
294 // Note that the matrix Q = H_0^* H_1^*... so its inverse is Q^* = (H_0 H_1 ...)^T
295 c.applyOnTheLeft(householderSequence(
296 dec().matrixQR().leftCols(rank),
297 dec().hCoeffs().head(rank)).transpose()
298 );
299
300 dec().matrixQR()
301 .topLeftCorner(rank, rank)
302 .template triangularView<Upper>()
303 .solveInPlace(c.topRows(rank));
304
305 dst.topRows(rank) = c.topRows(rank);
306 dst.bottomRows(cols-rank).setZero();
307 }
308};
309
310} // end namespace internal
311
312template<typename MatrixType>
313HouseholderQR<MatrixType>& HouseholderQR<MatrixType>::compute(const MatrixType& matrix)
314{
315 Index rows = matrix.rows();
316 Index cols = matrix.cols();
317 Index size = (std::min)(rows,cols);
318
319 m_qr = matrix;
320 m_hCoeffs.resize(size);
321
322 m_temp.resize(cols);
323
324 internal::householder_qr_inplace_blocked(m_qr, m_hCoeffs, 48, m_temp.data());
325
326 m_isInitialized = true;
327 return *this;
328}
329
334template<typename Derived>
340
341} // end namespace Eigen
342
343#endif // EIGEN_QR_H
EvalReturnType eval() const
Definition DenseBase.h:372
Householder QR decomposition of a matrix.
Definition HouseholderQR.h:43
MatrixType::RealScalar absDeterminant() const
Definition HouseholderQR.h:174
MatrixType::RealScalar logAbsDeterminant() const
Definition HouseholderQR.h:182
HouseholderQR()
Default Constructor.
Definition HouseholderQR.h:68
const MatrixType & matrixQR() const
Definition HouseholderQR.h:125
HouseholderQR(Index rows, Index cols)
Default Constructor with memory preallocation.
Definition HouseholderQR.h:76
const internal::solve_retval< HouseholderQR, Rhs > solve(const MatrixBase< Rhs > &b) const
Definition HouseholderQR.h:110
Base class for all dense matrices, vectors, and expressions.
Definition MatrixBase.h:50
const HouseholderQR< PlainObject > householderQr() const
Definition HouseholderQR.h:336
The matrix class, also used for vectors and row-vectors.
Definition Matrix.h:129
@ RowMajor
Definition Constants.h:259
@ ColMajor
Definition Constants.h:257
const unsigned int RowMajorBit
Definition Constants.h:48
Definition LDLT.h:18