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00026 #ifndef EIGEN_EIGENSOLVER_H
00027 #define EIGEN_EIGENSOLVER_H
00028
00029 #include "./EigenvaluesCommon.h"
00030 #include "./RealSchur.h"
00031
00078 template<typename _MatrixType> class EigenSolver
00079 {
00080 public:
00081
00083 typedef _MatrixType MatrixType;
00084
00085 enum {
00086 RowsAtCompileTime = MatrixType::RowsAtCompileTime,
00087 ColsAtCompileTime = MatrixType::ColsAtCompileTime,
00088 Options = MatrixType::Options,
00089 MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
00090 MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime
00091 };
00092
00094 typedef typename MatrixType::Scalar Scalar;
00095 typedef typename NumTraits<Scalar>::Real RealScalar;
00096 typedef typename MatrixType::Index Index;
00097
00104 typedef std::complex<RealScalar> ComplexScalar;
00105
00111 typedef Matrix<ComplexScalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1> EigenvalueType;
00112
00118 typedef Matrix<ComplexScalar, RowsAtCompileTime, ColsAtCompileTime, Options, MaxRowsAtCompileTime, MaxColsAtCompileTime> EigenvectorsType;
00119
00127 EigenSolver() : m_eivec(), m_eivalues(), m_isInitialized(false), m_realSchur(), m_matT(), m_tmp() {}
00128
00135 EigenSolver(Index size)
00136 : m_eivec(size, size),
00137 m_eivalues(size),
00138 m_isInitialized(false),
00139 m_eigenvectorsOk(false),
00140 m_realSchur(size),
00141 m_matT(size, size),
00142 m_tmp(size)
00143 {}
00144
00160 EigenSolver(const MatrixType& matrix, bool computeEigenvectors = true)
00161 : m_eivec(matrix.rows(), matrix.cols()),
00162 m_eivalues(matrix.cols()),
00163 m_isInitialized(false),
00164 m_eigenvectorsOk(false),
00165 m_realSchur(matrix.cols()),
00166 m_matT(matrix.rows(), matrix.cols()),
00167 m_tmp(matrix.cols())
00168 {
00169 compute(matrix, computeEigenvectors);
00170 }
00171
00192 EigenvectorsType eigenvectors() const;
00193
00212 const MatrixType& pseudoEigenvectors() const
00213 {
00214 eigen_assert(m_isInitialized && "EigenSolver is not initialized.");
00215 eigen_assert(m_eigenvectorsOk && "The eigenvectors have not been computed together with the eigenvalues.");
00216 return m_eivec;
00217 }
00218
00237 MatrixType pseudoEigenvalueMatrix() const;
00238
00257 const EigenvalueType& eigenvalues() const
00258 {
00259 eigen_assert(m_isInitialized && "EigenSolver is not initialized.");
00260 return m_eivalues;
00261 }
00262
00290 EigenSolver& compute(const MatrixType& matrix, bool computeEigenvectors = true);
00291
00292 ComputationInfo info() const
00293 {
00294 eigen_assert(m_isInitialized && "ComplexEigenSolver is not initialized.");
00295 return m_realSchur.info();
00296 }
00297
00298 private:
00299 void doComputeEigenvectors();
00300
00301 protected:
00302 MatrixType m_eivec;
00303 EigenvalueType m_eivalues;
00304 bool m_isInitialized;
00305 bool m_eigenvectorsOk;
00306 RealSchur<MatrixType> m_realSchur;
00307 MatrixType m_matT;
00308
00309 typedef Matrix<Scalar, ColsAtCompileTime, 1, Options & ~RowMajor, MaxColsAtCompileTime, 1> ColumnVectorType;
00310 ColumnVectorType m_tmp;
00311 };
00312
00313 template<typename MatrixType>
00314 MatrixType EigenSolver<MatrixType>::pseudoEigenvalueMatrix() const
00315 {
00316 eigen_assert(m_isInitialized && "EigenSolver is not initialized.");
00317 Index n = m_eivalues.rows();
00318 MatrixType matD = MatrixType::Zero(n,n);
00319 for (Index i=0; i<n; ++i)
00320 {
00321 if (internal::isMuchSmallerThan(internal::imag(m_eivalues.coeff(i)), internal::real(m_eivalues.coeff(i))))
00322 matD.coeffRef(i,i) = internal::real(m_eivalues.coeff(i));
00323 else
00324 {
00325 matD.template block<2,2>(i,i) << internal::real(m_eivalues.coeff(i)), internal::imag(m_eivalues.coeff(i)),
00326 -internal::imag(m_eivalues.coeff(i)), internal::real(m_eivalues.coeff(i));
00327 ++i;
00328 }
00329 }
00330 return matD;
00331 }
00332
00333 template<typename MatrixType>
00334 typename EigenSolver<MatrixType>::EigenvectorsType EigenSolver<MatrixType>::eigenvectors() const
00335 {
00336 eigen_assert(m_isInitialized && "EigenSolver is not initialized.");
00337 eigen_assert(m_eigenvectorsOk && "The eigenvectors have not been computed together with the eigenvalues.");
00338 Index n = m_eivec.cols();
00339 EigenvectorsType matV(n,n);
00340 for (Index j=0; j<n; ++j)
00341 {
00342 if (internal::isMuchSmallerThan(internal::imag(m_eivalues.coeff(j)), internal::real(m_eivalues.coeff(j))))
00343 {
00344
00345 matV.col(j) = m_eivec.col(j).template cast<ComplexScalar>();
00346 matV.col(j).normalize();
00347 }
00348 else
00349 {
00350
00351 for (Index i=0; i<n; ++i)
00352 {
00353 matV.coeffRef(i,j) = ComplexScalar(m_eivec.coeff(i,j), m_eivec.coeff(i,j+1));
00354 matV.coeffRef(i,j+1) = ComplexScalar(m_eivec.coeff(i,j), -m_eivec.coeff(i,j+1));
00355 }
00356 matV.col(j).normalize();
00357 matV.col(j+1).normalize();
00358 ++j;
00359 }
00360 }
00361 return matV;
00362 }
00363
00364 template<typename MatrixType>
00365 EigenSolver<MatrixType>& EigenSolver<MatrixType>::compute(const MatrixType& matrix, bool computeEigenvectors)
00366 {
00367 assert(matrix.cols() == matrix.rows());
00368
00369
00370 m_realSchur.compute(matrix, computeEigenvectors);
00371 if (m_realSchur.info() == Success)
00372 {
00373 m_matT = m_realSchur.matrixT();
00374 if (computeEigenvectors)
00375 m_eivec = m_realSchur.matrixU();
00376
00377
00378 m_eivalues.resize(matrix.cols());
00379 Index i = 0;
00380 while (i < matrix.cols())
00381 {
00382 if (i == matrix.cols() - 1 || m_matT.coeff(i+1, i) == Scalar(0))
00383 {
00384 m_eivalues.coeffRef(i) = m_matT.coeff(i, i);
00385 ++i;
00386 }
00387 else
00388 {
00389 Scalar p = Scalar(0.5) * (m_matT.coeff(i, i) - m_matT.coeff(i+1, i+1));
00390 Scalar z = internal::sqrt(internal::abs(p * p + m_matT.coeff(i+1, i) * m_matT.coeff(i, i+1)));
00391 m_eivalues.coeffRef(i) = ComplexScalar(m_matT.coeff(i+1, i+1) + p, z);
00392 m_eivalues.coeffRef(i+1) = ComplexScalar(m_matT.coeff(i+1, i+1) + p, -z);
00393 i += 2;
00394 }
00395 }
00396
00397
00398 if (computeEigenvectors)
00399 doComputeEigenvectors();
00400 }
00401
00402 m_isInitialized = true;
00403 m_eigenvectorsOk = computeEigenvectors;
00404
00405 return *this;
00406 }
00407
00408
00409 template<typename Scalar>
00410 std::complex<Scalar> cdiv(Scalar xr, Scalar xi, Scalar yr, Scalar yi)
00411 {
00412 Scalar r,d;
00413 if (internal::abs(yr) > internal::abs(yi))
00414 {
00415 r = yi/yr;
00416 d = yr + r*yi;
00417 return std::complex<Scalar>((xr + r*xi)/d, (xi - r*xr)/d);
00418 }
00419 else
00420 {
00421 r = yr/yi;
00422 d = yi + r*yr;
00423 return std::complex<Scalar>((r*xr + xi)/d, (r*xi - xr)/d);
00424 }
00425 }
00426
00427
00428 template<typename MatrixType>
00429 void EigenSolver<MatrixType>::doComputeEigenvectors()
00430 {
00431 const Index size = m_eivec.cols();
00432 const Scalar eps = NumTraits<Scalar>::epsilon();
00433
00434
00435 Scalar norm = 0.0;
00436 for (Index j = 0; j < size; ++j)
00437 {
00438 norm += m_matT.row(j).segment((std::max)(j-1,Index(0)), size-(std::max)(j-1,Index(0))).cwiseAbs().sum();
00439 }
00440
00441
00442 if (norm == 0.0)
00443 {
00444 return;
00445 }
00446
00447 for (Index n = size-1; n >= 0; n--)
00448 {
00449 Scalar p = m_eivalues.coeff(n).real();
00450 Scalar q = m_eivalues.coeff(n).imag();
00451
00452
00453 if (q == Scalar(0))
00454 {
00455 Scalar lastr=0, lastw=0;
00456 Index l = n;
00457
00458 m_matT.coeffRef(n,n) = 1.0;
00459 for (Index i = n-1; i >= 0; i--)
00460 {
00461 Scalar w = m_matT.coeff(i,i) - p;
00462 Scalar r = m_matT.row(i).segment(l,n-l+1).dot(m_matT.col(n).segment(l, n-l+1));
00463
00464 if (m_eivalues.coeff(i).imag() < 0.0)
00465 {
00466 lastw = w;
00467 lastr = r;
00468 }
00469 else
00470 {
00471 l = i;
00472 if (m_eivalues.coeff(i).imag() == 0.0)
00473 {
00474 if (w != 0.0)
00475 m_matT.coeffRef(i,n) = -r / w;
00476 else
00477 m_matT.coeffRef(i,n) = -r / (eps * norm);
00478 }
00479 else
00480 {
00481 Scalar x = m_matT.coeff(i,i+1);
00482 Scalar y = m_matT.coeff(i+1,i);
00483 Scalar denom = (m_eivalues.coeff(i).real() - p) * (m_eivalues.coeff(i).real() - p) + m_eivalues.coeff(i).imag() * m_eivalues.coeff(i).imag();
00484 Scalar t = (x * lastr - lastw * r) / denom;
00485 m_matT.coeffRef(i,n) = t;
00486 if (internal::abs(x) > internal::abs(lastw))
00487 m_matT.coeffRef(i+1,n) = (-r - w * t) / x;
00488 else
00489 m_matT.coeffRef(i+1,n) = (-lastr - y * t) / lastw;
00490 }
00491
00492
00493 Scalar t = internal::abs(m_matT.coeff(i,n));
00494 if ((eps * t) * t > Scalar(1))
00495 m_matT.col(n).tail(size-i) /= t;
00496 }
00497 }
00498 }
00499 else if (q < Scalar(0) && n > 0)
00500 {
00501 Scalar lastra=0, lastsa=0, lastw=0;
00502 Index l = n-1;
00503
00504
00505 if (internal::abs(m_matT.coeff(n,n-1)) > internal::abs(m_matT.coeff(n-1,n)))
00506 {
00507 m_matT.coeffRef(n-1,n-1) = q / m_matT.coeff(n,n-1);
00508 m_matT.coeffRef(n-1,n) = -(m_matT.coeff(n,n) - p) / m_matT.coeff(n,n-1);
00509 }
00510 else
00511 {
00512 std::complex<Scalar> cc = cdiv<Scalar>(0.0,-m_matT.coeff(n-1,n),m_matT.coeff(n-1,n-1)-p,q);
00513 m_matT.coeffRef(n-1,n-1) = internal::real(cc);
00514 m_matT.coeffRef(n-1,n) = internal::imag(cc);
00515 }
00516 m_matT.coeffRef(n,n-1) = 0.0;
00517 m_matT.coeffRef(n,n) = 1.0;
00518 for (Index i = n-2; i >= 0; i--)
00519 {
00520 Scalar ra = m_matT.row(i).segment(l, n-l+1).dot(m_matT.col(n-1).segment(l, n-l+1));
00521 Scalar sa = m_matT.row(i).segment(l, n-l+1).dot(m_matT.col(n).segment(l, n-l+1));
00522 Scalar w = m_matT.coeff(i,i) - p;
00523
00524 if (m_eivalues.coeff(i).imag() < 0.0)
00525 {
00526 lastw = w;
00527 lastra = ra;
00528 lastsa = sa;
00529 }
00530 else
00531 {
00532 l = i;
00533 if (m_eivalues.coeff(i).imag() == RealScalar(0))
00534 {
00535 std::complex<Scalar> cc = cdiv(-ra,-sa,w,q);
00536 m_matT.coeffRef(i,n-1) = internal::real(cc);
00537 m_matT.coeffRef(i,n) = internal::imag(cc);
00538 }
00539 else
00540 {
00541
00542 Scalar x = m_matT.coeff(i,i+1);
00543 Scalar y = m_matT.coeff(i+1,i);
00544 Scalar vr = (m_eivalues.coeff(i).real() - p) * (m_eivalues.coeff(i).real() - p) + m_eivalues.coeff(i).imag() * m_eivalues.coeff(i).imag() - q * q;
00545 Scalar vi = (m_eivalues.coeff(i).real() - p) * Scalar(2) * q;
00546 if ((vr == 0.0) && (vi == 0.0))
00547 vr = eps * norm * (internal::abs(w) + internal::abs(q) + internal::abs(x) + internal::abs(y) + internal::abs(lastw));
00548
00549 std::complex<Scalar> cc = cdiv(x*lastra-lastw*ra+q*sa,x*lastsa-lastw*sa-q*ra,vr,vi);
00550 m_matT.coeffRef(i,n-1) = internal::real(cc);
00551 m_matT.coeffRef(i,n) = internal::imag(cc);
00552 if (internal::abs(x) > (internal::abs(lastw) + internal::abs(q)))
00553 {
00554 m_matT.coeffRef(i+1,n-1) = (-ra - w * m_matT.coeff(i,n-1) + q * m_matT.coeff(i,n)) / x;
00555 m_matT.coeffRef(i+1,n) = (-sa - w * m_matT.coeff(i,n) - q * m_matT.coeff(i,n-1)) / x;
00556 }
00557 else
00558 {
00559 cc = cdiv(-lastra-y*m_matT.coeff(i,n-1),-lastsa-y*m_matT.coeff(i,n),lastw,q);
00560 m_matT.coeffRef(i+1,n-1) = internal::real(cc);
00561 m_matT.coeffRef(i+1,n) = internal::imag(cc);
00562 }
00563 }
00564
00565
00566 using std::max;
00567 Scalar t = (max)(internal::abs(m_matT.coeff(i,n-1)),internal::abs(m_matT.coeff(i,n)));
00568 if ((eps * t) * t > Scalar(1))
00569 m_matT.block(i, n-1, size-i, 2) /= t;
00570
00571 }
00572 }
00573 }
00574 else
00575 {
00576 eigen_assert("Internal bug in EigenSolver");
00577 }
00578 }
00579
00580
00581 for (Index j = size-1; j >= 0; j--)
00582 {
00583 m_tmp.noalias() = m_eivec.leftCols(j+1) * m_matT.col(j).segment(0, j+1);
00584 m_eivec.col(j) = m_tmp;
00585 }
00586 }
00587
00588 #endif // EIGEN_EIGENSOLVER_H