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Use EISPACK's strategy re max number of iters in Schur decomposition (bug #479).

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This commit is contained in:
Jitse Niesen 2012-07-22 22:03:23 +01:00
parent a63c4da68e
commit e546ee315a
2 changed files with 11 additions and 7 deletions
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8
Eigen/src/Eigenvalues/ComplexSchur.h
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@ -336,6 +336,7 @@ void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU)
Index iu = m_matT.cols() - 1; Index iu = m_matT.cols() - 1;
Index il; Index il;
Index iter = 0; // number of iterations we are working on the (iu,iu) element Index iter = 0; // number of iterations we are working on the (iu,iu) element
Index totalIter = 0; // number of iterations for whole matrix
while(true) while(true)
{ {
@ -350,9 +351,10 @@ void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU)
// if iu is zero then we are done; the whole matrix is triangularized // if iu is zero then we are done; the whole matrix is triangularized
if(iu==0) break; if(iu==0) break;
// if we spent too many iterations on the current element, we give up // if we spent too many iterations, we give up
iter++; iter++;
if(iter > m_maxIterations * m_matT.cols()) break; totalIter++;
if(totalIter > m_maxIterations * m_matT.cols()) break;
// find il, the top row of the active submatrix // find il, the top row of the active submatrix
il = iu-1; il = iu-1;
@ -382,7 +384,7 @@ void ComplexSchur<MatrixType>::reduceToTriangularForm(bool computeU)
} }
} }
if(iter <= m_maxIterations * m_matT.cols()) if(totalIter <= m_maxIterations * m_matT.cols())
m_info = Success; m_info = Success;
else else
m_info = NoConvergence; m_info = NoConvergence;

10
Eigen/src/Eigenvalues/RealSchur.h
View File

@ -220,8 +220,9 @@ RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const MatrixType& matrix,
// Rows il,...,iu is the part we are working on (the active window). // Rows il,...,iu is the part we are working on (the active window).
// Rows iu+1,...,end are already brought in triangular form. // Rows iu+1,...,end are already brought in triangular form.
Index iu = m_matT.cols() - 1; Index iu = m_matT.cols() - 1;
Index iter = 0; // iteration count Index iter = 0; // iteration count for current eigenvalue
Scalar exshift(0); // sum of exceptional shifts Index totalIter = 0; // iteration count for whole matrix
Scalar exshift(0); // sum of exceptional shifts
Scalar norm = computeNormOfT(); Scalar norm = computeNormOfT();
if(norm!=0) if(norm!=0)
@ -251,14 +252,15 @@ RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const MatrixType& matrix,
Vector3s firstHouseholderVector(0,0,0), shiftInfo; Vector3s firstHouseholderVector(0,0,0), shiftInfo;
computeShift(iu, iter, exshift, shiftInfo); computeShift(iu, iter, exshift, shiftInfo);
iter = iter + 1; iter = iter + 1;
if (iter > m_maxIterations * m_matT.cols()) break; totalIter = totalIter + 1;
if (totalIter > m_maxIterations * matrix.cols()) break;
Index im; Index im;
initFrancisQRStep(il, iu, shiftInfo, im, firstHouseholderVector); initFrancisQRStep(il, iu, shiftInfo, im, firstHouseholderVector);
performFrancisQRStep(il, im, iu, computeU, firstHouseholderVector, workspace); performFrancisQRStep(il, im, iu, computeU, firstHouseholderVector, workspace);
} }
} }
} }
if(iter <= m_maxIterations * m_matT.cols()) if(totalIter <= m_maxIterations * matrix.cols())
m_info = Success; m_info = Success;
else else
m_info = NoConvergence; m_info = NoConvergence;