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* move dummy_precision and epsilon to NumTraits

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* make NumTraits inherits std::numeric_limits
This commit is contained in:
Gael Guennebaud
2010-02-10 10:52:28 +01:00
parent c11df02f0d
commit fe0827495a
34 changed files with 108 additions and 103 deletions
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4
Eigen/src/QR/ColPivHouseholderQR.h
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@@ -282,7 +282,7 @@ template<typename _MatrixType> class ColPivHouseholderQR
return m_usePrescribedThreshold ? m_prescribedThreshold
// this formula comes from experimenting (see "LU precision tuning" thread on the list)
// and turns out to be identical to Higham's formula used already in LDLt.
: epsilon<Scalar>() * m_qr.diagonalSize();
: NumTraits<Scalar>::epsilon() * m_qr.diagonalSize();
}
/** \returns the number of nonzero pivots in the QR decomposition.
@@ -350,7 +350,7 @@ ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const
for(int k = 0; k < cols; ++k)
colSqNorms.coeffRef(k) = m_qr.col(k).squaredNorm();
RealScalar threshold_helper = colSqNorms.maxCoeff() * ei_abs2(epsilon<Scalar>()) / rows;
RealScalar threshold_helper = colSqNorms.maxCoeff() * ei_abs2(NumTraits<Scalar>::epsilon()) / rows;
m_nonzero_pivots = size; // the generic case is that in which all pivots are nonzero (invertible case)
m_maxpivot = RealScalar(0);

4
Eigen/src/QR/FullPivHouseholderQR.h
View File

@@ -270,7 +270,7 @@ FullPivHouseholderQR<MatrixType>& FullPivHouseholderQR<MatrixType>::compute(cons
RowVectorType temp(cols);
m_precision = epsilon<Scalar>() * size;
m_precision = NumTraits<Scalar>::epsilon() * size;
m_rows_transpositions.resize(matrix.rows());
IntRowVectorType cols_transpositions(matrix.cols());
@@ -370,7 +370,7 @@ struct ei_solve_retval<FullPivHouseholderQR<_MatrixType>, Rhs>
RealScalar biggest_in_upper_part_of_c = c.corner(TopLeft, dec().rank(), c.cols()).cwiseAbs().maxCoeff();
RealScalar biggest_in_lower_part_of_c = c.corner(BottomLeft, rows-dec().rank(), c.cols()).cwiseAbs().maxCoeff();
// FIXME brain dead
const RealScalar m_precision = epsilon<Scalar>() * std::min(rows,cols);
const RealScalar m_precision = NumTraits<Scalar>::epsilon() * std::min(rows,cols);
if(!ei_isMuchSmallerThan(biggest_in_lower_part_of_c, biggest_in_upper_part_of_c, m_precision))
return;
}