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merge and add start/end to Eigen2Support

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This commit is contained in:
Gael Guennebaud
2010-01-05 13:07:32 +01:00
parent 90d2ae7fec 51b8f014f3
commit 9d9e00b608
78 changed files with 1072 additions and 592 deletions
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14
Eigen/src/QR/ColPivHouseholderQR.h
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@@ -359,14 +359,14 @@ ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const
{
// first, we look up in our table colSqNorms which column has the biggest squared norm
int biggest_col_index;
RealScalar biggest_col_sq_norm = colSqNorms.end(cols-k).maxCoeff(&biggest_col_index);
RealScalar biggest_col_sq_norm = colSqNorms.tail(cols-k).maxCoeff(&biggest_col_index);
biggest_col_index += k;
// since our table colSqNorms accumulates imprecision at every step, we must now recompute
// the actual squared norm of the selected column.
// Note that not doing so does result in solve() sometimes returning inf/nan values
// when running the unit test with 1000 repetitions.
biggest_col_sq_norm = m_qr.col(biggest_col_index).end(rows-k).squaredNorm();
biggest_col_sq_norm = m_qr.col(biggest_col_index).tail(rows-k).squaredNorm();
// we store that back into our table: it can't hurt to correct our table.
colSqNorms.coeffRef(biggest_col_index) = biggest_col_sq_norm;
@@ -379,7 +379,7 @@ ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const
if(biggest_col_sq_norm < threshold_helper * (rows-k))
{
m_nonzero_pivots = k;
m_hCoeffs.end(size-k).setZero();
m_hCoeffs.tail(size-k).setZero();
m_qr.corner(BottomRight,rows-k,cols-k)
.template triangularView<StrictlyLowerTriangular>()
.setZero();
@@ -396,7 +396,7 @@ ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const
// generate the householder vector, store it below the diagonal
RealScalar beta;
m_qr.col(k).end(rows-k).makeHouseholderInPlace(m_hCoeffs.coeffRef(k), beta);
m_qr.col(k).tail(rows-k).makeHouseholderInPlace(m_hCoeffs.coeffRef(k), beta);
// apply the householder transformation to the diagonal coefficient
m_qr.coeffRef(k,k) = beta;
@@ -406,10 +406,10 @@ ColPivHouseholderQR<MatrixType>& ColPivHouseholderQR<MatrixType>::compute(const
// apply the householder transformation
m_qr.corner(BottomRight, rows-k, cols-k-1)
.applyHouseholderOnTheLeft(m_qr.col(k).end(rows-k-1), m_hCoeffs.coeffRef(k), &temp.coeffRef(k+1));
.applyHouseholderOnTheLeft(m_qr.col(k).tail(rows-k-1), m_hCoeffs.coeffRef(k), &temp.coeffRef(k+1));
// update our table of squared norms of the columns
colSqNorms.end(cols-k-1) -= m_qr.row(k).end(cols-k-1).cwiseAbs2();
colSqNorms.tail(cols-k-1) -= m_qr.row(k).tail(cols-k-1).cwiseAbs2();
}
m_cols_permutation.setIdentity(cols);
@@ -427,7 +427,7 @@ struct ei_solve_retval<ColPivHouseholderQR<_MatrixType>, Rhs>
: ei_solve_retval_base<ColPivHouseholderQR<_MatrixType>, Rhs>
{
EIGEN_MAKE_SOLVE_HELPERS(ColPivHouseholderQR<_MatrixType>,Rhs)
template<typename Dest> void evalTo(Dest& dst) const
{
const int rows = dec().rows(), cols = dec().cols(),

10
Eigen/src/QR/FullPivHouseholderQR.h
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@@ -306,7 +306,7 @@ FullPivHouseholderQR<MatrixType>& FullPivHouseholderQR<MatrixType>::compute(cons
m_rows_transpositions.coeffRef(k) = row_of_biggest_in_corner;
cols_transpositions.coeffRef(k) = col_of_biggest_in_corner;
if(k != row_of_biggest_in_corner) {
m_qr.row(k).end(cols-k).swap(m_qr.row(row_of_biggest_in_corner).end(cols-k));
m_qr.row(k).tail(cols-k).swap(m_qr.row(row_of_biggest_in_corner).tail(cols-k));
++number_of_transpositions;
}
if(k != col_of_biggest_in_corner) {
@@ -315,11 +315,11 @@ FullPivHouseholderQR<MatrixType>& FullPivHouseholderQR<MatrixType>::compute(cons
}
RealScalar beta;
m_qr.col(k).end(rows-k).makeHouseholderInPlace(m_hCoeffs.coeffRef(k), beta);
m_qr.col(k).tail(rows-k).makeHouseholderInPlace(m_hCoeffs.coeffRef(k), beta);
m_qr.coeffRef(k,k) = beta;
m_qr.corner(BottomRight, rows-k, cols-k-1)
.applyHouseholderOnTheLeft(m_qr.col(k).end(rows-k-1), m_hCoeffs.coeffRef(k), &temp.coeffRef(k+1));
.applyHouseholderOnTheLeft(m_qr.col(k).tail(rows-k-1), m_hCoeffs.coeffRef(k), &temp.coeffRef(k+1));
}
m_cols_permutation.setIdentity(cols);
@@ -360,7 +360,7 @@ struct ei_solve_retval<FullPivHouseholderQR<_MatrixType>, Rhs>
int remainingSize = rows-k;
c.row(k).swap(c.row(dec().rowsTranspositions().coeff(k)));
c.corner(BottomRight, remainingSize, rhs().cols())
.applyHouseholderOnTheLeft(dec().matrixQR().col(k).end(remainingSize-1),
.applyHouseholderOnTheLeft(dec().matrixQR().col(k).tail(remainingSize-1),
dec().hCoeffs().coeff(k), &temp.coeffRef(0));
}
@@ -400,7 +400,7 @@ typename FullPivHouseholderQR<MatrixType>::MatrixQType FullPivHouseholderQR<Matr
for (int k = size-1; k >= 0; k--)
{
res.block(k, k, rows-k, rows-k)
.applyHouseholderOnTheLeft(m_qr.col(k).end(rows-k-1), ei_conj(m_hCoeffs.coeff(k)), &temp.coeffRef(k));
.applyHouseholderOnTheLeft(m_qr.col(k).tail(rows-k-1), ei_conj(m_hCoeffs.coeff(k)), &temp.coeffRef(k));
res.row(k).swap(res.row(m_rows_transpositions.coeff(k)));
}
return res;

6
Eigen/src/QR/HouseholderQR.h
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@@ -197,12 +197,12 @@ HouseholderQR<MatrixType>& HouseholderQR<MatrixType>::compute(const MatrixType&
int remainingCols = cols - k - 1;
RealScalar beta;
m_qr.col(k).end(remainingRows).makeHouseholderInPlace(m_hCoeffs.coeffRef(k), beta);
m_qr.col(k).tail(remainingRows).makeHouseholderInPlace(m_hCoeffs.coeffRef(k), beta);
m_qr.coeffRef(k,k) = beta;
// apply H to remaining part of m_qr from the left
m_qr.corner(BottomRight, remainingRows, remainingCols)
.applyHouseholderOnTheLeft(m_qr.col(k).end(remainingRows-1), m_hCoeffs.coeffRef(k), &temp.coeffRef(k+1));
.applyHouseholderOnTheLeft(m_qr.col(k).tail(remainingRows-1), m_hCoeffs.coeffRef(k), &temp.coeffRef(k+1));
}
m_isInitialized = true;
return *this;
@@ -226,7 +226,7 @@ struct ei_solve_retval<HouseholderQR<_MatrixType>, Rhs>
// Note that the matrix Q = H_0^* H_1^*... so its inverse is Q^* = (H_0 H_1 ...)^T
c.applyOnTheLeft(householderSequence(
dec().matrixQR().corner(TopLeft,rows,rank),
dec().hCoeffs().start(rank)).transpose()
dec().hCoeffs().head(rank)).transpose()
);
dec().matrixQR()