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Big renaming:

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start ---> head
  end   ---> tail
Much frustration with sed syntax. Need to learn perl some day.
This commit is contained in:
Benoit Jacob
2010-01-04 21:24:43 -05:00
parent 78ba523d30
commit 39ac57fa6d
43 changed files with 158 additions and 158 deletions
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2
Eigen/src/Eigenvalues/ComplexEigenSolver.h
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@@ -133,7 +133,7 @@ void ComplexEigenSolver<MatrixType>::compute(const MatrixType& matrix)
for (int i=0; i<n; i++)
{
int k;
m_eivalues.cwise().abs().end(n-i).minCoeff(&k);
m_eivalues.cwise().abs().tail(n-i).minCoeff(&k);
if (k != 0)
{
k += i;

4
Eigen/src/Eigenvalues/EigenSolver.h
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@@ -620,7 +620,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH)
// Overflow control
t = ei_abs(matH.coeff(i,n));
if ((eps * t) * t > 1)
matH.col(n).end(nn-i) /= t;
matH.col(n).tail(nn-i) /= t;
}
}
}
@@ -708,7 +708,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH)
// in this algo low==0 and high==nn-1 !!
if (i < low || i > high)
{
m_eivec.row(i).end(nn-i) = matH.row(i).end(nn-i);
m_eivec.row(i).tail(nn-i) = matH.row(i).tail(nn-i);
}
}

8
Eigen/src/Eigenvalues/HessenbergDecomposition.h
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@@ -150,7 +150,7 @@ void HessenbergDecomposition<MatrixType>::_compute(MatrixType& matA, CoeffVector
int remainingSize = n-i-1;
RealScalar beta;
Scalar h;
matA.col(i).end(remainingSize).makeHouseholderInPlace(h, beta);
matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta);
matA.col(i).coeffRef(i+1) = beta;
hCoeffs.coeffRef(i) = h;
@@ -159,11 +159,11 @@ void HessenbergDecomposition<MatrixType>::_compute(MatrixType& matA, CoeffVector
// A = H A
matA.corner(BottomRight, remainingSize, remainingSize)
.applyHouseholderOnTheLeft(matA.col(i).end(remainingSize-1), h, &temp.coeffRef(0));
.applyHouseholderOnTheLeft(matA.col(i).tail(remainingSize-1), h, &temp.coeffRef(0));
// A = A H'
matA.corner(BottomRight, n, remainingSize)
.applyHouseholderOnTheRight(matA.col(i).end(remainingSize-1).conjugate(), ei_conj(h), &temp.coeffRef(0));
.applyHouseholderOnTheRight(matA.col(i).tail(remainingSize-1).conjugate(), ei_conj(h), &temp.coeffRef(0));
}
}
@@ -178,7 +178,7 @@ HessenbergDecomposition<MatrixType>::matrixQ() const
for (int i = n-2; i>=0; i--)
{
matQ.corner(BottomRight,n-i-1,n-i-1)
.applyHouseholderOnTheLeft(m_matrix.col(i).end(n-i-2), ei_conj(m_hCoeffs.coeff(i)), &temp.coeffRef(0,0));
.applyHouseholderOnTheLeft(m_matrix.col(i).tail(n-i-2), ei_conj(m_hCoeffs.coeff(i)), &temp.coeffRef(0,0));
}
return matQ;
}

14
Eigen/src/Eigenvalues/Tridiagonalization.h
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@@ -202,19 +202,19 @@ void Tridiagonalization<MatrixType>::_compute(MatrixType& matA, CoeffVectorType&
int remainingSize = n-i-1;
RealScalar beta;
Scalar h;
matA.col(i).end(remainingSize).makeHouseholderInPlace(h, beta);
matA.col(i).tail(remainingSize).makeHouseholderInPlace(h, beta);
// Apply similarity transformation to remaining columns,
// i.e., A = H A H' where H = I - h v v' and v = matA.col(i).end(n-i-1)
// i.e., A = H A H' where H = I - h v v' and v = matA.col(i).tail(n-i-1)
matA.col(i).coeffRef(i+1) = 1;
hCoeffs.end(n-i-1) = (matA.corner(BottomRight,remainingSize,remainingSize).template selfadjointView<LowerTriangular>()
* (ei_conj(h) * matA.col(i).end(remainingSize)));
hCoeffs.tail(n-i-1) = (matA.corner(BottomRight,remainingSize,remainingSize).template selfadjointView<LowerTriangular>()
* (ei_conj(h) * matA.col(i).tail(remainingSize)));
hCoeffs.end(n-i-1) += (ei_conj(h)*Scalar(-0.5)*(hCoeffs.end(remainingSize).dot(matA.col(i).end(remainingSize)))) * matA.col(i).end(n-i-1);
hCoeffs.tail(n-i-1) += (ei_conj(h)*Scalar(-0.5)*(hCoeffs.tail(remainingSize).dot(matA.col(i).tail(remainingSize)))) * matA.col(i).tail(n-i-1);
matA.corner(BottomRight, remainingSize, remainingSize).template selfadjointView<LowerTriangular>()
.rankUpdate(matA.col(i).end(remainingSize), hCoeffs.end(remainingSize), -1);
.rankUpdate(matA.col(i).tail(remainingSize), hCoeffs.tail(remainingSize), -1);
matA.col(i).coeffRef(i+1) = beta;
hCoeffs.coeffRef(i) = h;
@@ -242,7 +242,7 @@ void Tridiagonalization<MatrixType>::matrixQInPlace(MatrixBase<QDerived>* q) con
for (int i = n-2; i>=0; i--)
{
matQ.corner(BottomRight,n-i-1,n-i-1)
.applyHouseholderOnTheLeft(m_matrix.col(i).end(n-i-2), ei_conj(m_hCoeffs.coeff(i)), &aux.coeffRef(0,0));
.applyHouseholderOnTheLeft(m_matrix.col(i).tail(n-i-2), ei_conj(m_hCoeffs.coeff(i)), &aux.coeffRef(0,0));
}
}