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Fix SparseLU and SparseQR for custom scalar types

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libeigen/eigen!2345
This commit is contained in:
Tyler Veness
2026-03-27 00:13:11 -07:00
committed by Rasmus Munk Larsen
parent 002229ce47
commit 9939a4c6e3
2 changed files with 9 additions and 9 deletions
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12
Eigen/src/SparseQR/SparseQR.h
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@@ -401,10 +401,10 @@ void SparseQR<MatrixType, OrderingType>::factorize(const MatrixType& mat) {
*/
RealScalar pivotThreshold;
if (m_useDefaultThreshold) {
RealScalar max2Norm = 0.0;
RealScalar max2Norm = RealScalar(0.0);
for (int j = 0; j < n; j++) max2Norm = numext::maxi(max2Norm, m_pmat.col(j).norm());
if (max2Norm == RealScalar(0)) max2Norm = RealScalar(1);
pivotThreshold = 20 * (m + n) * max2Norm * NumTraits<RealScalar>::epsilon();
pivotThreshold = RealScalar(20 * (m + n)) * max2Norm * NumTraits<RealScalar>::epsilon();
} else {
pivotThreshold = m_threshold;
}
@@ -497,7 +497,7 @@ void SparseQR<MatrixType, OrderingType>::factorize(const MatrixType& mat) {
} // End update current column
Scalar tau = RealScalar(0);
RealScalar beta = 0;
RealScalar beta = RealScalar(0);
if (nonzeroCol < diagSize) {
// Compute the Householder reflection that eliminate the current column
@@ -505,16 +505,16 @@ void SparseQR<MatrixType, OrderingType>::factorize(const MatrixType& mat) {
Scalar c0 = nzcolQ ? tval(Qidx(0)) : Scalar(0);
// First, the squared norm of Q((col+1):m, col)
RealScalar sqrNorm = 0.;
RealScalar sqrNorm = RealScalar(0.);
for (Index itq = 1; itq < nzcolQ; ++itq) sqrNorm += numext::abs2(tval(Qidx(itq)));
if (sqrNorm == RealScalar(0) && numext::imag(c0) == RealScalar(0)) {
beta = numext::real(c0);
tval(Qidx(0)) = 1;
tval(Qidx(0)) = Scalar(1);
} else {
using std::sqrt;
beta = sqrt(numext::abs2(c0) + sqrNorm);
if (numext::real(c0) >= RealScalar(0)) beta = -beta;
tval(Qidx(0)) = 1;
tval(Qidx(0)) = Scalar(1);
for (Index itq = 1; itq < nzcolQ; ++itq) tval(Qidx(itq)) /= (c0 - beta);
tau = numext::conj((beta - c0) / beta);
}