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reduce float warnings (comparisons and implicit conversions)

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This commit is contained in:
Erik Schultheis
2022-01-26 18:16:19 +00:00
committed by Rasmus Munk Larsen
parent 51311ec651
commit d271a7d545
41 changed files with 152 additions and 133 deletions
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40
Eigen/src/SVD/BDCSVD.h
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@@ -282,7 +282,7 @@ BDCSVD<MatrixType>& BDCSVD<MatrixType>::compute(const MatrixType& matrix, unsign
return *this;
}
if(scale==Literal(0)) scale = Literal(1);
if(numext::is_exactly_zero(scale)) scale = Literal(1);
MatrixX copy;
if (m_isTranspose) copy = matrix.adjoint()/scale;
else copy = matrix/scale;
@@ -621,7 +621,10 @@ void BDCSVD<MatrixType>::computeSVDofM(Eigen::Index firstCol, Eigen::Index n, Ma
// but others are interleaved and we must ignore them at this stage.
// To this end, let's compute a permutation skipping them:
Index actual_n = n;
while(actual_n>1 && diag(actual_n-1)==Literal(0)) {--actual_n; eigen_internal_assert(col0(actual_n)==Literal(0)); }
while(actual_n>1 && numext::is_exactly_zero(diag(actual_n - 1))) {
--actual_n;
eigen_internal_assert(numext::is_exactly_zero(col0(actual_n)));
}
Index m = 0; // size of the deflated problem
for(Index k=0;k<actual_n;++k)
if(abs(col0(k))>considerZero)
@@ -753,11 +756,11 @@ void BDCSVD<MatrixType>::computeSingVals(const ArrayRef& col0, const ArrayRef& d
Index actual_n = n;
// Note that here actual_n is computed based on col0(i)==0 instead of diag(i)==0 as above
// because 1) we have diag(i)==0 => col0(i)==0 and 2) if col0(i)==0, then diag(i) is already a singular value.
while(actual_n>1 && col0(actual_n-1)==Literal(0)) --actual_n;
while(actual_n>1 && numext::is_exactly_zero(col0(actual_n - 1))) --actual_n;
for (Index k = 0; k < n; ++k)
{
if (col0(k) == Literal(0) || actual_n==1)
if (numext::is_exactly_zero(col0(k)) || actual_n == 1)
{
// if col0(k) == 0, then entry is deflated, so singular value is on diagonal
// if actual_n==1, then the deflated problem is already diagonalized
@@ -778,7 +781,7 @@ void BDCSVD<MatrixType>::computeSingVals(const ArrayRef& col0, const ArrayRef& d
// recall that at this stage we assume that z[j]!=0 and all entries for which z[j]==0 have been put aside.
// This should be equivalent to using perm[]
Index l = k+1;
while(col0(l)==Literal(0)) { ++l; eigen_internal_assert(l<actual_n); }
while(numext::is_exactly_zero(col0(l))) { ++l; eigen_internal_assert(l < actual_n); }
right = diag(l);
}
@@ -813,7 +816,8 @@ void BDCSVD<MatrixType>::computeSingVals(const ArrayRef& col0, const ArrayRef& d
{
// check that after the shift, f(mid) is still negative:
RealScalar midShifted = (right - left) / RealScalar(2);
if(shift==right)
// we can test exact equality here, because shift comes from `... ? left : right`
if(numext::equal_strict(shift, right))
midShifted = -midShifted;
RealScalar fMidShifted = secularEq(midShifted, col0, diag, perm, diagShifted, shift);
if(fMidShifted>0)
@@ -826,7 +830,8 @@ void BDCSVD<MatrixType>::computeSingVals(const ArrayRef& col0, const ArrayRef& d
// initial guess
RealScalar muPrev, muCur;
if (shift == left)
// we can test exact equality here, because shift comes from `... ? left : right`
if (numext::equal_strict(shift, left))
{
muPrev = (right - left) * RealScalar(0.1);
if (k == actual_n-1) muCur = right - left;
@@ -849,7 +854,7 @@ void BDCSVD<MatrixType>::computeSingVals(const ArrayRef& col0, const ArrayRef& d
// rational interpolation: fit a function of the form a / mu + b through the two previous
// iterates and use its zero to compute the next iterate
bool useBisection = fPrev*fCur>Literal(0);
while (fCur!=Literal(0) && abs(muCur - muPrev) > Literal(8) * NumTraits<RealScalar>::epsilon() * numext::maxi<RealScalar>(abs(muCur), abs(muPrev)) && abs(fCur - fPrev)>NumTraits<RealScalar>::epsilon() && !useBisection)
while (!numext::is_exactly_zero(fCur) && abs(muCur - muPrev) > Literal(8) * NumTraits<RealScalar>::epsilon() * numext::maxi<RealScalar>(abs(muCur), abs(muPrev)) && abs(fCur - fPrev) > NumTraits<RealScalar>::epsilon() && !useBisection)
{
++m_numIters;
@@ -869,8 +874,9 @@ void BDCSVD<MatrixType>::computeSingVals(const ArrayRef& col0, const ArrayRef& d
muCur = muZero;
fCur = fZero;
if (shift == left && (muCur < Literal(0) || muCur > right - left)) useBisection = true;
if (shift == right && (muCur < -(right - left) || muCur > Literal(0))) useBisection = true;
// we can test exact equality here, because shift comes from `... ? left : right`
if (numext::equal_strict(shift, left) && (muCur < Literal(0) || muCur > right - left)) useBisection = true;
if (numext::equal_strict(shift, right) && (muCur < -(right - left) || muCur > Literal(0))) useBisection = true;
if (abs(fCur)>abs(fPrev)) useBisection = true;
}
@@ -881,7 +887,8 @@ void BDCSVD<MatrixType>::computeSingVals(const ArrayRef& col0, const ArrayRef& d
std::cout << "useBisection for k = " << k << ", actual_n = " << actual_n << "\n";
#endif
RealScalar leftShifted, rightShifted;
if (shift == left)
// we can test exact equality here, because shift comes from `... ? left : right`
if (numext::equal_strict(shift, left))
{
// to avoid overflow, we must have mu > max(real_min, |z(k)|/sqrt(real_max)),
// the factor 2 is to be more conservative
@@ -959,7 +966,8 @@ void BDCSVD<MatrixType>::computeSingVals(const ArrayRef& col0, const ArrayRef& d
// Instead fo abbording or entering an infinite loop,
// let's just use the middle as the estimated zero-crossing:
muCur = (right - left) * RealScalar(0.5);
if(shift == right)
// we can test exact equality here, because shift comes from `... ? left : right`
if(numext::equal_strict(shift, right))
muCur = -muCur;
}
}
@@ -1004,7 +1012,7 @@ void BDCSVD<MatrixType>::perturbCol0
// The offset permits to skip deflated entries while computing zhat
for (Index k = 0; k < n; ++k)
{
if (col0(k) == Literal(0)) // deflated
if (numext::is_exactly_zero(col0(k))) // deflated
zhat(k) = Literal(0);
else
{
@@ -1077,7 +1085,7 @@ void BDCSVD<MatrixType>::computeSingVecs
for (Index k = 0; k < n; ++k)
{
if (zhat(k) == Literal(0))
if (numext::is_exactly_zero(zhat(k)))
{
U.col(k) = VectorType::Unit(n+1, k);
if (m_compV) V.col(k) = VectorType::Unit(n, k);
@@ -1123,7 +1131,7 @@ void BDCSVD<MatrixType>::deflation43(Eigen::Index firstCol, Eigen::Index shift,
RealScalar c = m_computed(start, start);
RealScalar s = m_computed(start+i, start);
RealScalar r = numext::hypot(c,s);
if (r == Literal(0))
if (numext::is_exactly_zero(r))
{
m_computed(start+i, start+i) = Literal(0);
return;
@@ -1163,7 +1171,7 @@ void BDCSVD<MatrixType>::deflation44(Eigen::Index firstColu , Eigen::Index first
<< m_computed(firstColm + i+1, firstColm+i+1) << " "
<< m_computed(firstColm + i+2, firstColm+i+2) << "\n";
#endif
if (r==Literal(0))
if (numext::is_exactly_zero(r))
{
m_computed(firstColm + i, firstColm + i) = m_computed(firstColm + j, firstColm + j);
return;

6
Eigen/src/SVD/JacobiSVD.h
View File

@@ -377,7 +377,7 @@ struct svd_precondition_2x2_block_to_be_real<MatrixType, QRPreconditioner, true>
const RealScalar considerAsZero = (std::numeric_limits<RealScalar>::min)();
const RealScalar precision = NumTraits<Scalar>::epsilon();
if(n==0)
if(numext::is_exactly_zero(n))
{
// make sure first column is zero
work_matrix.coeffRef(p,p) = work_matrix.coeffRef(q,p) = Scalar(0);
@@ -684,7 +684,7 @@ JacobiSVD<MatrixType, QRPreconditioner>::compute(const MatrixType& matrix, unsig
m_info = InvalidInput;
return *this;
}
if(scale==RealScalar(0)) scale = RealScalar(1);
if(numext::is_exactly_zero(scale)) scale = RealScalar(1);
/*** step 1. The R-SVD step: we use a QR decomposition to reduce to the case of a square matrix */
@@ -777,7 +777,7 @@ JacobiSVD<MatrixType, QRPreconditioner>::compute(const MatrixType& matrix, unsig
{
Index pos;
RealScalar maxRemainingSingularValue = m_singularValues.tail(m_diagSize-i).maxCoeff(&pos);
if(maxRemainingSingularValue == RealScalar(0))
if(numext::is_exactly_zero(maxRemainingSingularValue))
{
m_nonzeroSingularValues = i;
break;