Fix bug #314: - remove most of the metaprogramming kung fu in MathFunctions.h (only keep functions that differs from the std) - remove the overloads for array expression that were in the std namespace
diff --git a/unsupported/Eigen/AlignedVector3 b/unsupported/Eigen/AlignedVector3 index 8ad0eb4..7236ddd 100644 --- a/unsupported/Eigen/AlignedVector3 +++ b/unsupported/Eigen/AlignedVector3
@@ -167,7 +167,8 @@ inline Scalar norm() const { - return internal::sqrt(squaredNorm()); + using std::sqrt; + return sqrt(squaredNorm()); } inline AlignedVector3 cross(const AlignedVector3& other) const
diff --git a/unsupported/Eigen/src/FFT/ei_kissfft_impl.h b/unsupported/Eigen/src/FFT/ei_kissfft_impl.h index 37f5af4..be51b4e 100644 --- a/unsupported/Eigen/src/FFT/ei_kissfft_impl.h +++ b/unsupported/Eigen/src/FFT/ei_kissfft_impl.h
@@ -28,6 +28,7 @@ inline void make_twiddles(int nfft,bool inverse) { + using std::acos; m_inverse = inverse; m_twiddles.resize(nfft); Scalar phinc = (inverse?2:-2)* acos( (Scalar) -1) / nfft; @@ -399,6 +400,7 @@ inline Complex * real_twiddles(int ncfft2) { + using std::acos; std::vector<Complex> & twidref = m_realTwiddles[ncfft2];// creates new if not there if ( (int)twidref.size() != ncfft2 ) { twidref.resize(ncfft2);
diff --git a/unsupported/Eigen/src/IterativeSolvers/IncompleteCholesky.h b/unsupported/Eigen/src/IterativeSolvers/IncompleteCholesky.h index 5bc41c0..746d294 100644 --- a/unsupported/Eigen/src/IterativeSolvers/IncompleteCholesky.h +++ b/unsupported/Eigen/src/IterativeSolvers/IncompleteCholesky.h
@@ -116,6 +116,7 @@ template<typename _MatrixType> void IncompleteCholesky<Scalar,_UpLo, OrderingType>::factorize(const _MatrixType& mat) { + using std::sqrt; eigen_assert(m_analysisIsOk && "analyzePattern() should be called first"); // FIXME Stability: We should probably compute the scaling factors and the shifts that are needed to ensure a succesful LLT factorization and an efficient preconditioner. @@ -182,7 +183,7 @@ m_info = NumericalIssue; return; } - RealScalar rdiag = internal::sqrt(RealScalar(diag)); + RealScalar rdiag = sqrt(RealScalar(diag)); Scalar scal = Scalar(1)/rdiag; vals[colPtr[j]] = rdiag; // Insert the largest p elements in the matrix and scale them meanwhile
diff --git a/unsupported/Eigen/src/IterativeSolvers/IterationController.h b/unsupported/Eigen/src/IterativeSolvers/IterationController.h index aaf46d5..ea86dfe 100644 --- a/unsupported/Eigen/src/IterativeSolvers/IterationController.h +++ b/unsupported/Eigen/src/IterativeSolvers/IterationController.h
@@ -129,7 +129,8 @@ bool converged() const { return m_res <= m_rhsn * m_resmax; } bool converged(double nr) { - m_res = internal::abs(nr); + using std::abs; + m_res = abs(nr); m_resminreach = (std::min)(m_resminreach, m_res); return converged(); }
diff --git a/unsupported/Eigen/src/IterativeSolvers/MINRES.h b/unsupported/Eigen/src/IterativeSolvers/MINRES.h index 46d7bed..6bc1b8f 100644 --- a/unsupported/Eigen/src/IterativeSolvers/MINRES.h +++ b/unsupported/Eigen/src/IterativeSolvers/MINRES.h
@@ -32,6 +32,7 @@ const Preconditioner& precond, int& iters, typename Dest::RealScalar& tol_error) { + using std::sqrt; typedef typename Dest::RealScalar RealScalar; typedef typename Dest::Scalar Scalar; typedef Matrix<Scalar,Dynamic,1> VectorType;
diff --git a/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h b/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h index e87a28f..7d42664 100644 --- a/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h +++ b/unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h
@@ -235,6 +235,7 @@ template <typename MatrixType, typename AtomicType> void MatrixFunction<MatrixType,AtomicType,1>::partitionEigenvalues() { + using std::abs; const Index rows = m_T.rows(); VectorType diag = m_T.diagonal(); // contains eigenvalues of A @@ -251,14 +252,14 @@ // Look for other element to add to the set for (Index j=i+1; j<rows; ++j) { - if (internal::abs(diag(j) - diag(i)) <= separation() && std::find(qi->begin(), qi->end(), diag(j)) == qi->end()) { - typename ListOfClusters::iterator qj = findCluster(diag(j)); - if (qj == m_clusters.end()) { - qi->push_back(diag(j)); - } else { - qi->insert(qi->end(), qj->begin(), qj->end()); - m_clusters.erase(qj); - } + if (abs(diag(j) - diag(i)) <= separation() && std::find(qi->begin(), qi->end(), diag(j)) == qi->end()) { + typename ListOfClusters::iterator qj = findCluster(diag(j)); + if (qj == m_clusters.end()) { + qi->push_back(diag(j)); + } else { + qi->insert(qi->end(), qj->begin(), qj->end()); + m_clusters.erase(qj); + } } } }
diff --git a/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h b/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h index e1e5b77..6ec870d 100644 --- a/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h +++ b/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h
@@ -125,6 +125,7 @@ template <typename MatrixType> void MatrixLogarithmAtomic<MatrixType>::computeBig(const MatrixType& A, MatrixType& result) { + using std::pow; int numberOfSquareRoots = 0; int numberOfExtraSquareRoots = 0; int degree; @@ -141,7 +142,7 @@ degree = getPadeDegree(normTminusI); int degree2 = getPadeDegree(normTminusI / RealScalar(2)); if ((degree - degree2 <= 1) || (numberOfExtraSquareRoots == 1)) - break; + break; ++numberOfExtraSquareRoots; } MatrixType sqrtT;
diff --git a/unsupported/Eigen/src/MatrixFunctions/MatrixSquareRoot.h b/unsupported/Eigen/src/MatrixFunctions/MatrixSquareRoot.h index 3786510..abbf640 100644 --- a/unsupported/Eigen/src/MatrixFunctions/MatrixSquareRoot.h +++ b/unsupported/Eigen/src/MatrixFunctions/MatrixSquareRoot.h
@@ -99,11 +99,12 @@ void MatrixSquareRootQuasiTriangular<MatrixType>::computeDiagonalPartOfSqrt(MatrixType& sqrtT, const MatrixType& T) { + using std::sqrt; const Index size = m_A.rows(); for (Index i = 0; i < size; i++) { if (i == size - 1 || T.coeff(i+1, i) == 0) { eigen_assert(T(i,i) > 0); - sqrtT.coeffRef(i,i) = internal::sqrt(T.coeff(i,i)); + sqrtT.coeffRef(i,i) = sqrt(T.coeff(i,i)); } else { compute2x2diagonalBlock(sqrtT, T, i); @@ -289,6 +290,7 @@ template <typename ResultType> void MatrixSquareRootTriangular<MatrixType>::compute(ResultType &result) { + using std::sqrt; // Compute Schur decomposition of m_A const ComplexSchur<MatrixType> schurOfA(m_A); const MatrixType& T = schurOfA.matrixT(); @@ -299,7 +301,7 @@ result.resize(m_A.rows(), m_A.cols()); typedef typename MatrixType::Index Index; for (Index i = 0; i < m_A.rows(); i++) { - result.coeffRef(i,i) = internal::sqrt(T.coeff(i,i)); + result.coeffRef(i,i) = sqrt(T.coeff(i,i)); } for (Index j = 1; j < m_A.cols(); j++) { for (Index i = j-1; i >= 0; i--) {
diff --git a/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h b/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h index d9ce4ea..b190827 100644 --- a/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h +++ b/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h
@@ -52,7 +52,7 @@ Parameters() : factor(Scalar(100.)) , maxfev(1000) - , xtol(internal::sqrt(NumTraits<Scalar>::epsilon())) + , xtol(std::sqrt(NumTraits<Scalar>::epsilon())) , nb_of_subdiagonals(-1) , nb_of_superdiagonals(-1) , epsfcn(Scalar(0.)) {} @@ -70,7 +70,7 @@ HybridNonLinearSolverSpace::Status hybrj1( FVectorType &x, - const Scalar tol = internal::sqrt(NumTraits<Scalar>::epsilon()) + const Scalar tol = std::sqrt(NumTraits<Scalar>::epsilon()) ); HybridNonLinearSolverSpace::Status solveInit(FVectorType &x); @@ -79,7 +79,7 @@ HybridNonLinearSolverSpace::Status hybrd1( FVectorType &x, - const Scalar tol = internal::sqrt(NumTraits<Scalar>::epsilon()) + const Scalar tol = std::sqrt(NumTraits<Scalar>::epsilon()) ); HybridNonLinearSolverSpace::Status solveNumericalDiffInit(FVectorType &x); @@ -185,6 +185,8 @@ HybridNonLinearSolverSpace::Status HybridNonLinearSolver<FunctorType,Scalar>::solveOneStep(FVectorType &x) { + using std::abs; + assert(x.size()==n); // check the caller is not cheating us Index j; @@ -276,7 +278,7 @@ ++ncsuc; if (ratio >= Scalar(.5) || ncsuc > 1) delta = (std::max)(delta, pnorm / Scalar(.5)); - if (internal::abs(ratio - 1.) <= Scalar(.1)) { + if (abs(ratio - 1.) <= Scalar(.1)) { delta = pnorm / Scalar(.5); } } @@ -423,6 +425,9 @@ HybridNonLinearSolverSpace::Status HybridNonLinearSolver<FunctorType,Scalar>::solveNumericalDiffOneStep(FVectorType &x) { + using std::sqrt; + using std::abs; + assert(x.size()==n); // check the caller is not cheating us Index j; @@ -516,7 +521,7 @@ ++ncsuc; if (ratio >= Scalar(.5) || ncsuc > 1) delta = (std::max)(delta, pnorm / Scalar(.5)); - if (internal::abs(ratio - 1.) <= Scalar(.1)) { + if (abs(ratio - 1.) <= Scalar(.1)) { delta = pnorm / Scalar(.5); } }
diff --git a/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h b/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h index 075faee..4b1a2d0 100644 --- a/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h +++ b/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h
@@ -55,8 +55,8 @@ Parameters() : factor(Scalar(100.)) , maxfev(400) - , ftol(internal::sqrt(NumTraits<Scalar>::epsilon())) - , xtol(internal::sqrt(NumTraits<Scalar>::epsilon())) + , ftol(std::sqrt(NumTraits<Scalar>::epsilon())) + , xtol(std::sqrt(NumTraits<Scalar>::epsilon())) , gtol(Scalar(0.)) , epsfcn(Scalar(0.)) {} Scalar factor; @@ -72,7 +72,7 @@ LevenbergMarquardtSpace::Status lmder1( FVectorType &x, - const Scalar tol = internal::sqrt(NumTraits<Scalar>::epsilon()) + const Scalar tol = std::sqrt(NumTraits<Scalar>::epsilon()) ); LevenbergMarquardtSpace::Status minimize(FVectorType &x); @@ -83,12 +83,12 @@ FunctorType &functor, FVectorType &x, Index *nfev, - const Scalar tol = internal::sqrt(NumTraits<Scalar>::epsilon()) + const Scalar tol = std::sqrt(NumTraits<Scalar>::epsilon()) ); LevenbergMarquardtSpace::Status lmstr1( FVectorType &x, - const Scalar tol = internal::sqrt(NumTraits<Scalar>::epsilon()) + const Scalar tol = std::sqrt(NumTraits<Scalar>::epsilon()) ); LevenbergMarquardtSpace::Status minimizeOptimumStorage(FVectorType &x); @@ -206,6 +206,9 @@ LevenbergMarquardtSpace::Status LevenbergMarquardt<FunctorType,Scalar>::minimizeOneStep(FVectorType &x) { + using std::abs; + using std::sqrt; + assert(x.size()==n); // check the caller is not cheating us /* calculate the jacobian matrix. */ @@ -249,7 +252,7 @@ if (fnorm != 0.) for (Index j = 0; j < n; ++j) if (wa2[permutation.indices()[j]] != 0.) - gnorm = (std::max)(gnorm, internal::abs( fjac.col(j).head(j+1).dot(qtf.head(j+1)/fnorm) / wa2[permutation.indices()[j]])); + gnorm = (std::max)(gnorm, abs( fjac.col(j).head(j+1).dot(qtf.head(j+1)/fnorm) / wa2[permutation.indices()[j]])); /* test for convergence of the gradient norm. */ if (gnorm <= parameters.gtol) @@ -288,7 +291,7 @@ /* the scaled directional derivative. */ wa3 = fjac.template triangularView<Upper>() * (qrfac.colsPermutation().inverse() *wa1); temp1 = internal::abs2(wa3.stableNorm() / fnorm); - temp2 = internal::abs2(internal::sqrt(par) * pnorm / fnorm); + temp2 = internal::abs2(sqrt(par) * pnorm / fnorm); prered = temp1 + temp2 / Scalar(.5); dirder = -(temp1 + temp2); @@ -326,9 +329,9 @@ } /* tests for convergence. */ - if (internal::abs(actred) <= parameters.ftol && prered <= parameters.ftol && Scalar(.5) * ratio <= 1. && delta <= parameters.xtol * xnorm) + if (abs(actred) <= parameters.ftol && prered <= parameters.ftol && Scalar(.5) * ratio <= 1. && delta <= parameters.xtol * xnorm) return LevenbergMarquardtSpace::RelativeErrorAndReductionTooSmall; - if (internal::abs(actred) <= parameters.ftol && prered <= parameters.ftol && Scalar(.5) * ratio <= 1.) + if (abs(actred) <= parameters.ftol && prered <= parameters.ftol && Scalar(.5) * ratio <= 1.) return LevenbergMarquardtSpace::RelativeReductionTooSmall; if (delta <= parameters.xtol * xnorm) return LevenbergMarquardtSpace::RelativeErrorTooSmall; @@ -336,7 +339,7 @@ /* tests for termination and stringent tolerances. */ if (nfev >= parameters.maxfev) return LevenbergMarquardtSpace::TooManyFunctionEvaluation; - if (internal::abs(actred) <= NumTraits<Scalar>::epsilon() && prered <= NumTraits<Scalar>::epsilon() && Scalar(.5) * ratio <= 1.) + if (abs(actred) <= NumTraits<Scalar>::epsilon() && prered <= NumTraits<Scalar>::epsilon() && Scalar(.5) * ratio <= 1.) return LevenbergMarquardtSpace::FtolTooSmall; if (delta <= NumTraits<Scalar>::epsilon() * xnorm) return LevenbergMarquardtSpace::XtolTooSmall; @@ -423,6 +426,9 @@ LevenbergMarquardtSpace::Status LevenbergMarquardt<FunctorType,Scalar>::minimizeOptimumStorageOneStep(FVectorType &x) { + using std::abs; + using std::sqrt; + assert(x.size()==n); // check the caller is not cheating us Index i, j; @@ -496,7 +502,7 @@ if (fnorm != 0.) for (j = 0; j < n; ++j) if (wa2[permutation.indices()[j]] != 0.) - gnorm = (std::max)(gnorm, internal::abs( fjac.col(j).head(j+1).dot(qtf.head(j+1)/fnorm) / wa2[permutation.indices()[j]])); + gnorm = (std::max)(gnorm, abs( fjac.col(j).head(j+1).dot(qtf.head(j+1)/fnorm) / wa2[permutation.indices()[j]])); /* test for convergence of the gradient norm. */ if (gnorm <= parameters.gtol) @@ -535,7 +541,7 @@ /* the scaled directional derivative. */ wa3 = fjac.topLeftCorner(n,n).template triangularView<Upper>() * (permutation.inverse() * wa1); temp1 = internal::abs2(wa3.stableNorm() / fnorm); - temp2 = internal::abs2(internal::sqrt(par) * pnorm / fnorm); + temp2 = internal::abs2(sqrt(par) * pnorm / fnorm); prered = temp1 + temp2 / Scalar(.5); dirder = -(temp1 + temp2); @@ -573,9 +579,9 @@ } /* tests for convergence. */ - if (internal::abs(actred) <= parameters.ftol && prered <= parameters.ftol && Scalar(.5) * ratio <= 1. && delta <= parameters.xtol * xnorm) + if (abs(actred) <= parameters.ftol && prered <= parameters.ftol && Scalar(.5) * ratio <= 1. && delta <= parameters.xtol * xnorm) return LevenbergMarquardtSpace::RelativeErrorAndReductionTooSmall; - if (internal::abs(actred) <= parameters.ftol && prered <= parameters.ftol && Scalar(.5) * ratio <= 1.) + if (abs(actred) <= parameters.ftol && prered <= parameters.ftol && Scalar(.5) * ratio <= 1.) return LevenbergMarquardtSpace::RelativeReductionTooSmall; if (delta <= parameters.xtol * xnorm) return LevenbergMarquardtSpace::RelativeErrorTooSmall; @@ -583,7 +589,7 @@ /* tests for termination and stringent tolerances. */ if (nfev >= parameters.maxfev) return LevenbergMarquardtSpace::TooManyFunctionEvaluation; - if (internal::abs(actred) <= NumTraits<Scalar>::epsilon() && prered <= NumTraits<Scalar>::epsilon() && Scalar(.5) * ratio <= 1.) + if (abs(actred) <= NumTraits<Scalar>::epsilon() && prered <= NumTraits<Scalar>::epsilon() && Scalar(.5) * ratio <= 1.) return LevenbergMarquardtSpace::FtolTooSmall; if (delta <= NumTraits<Scalar>::epsilon() * xnorm) return LevenbergMarquardtSpace::XtolTooSmall;
diff --git a/unsupported/Eigen/src/NonLinearOptimization/chkder.h b/unsupported/Eigen/src/NonLinearOptimization/chkder.h index ad37c50..db8ff7d 100644 --- a/unsupported/Eigen/src/NonLinearOptimization/chkder.h +++ b/unsupported/Eigen/src/NonLinearOptimization/chkder.h
@@ -16,6 +16,10 @@ Matrix< Scalar, Dynamic, 1 > &err ) { + using std::sqrt; + using std::abs; + using std::log; + typedef DenseIndex Index; const Scalar eps = sqrt(NumTraits<Scalar>::epsilon());
diff --git a/unsupported/Eigen/src/NonLinearOptimization/covar.h b/unsupported/Eigen/src/NonLinearOptimization/covar.h index c73a096..c2fb794 100644 --- a/unsupported/Eigen/src/NonLinearOptimization/covar.h +++ b/unsupported/Eigen/src/NonLinearOptimization/covar.h
@@ -6,8 +6,9 @@ void covar( Matrix< Scalar, Dynamic, Dynamic > &r, const VectorXi &ipvt, - Scalar tol = sqrt(NumTraits<Scalar>::epsilon()) ) + Scalar tol = std::sqrt(NumTraits<Scalar>::epsilon()) ) { + using std::abs; typedef DenseIndex Index; /* Local variables */
diff --git a/unsupported/Eigen/src/NonLinearOptimization/dogleg.h b/unsupported/Eigen/src/NonLinearOptimization/dogleg.h index 4fbc98b..57dbc8b 100644 --- a/unsupported/Eigen/src/NonLinearOptimization/dogleg.h +++ b/unsupported/Eigen/src/NonLinearOptimization/dogleg.h
@@ -10,6 +10,9 @@ Scalar delta, Matrix< Scalar, Dynamic, 1 > &x) { + using std::abs; + using std::sqrt; + typedef DenseIndex Index; /* Local variables */
diff --git a/unsupported/Eigen/src/NonLinearOptimization/fdjac1.h b/unsupported/Eigen/src/NonLinearOptimization/fdjac1.h index 1cabe69..0594793 100644 --- a/unsupported/Eigen/src/NonLinearOptimization/fdjac1.h +++ b/unsupported/Eigen/src/NonLinearOptimization/fdjac1.h
@@ -11,6 +11,9 @@ DenseIndex ml, DenseIndex mu, Scalar epsfcn) { + using std::sqrt; + using std::abs; + typedef DenseIndex Index; /* Local variables */
diff --git a/unsupported/Eigen/src/NonLinearOptimization/lmpar.h b/unsupported/Eigen/src/NonLinearOptimization/lmpar.h index 8aac575..834407c 100644 --- a/unsupported/Eigen/src/NonLinearOptimization/lmpar.h +++ b/unsupported/Eigen/src/NonLinearOptimization/lmpar.h
@@ -12,6 +12,8 @@ Scalar &par, Matrix< Scalar, Dynamic, 1 > &x) { + using std::abs; + using std::sqrt; typedef DenseIndex Index; /* Local variables */ @@ -168,6 +170,8 @@ Matrix< Scalar, Dynamic, 1 > &x) { + using std::sqrt; + using std::abs; typedef DenseIndex Index; /* Local variables */
diff --git a/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h b/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h index d848cb4..7ee30e1 100644 --- a/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h +++ b/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h
@@ -63,11 +63,13 @@ */ int df(const InputType& _x, JacobianType &jac) const { + using std::sqrt; + using std::abs; /* Local variables */ Scalar h; int nfev=0; const typename InputType::Index n = _x.size(); - const Scalar eps = internal::sqrt(((std::max)(epsfcn,NumTraits<Scalar>::epsilon() ))); + const Scalar eps = sqrt(((std::max)(epsfcn,NumTraits<Scalar>::epsilon() ))); ValueType val1, val2; InputType x = _x; // TODO : we should do this only if the size is not already known @@ -89,7 +91,7 @@ // Function Body for (int j = 0; j < n; ++j) { - h = eps * internal::abs(x[j]); + h = eps * abs(x[j]); if (h == 0.) { h = eps; }
diff --git a/unsupported/Eigen/src/Polynomials/Companion.h b/unsupported/Eigen/src/Polynomials/Companion.h index 4badd9d..b515c29 100644 --- a/unsupported/Eigen/src/Polynomials/Companion.h +++ b/unsupported/Eigen/src/Polynomials/Companion.h
@@ -210,6 +210,7 @@ template< typename _Scalar, int _Deg > void companion<_Scalar,_Deg>::balance() { + using std::abs; EIGEN_STATIC_ASSERT( Deg == Dynamic || 1 < Deg, YOU_MADE_A_PROGRAMMING_MISTAKE ); const Index deg = m_monic.size(); const Index deg_1 = deg-1;
diff --git a/unsupported/Eigen/src/Polynomials/PolynomialSolver.h b/unsupported/Eigen/src/Polynomials/PolynomialSolver.h index 70b873d..fba8fc9 100644 --- a/unsupported/Eigen/src/Polynomials/PolynomialSolver.h +++ b/unsupported/Eigen/src/Polynomials/PolynomialSolver.h
@@ -69,10 +69,11 @@ inline void realRoots( Stl_back_insertion_sequence& bi_seq, const RealScalar& absImaginaryThreshold = NumTraits<Scalar>::dummy_precision() ) const { + using std::abs; bi_seq.clear(); for(Index i=0; i<m_roots.size(); ++i ) { - if( internal::abs( m_roots[i].imag() ) < absImaginaryThreshold ){ + if( abs( m_roots[i].imag() ) < absImaginaryThreshold ){ bi_seq.push_back( m_roots[i].real() ); } } } @@ -118,13 +119,14 @@ bool& hasArealRoot, const RealScalar& absImaginaryThreshold = NumTraits<Scalar>::dummy_precision() ) const { + using std::abs; hasArealRoot = false; Index res=0; RealScalar abs2(0); for( Index i=0; i<m_roots.size(); ++i ) { - if( internal::abs( m_roots[i].imag() ) < absImaginaryThreshold ) + if( abs( m_roots[i].imag() ) < absImaginaryThreshold ) { if( !hasArealRoot ) { @@ -144,7 +146,7 @@ } else { - if( internal::abs( m_roots[i].imag() ) < internal::abs( m_roots[res].imag() ) ){ + if( abs( m_roots[i].imag() ) < abs( m_roots[res].imag() ) ){ res = i; } } } @@ -158,13 +160,14 @@ bool& hasArealRoot, const RealScalar& absImaginaryThreshold = NumTraits<Scalar>::dummy_precision() ) const { + using std::abs; hasArealRoot = false; Index res=0; RealScalar val(0); for( Index i=0; i<m_roots.size(); ++i ) { - if( internal::abs( m_roots[i].imag() ) < absImaginaryThreshold ) + if( abs( m_roots[i].imag() ) < absImaginaryThreshold ) { if( !hasArealRoot ) { @@ -184,7 +187,7 @@ } else { - if( internal::abs( m_roots[i].imag() ) < internal::abs( m_roots[res].imag() ) ){ + if( abs( m_roots[i].imag() ) < abs( m_roots[res].imag() ) ){ res = i; } } }
diff --git a/unsupported/Eigen/src/Polynomials/PolynomialUtils.h b/unsupported/Eigen/src/Polynomials/PolynomialUtils.h index c23204c..5a9ab11 100644 --- a/unsupported/Eigen/src/Polynomials/PolynomialUtils.h +++ b/unsupported/Eigen/src/Polynomials/PolynomialUtils.h
@@ -74,6 +74,7 @@ inline typename NumTraits<typename Polynomial::Scalar>::Real cauchy_max_bound( const Polynomial& poly ) { + using std::abs; typedef typename Polynomial::Scalar Scalar; typedef typename NumTraits<Scalar>::Real Real; @@ -82,7 +83,7 @@ Real cb(0); for( DenseIndex i=0; i<poly.size()-1; ++i ){ - cb += internal::abs(poly[i]*inv_leading_coeff); } + cb += abs(poly[i]*inv_leading_coeff); } return cb + Real(1); } @@ -96,6 +97,7 @@ inline typename NumTraits<typename Polynomial::Scalar>::Real cauchy_min_bound( const Polynomial& poly ) { + using std::abs; typedef typename Polynomial::Scalar Scalar; typedef typename NumTraits<Scalar>::Real Real; @@ -107,7 +109,7 @@ const Scalar inv_min_coeff = Scalar(1)/poly[i]; Real cb(1); for( DenseIndex j=i+1; j<poly.size(); ++j ){ - cb += internal::abs(poly[j]*inv_min_coeff); } + cb += abs(poly[j]*inv_min_coeff); } return Real(1)/cb; }
diff --git a/unsupported/doc/examples/PolynomialSolver1.cpp b/unsupported/doc/examples/PolynomialSolver1.cpp index 71e6b82..cd777a4 100644 --- a/unsupported/doc/examples/PolynomialSolver1.cpp +++ b/unsupported/doc/examples/PolynomialSolver1.cpp
@@ -49,5 +49,5 @@ cout.precision(10); cout << "The last root in float then in double: " << psolvef.roots()[5] << "\t" << psolve6d.roots()[5] << endl; std::complex<float> castedRoot( psolve6d.roots()[5].real(), psolve6d.roots()[5].imag() ); - cout << "Norm of the difference: " << internal::abs( psolvef.roots()[5] - castedRoot ) << endl; + cout << "Norm of the difference: " << std::abs( psolvef.roots()[5] - castedRoot ) << endl; }
diff --git a/unsupported/test/NonLinearOptimization.cpp b/unsupported/test/NonLinearOptimization.cpp index 983d80e..d7376b0 100644 --- a/unsupported/test/NonLinearOptimization.cpp +++ b/unsupported/test/NonLinearOptimization.cpp
@@ -12,6 +12,8 @@ // It is intended to be done for this test only. #include <Eigen/src/Core/util/DisableStupidWarnings.h> +using std::sqrt; + int fcn_chkder(const VectorXd &x, VectorXd &fvec, MatrixXd &fjac, int iflag) { /* subroutine fcn for chkder example. */ @@ -795,7 +797,9 @@ static const double m_x[236]; int operator()(const VectorXd &b, VectorXd &fvec) { - static const double m_y[236] = { .591E0 , 1.547E0 , 2.902E0 , 2.894E0 , 4.703E0 , 6.307E0 , 7.03E0 , 7.898E0 , 9.470E0 , 9.484E0 , 10.072E0 , 10.163E0 , 11.615E0 , 12.005E0 , 12.478E0 , 12.982E0 , 12.970E0 , 13.926E0 , 14.452E0 , 14.404E0 , 15.190E0 , 15.550E0 , 15.528E0 , 15.499E0 , 16.131E0 , 16.438E0 , 16.387E0 , 16.549E0 , 16.872E0 , 16.830E0 , 16.926E0 , 16.907E0 , 16.966E0 , 17.060E0 , 17.122E0 , 17.311E0 , 17.355E0 , 17.668E0 , 17.767E0 , 17.803E0 , 17.765E0 , 17.768E0 , 17.736E0 , 17.858E0 , 17.877E0 , 17.912E0 , 18.046E0 , 18.085E0 , 18.291E0 , 18.357E0 , 18.426E0 , 18.584E0 , 18.610E0 , 18.870E0 , 18.795E0 , 19.111E0 , .367E0 , .796E0 , 0.892E0 , 1.903E0 , 2.150E0 , 3.697E0 , 5.870E0 , 6.421E0 , 7.422E0 , 9.944E0 , 11.023E0 , 11.87E0 , 12.786E0 , 14.067E0 , 13.974E0 , 14.462E0 , 14.464E0 , 15.381E0 , 15.483E0 , 15.59E0 , 16.075E0 , 16.347E0 , 16.181E0 , 16.915E0 , 17.003E0 , 16.978E0 , 17.756E0 , 17.808E0 , 17.868E0 , 18.481E0 , 18.486E0 , 19.090E0 , 16.062E0 , 16.337E0 , 16.345E0 , 16.388E0 , 17.159E0 , 17.116E0 , 17.164E0 , 17.123E0 , 17.979E0 , 17.974E0 , 18.007E0 , 17.993E0 , 18.523E0 , 18.669E0 , 18.617E0 , 19.371E0 , 19.330E0 , 0.080E0 , 0.248E0 , 1.089E0 , 1.418E0 , 2.278E0 , 3.624E0 , 4.574E0 , 5.556E0 , 7.267E0 , 7.695E0 , 9.136E0 , 9.959E0 , 9.957E0 , 11.600E0 , 13.138E0 , 13.564E0 , 13.871E0 , 13.994E0 , 14.947E0 , 15.473E0 , 15.379E0 , 15.455E0 , 15.908E0 , 16.114E0 , 17.071E0 , 17.135E0 , 17.282E0 , 17.368E0 , 17.483E0 , 17.764E0 , 18.185E0 , 18.271E0 , 18.236E0 , 18.237E0 , 18.523E0 , 18.627E0 , 18.665E0 , 19.086E0 , 0.214E0 , 0.943E0 , 1.429E0 , 2.241E0 , 2.951E0 , 3.782E0 , 4.757E0 , 5.602E0 , 7.169E0 , 8.920E0 , 10.055E0 , 12.035E0 , 12.861E0 , 13.436E0 , 14.167E0 , 14.755E0 , 15.168E0 , 15.651E0 , 15.746E0 , 16.216E0 , 16.445E0 , 16.965E0 , 17.121E0 , 17.206E0 , 17.250E0 , 17.339E0 , 17.793E0 , 18.123E0 , 18.49E0 , 18.566E0 , 18.645E0 , 18.706E0 , 18.924E0 , 19.1E0 , 0.375E0 , 0.471E0 , 1.504E0 , 2.204E0 , 2.813E0 , 4.765E0 , 9.835E0 , 10.040E0 , 11.946E0 , 12.596E0 , 13.303E0 , 13.922E0 , 14.440E0 , 14.951E0 , 15.627E0 , 15.639E0 , 15.814E0 , 16.315E0 , 16.334E0 , 16.430E0 , 16.423E0 , 17.024E0 , 17.009E0 , 17.165E0 , 17.134E0 , 17.349E0 , 17.576E0 , 17.848E0 , 18.090E0 , 18.276E0 , 18.404E0 , 18.519E0 , 19.133E0 , 19.074E0 , 19.239E0 , 19.280E0 , 19.101E0 , 19.398E0 , 19.252E0 , 19.89E0 , 20.007E0 , 19.929E0 , 19.268E0 , 19.324E0 , 20.049E0 , 20.107E0 , 20.062E0 , 20.065E0 , 19.286E0 , 19.972E0 , 20.088E0 , 20.743E0 , 20.83E0 , 20.935E0 , 21.035E0 , 20.93E0 , 21.074E0 , 21.085E0 , 20.935E0 }; + static const double m_y[236] = { .591E0 , 1.547E0 , 2.902E0 , 2.894E0 , 4.703E0 , 6.307E0 , 7.03E0 , 7.898E0 , 9.470E0 , 9.484E0 , 10.072E0 , 10.163E0 , 11.615E0 , 12.005E0 , 12.478E0 , 12.982E0 , 12.970E0 , 13.926E0 , 14.452E0 , 14.404E0 , 15.190E0 , 15.550E0 , 15.528E0 , 15.499E0 , 16.131E0 , 16.438E0 , 16.387E0 , 16.549E0 , 16.872E0 , 16.830E0 , 16.926E0 , 16.907E0 , 16.966E0 , 17.060E0 , 17.122E0 , 17.311E0 , 17.355E0 , 17.668E0 , 17.767E0 , 17.803E0 , 17.765E0 , 17.768E0 , 17.736E0 , 17.858E0 , 17.877E0 , 17.912E0 , 18.046E0 , 18.085E0 , 18.291E0 , 18.357E0 , 18.426E0 , 18.584E0 , 18.610E0 , 18.870E0 , 18.795E0 , 19.111E0 , .367E0 , .796E0 , 0.892E0 , 1.903E0 , 2.150E0 , 3.697E0 , 5.870E0 , 6.421E0 , 7.422E0 , 9.944E0 , 11.023E0 , 11.87E0 , 12.786E0 , 14.067E0 , 13.974E0 , 14.462E0 , 14.464E0 , 15.381E0 , 15.483E0 , 15.59E0 , 16.075E0 , 16.347E0 , 16.181E0 , 16.915E0 , 17.003E0 , 16.978E0 , 17.756E0 , 17.808E0 , 17.868E0 , 18.481E0 , 18.486E0 , 19.090E0 , 16.062E0 , 16.337E0 , 16.345E0 , + 16.388E0 , 17.159E0 , 17.116E0 , 17.164E0 , 17.123E0 , 17.979E0 , 17.974E0 , 18.007E0 , 17.993E0 , 18.523E0 , 18.669E0 , 18.617E0 , 19.371E0 , 19.330E0 , 0.080E0 , 0.248E0 , 1.089E0 , 1.418E0 , 2.278E0 , 3.624E0 , 4.574E0 , 5.556E0 , 7.267E0 , 7.695E0 , 9.136E0 , 9.959E0 , 9.957E0 , 11.600E0 , 13.138E0 , 13.564E0 , 13.871E0 , 13.994E0 , 14.947E0 , 15.473E0 , 15.379E0 , 15.455E0 , 15.908E0 , 16.114E0 , 17.071E0 , 17.135E0 , 17.282E0 , 17.368E0 , 17.483E0 , 17.764E0 , 18.185E0 , 18.271E0 , 18.236E0 , 18.237E0 , 18.523E0 , 18.627E0 , 18.665E0 , 19.086E0 , 0.214E0 , 0.943E0 , 1.429E0 , 2.241E0 , 2.951E0 , 3.782E0 , 4.757E0 , 5.602E0 , 7.169E0 , 8.920E0 , 10.055E0 , 12.035E0 , 12.861E0 , 13.436E0 , 14.167E0 , 14.755E0 , 15.168E0 , 15.651E0 , 15.746E0 , 16.216E0 , 16.445E0 , 16.965E0 , 17.121E0 , 17.206E0 , 17.250E0 , 17.339E0 , 17.793E0 , 18.123E0 , 18.49E0 , 18.566E0 , 18.645E0 , 18.706E0 , 18.924E0 , 19.1E0 , 0.375E0 , 0.471E0 , 1.504E0 , 2.204E0 , 2.813E0 , 4.765E0 , 9.835E0 , 10.040E0 , 11.946E0 , 12.596E0 , +13.303E0 , 13.922E0 , 14.440E0 , 14.951E0 , 15.627E0 , 15.639E0 , 15.814E0 , 16.315E0 , 16.334E0 , 16.430E0 , 16.423E0 , 17.024E0 , 17.009E0 , 17.165E0 , 17.134E0 , 17.349E0 , 17.576E0 , 17.848E0 , 18.090E0 , 18.276E0 , 18.404E0 , 18.519E0 , 19.133E0 , 19.074E0 , 19.239E0 , 19.280E0 , 19.101E0 , 19.398E0 , 19.252E0 , 19.89E0 , 20.007E0 , 19.929E0 , 19.268E0 , 19.324E0 , 20.049E0 , 20.107E0 , 20.062E0 , 20.065E0 , 19.286E0 , 19.972E0 , 20.088E0 , 20.743E0 , 20.83E0 , 20.935E0 , 21.035E0 , 20.93E0 , 21.074E0 , 21.085E0 , 20.935E0 }; // int called=0; printf("call hahn1_functor with iflag=%d, called=%d\n", iflag, called); if (iflag==1) called++; @@ -828,7 +832,9 @@ return 0; } }; -const double hahn1_functor::m_x[236] = { 24.41E0 , 34.82E0 , 44.09E0 , 45.07E0 , 54.98E0 , 65.51E0 , 70.53E0 , 75.70E0 , 89.57E0 , 91.14E0 , 96.40E0 , 97.19E0 , 114.26E0 , 120.25E0 , 127.08E0 , 133.55E0 , 133.61E0 , 158.67E0 , 172.74E0 , 171.31E0 , 202.14E0 , 220.55E0 , 221.05E0 , 221.39E0 , 250.99E0 , 268.99E0 , 271.80E0 , 271.97E0 , 321.31E0 , 321.69E0 , 330.14E0 , 333.03E0 , 333.47E0 , 340.77E0 , 345.65E0 , 373.11E0 , 373.79E0 , 411.82E0 , 419.51E0 , 421.59E0 , 422.02E0 , 422.47E0 , 422.61E0 , 441.75E0 , 447.41E0 , 448.7E0 , 472.89E0 , 476.69E0 , 522.47E0 , 522.62E0 , 524.43E0 , 546.75E0 , 549.53E0 , 575.29E0 , 576.00E0 , 625.55E0 , 20.15E0 , 28.78E0 , 29.57E0 , 37.41E0 , 39.12E0 , 50.24E0 , 61.38E0 , 66.25E0 , 73.42E0 , 95.52E0 , 107.32E0 , 122.04E0 , 134.03E0 , 163.19E0 , 163.48E0 , 175.70E0 , 179.86E0 , 211.27E0 , 217.78E0 , 219.14E0 , 262.52E0 , 268.01E0 , 268.62E0 , 336.25E0 , 337.23E0 , 339.33E0 , 427.38E0 , 428.58E0 , 432.68E0 , 528.99E0 , 531.08E0 , 628.34E0 , 253.24E0 , 273.13E0 , 273.66E0 , 282.10E0 , 346.62E0 , 347.19E0 , 348.78E0 , 351.18E0 , 450.10E0 , 450.35E0 , 451.92E0 , 455.56E0 , 552.22E0 , 553.56E0 , 555.74E0 , 652.59E0 , 656.20E0 , 14.13E0 , 20.41E0 , 31.30E0 , 33.84E0 , 39.70E0 , 48.83E0 , 54.50E0 , 60.41E0 , 72.77E0 , 75.25E0 , 86.84E0 , 94.88E0 , 96.40E0 , 117.37E0 , 139.08E0 , 147.73E0 , 158.63E0 , 161.84E0 , 192.11E0 , 206.76E0 , 209.07E0 , 213.32E0 , 226.44E0 , 237.12E0 , 330.90E0 , 358.72E0 , 370.77E0 , 372.72E0 , 396.24E0 , 416.59E0 , 484.02E0 , 495.47E0 , 514.78E0 , 515.65E0 , 519.47E0 , 544.47E0 , 560.11E0 , 620.77E0 , 18.97E0 , 28.93E0 , 33.91E0 , 40.03E0 , 44.66E0 , 49.87E0 , 55.16E0 , 60.90E0 , 72.08E0 , 85.15E0 , 97.06E0 , 119.63E0 , 133.27E0 , 143.84E0 , 161.91E0 , 180.67E0 , 198.44E0 , 226.86E0 , 229.65E0 , 258.27E0 , 273.77E0 , 339.15E0 , 350.13E0 , 362.75E0 , 371.03E0 , 393.32E0 , 448.53E0 , 473.78E0 , 511.12E0 , 524.70E0 , 548.75E0 , 551.64E0 , 574.02E0 , 623.86E0 , 21.46E0 , 24.33E0 , 33.43E0 , 39.22E0 , 44.18E0 , 55.02E0 , 94.33E0 , 96.44E0 , 118.82E0 , 128.48E0 , 141.94E0 , 156.92E0 , 171.65E0 , 190.00E0 , 223.26E0 , 223.88E0 , 231.50E0 , 265.05E0 , 269.44E0 , 271.78E0 , 273.46E0 , 334.61E0 , 339.79E0 , 349.52E0 , 358.18E0 , 377.98E0 , 394.77E0 , 429.66E0 , 468.22E0 , 487.27E0 , 519.54E0 , 523.03E0 , 612.99E0 , 638.59E0 , 641.36E0 , 622.05E0 , 631.50E0 , 663.97E0 , 646.9E0 , 748.29E0 , 749.21E0 , 750.14E0 , 647.04E0 , 646.89E0 , 746.9E0 , 748.43E0 , 747.35E0 , 749.27E0 , 647.61E0 , 747.78E0 , 750.51E0 , 851.37E0 , 845.97E0 , 847.54E0 , 849.93E0 , 851.61E0 , 849.75E0 , 850.98E0 , 848.23E0}; +const double hahn1_functor::m_x[236] = { 24.41E0 , 34.82E0 , 44.09E0 , 45.07E0 , 54.98E0 , 65.51E0 , 70.53E0 , 75.70E0 , 89.57E0 , 91.14E0 , 96.40E0 , 97.19E0 , 114.26E0 , 120.25E0 , 127.08E0 , 133.55E0 , 133.61E0 , 158.67E0 , 172.74E0 , 171.31E0 , 202.14E0 , 220.55E0 , 221.05E0 , 221.39E0 , 250.99E0 , 268.99E0 , 271.80E0 , 271.97E0 , 321.31E0 , 321.69E0 , 330.14E0 , 333.03E0 , 333.47E0 , 340.77E0 , 345.65E0 , 373.11E0 , 373.79E0 , 411.82E0 , 419.51E0 , 421.59E0 , 422.02E0 , 422.47E0 , 422.61E0 , 441.75E0 , 447.41E0 , 448.7E0 , 472.89E0 , 476.69E0 , 522.47E0 , 522.62E0 , 524.43E0 , 546.75E0 , 549.53E0 , 575.29E0 , 576.00E0 , 625.55E0 , 20.15E0 , 28.78E0 , 29.57E0 , 37.41E0 , 39.12E0 , 50.24E0 , 61.38E0 , 66.25E0 , 73.42E0 , 95.52E0 , 107.32E0 , 122.04E0 , 134.03E0 , 163.19E0 , 163.48E0 , 175.70E0 , 179.86E0 , 211.27E0 , 217.78E0 , 219.14E0 , 262.52E0 , 268.01E0 , 268.62E0 , 336.25E0 , 337.23E0 , 339.33E0 , 427.38E0 , 428.58E0 , 432.68E0 , 528.99E0 , 531.08E0 , 628.34E0 , 253.24E0 , 273.13E0 , 273.66E0 , +282.10E0 , 346.62E0 , 347.19E0 , 348.78E0 , 351.18E0 , 450.10E0 , 450.35E0 , 451.92E0 , 455.56E0 , 552.22E0 , 553.56E0 , 555.74E0 , 652.59E0 , 656.20E0 , 14.13E0 , 20.41E0 , 31.30E0 , 33.84E0 , 39.70E0 , 48.83E0 , 54.50E0 , 60.41E0 , 72.77E0 , 75.25E0 , 86.84E0 , 94.88E0 , 96.40E0 , 117.37E0 , 139.08E0 , 147.73E0 , 158.63E0 , 161.84E0 , 192.11E0 , 206.76E0 , 209.07E0 , 213.32E0 , 226.44E0 , 237.12E0 , 330.90E0 , 358.72E0 , 370.77E0 , 372.72E0 , 396.24E0 , 416.59E0 , 484.02E0 , 495.47E0 , 514.78E0 , 515.65E0 , 519.47E0 , 544.47E0 , 560.11E0 , 620.77E0 , 18.97E0 , 28.93E0 , 33.91E0 , 40.03E0 , 44.66E0 , 49.87E0 , 55.16E0 , 60.90E0 , 72.08E0 , 85.15E0 , 97.06E0 , 119.63E0 , 133.27E0 , 143.84E0 , 161.91E0 , 180.67E0 , 198.44E0 , 226.86E0 , 229.65E0 , 258.27E0 , 273.77E0 , 339.15E0 , 350.13E0 , 362.75E0 , 371.03E0 , 393.32E0 , 448.53E0 , 473.78E0 , 511.12E0 , 524.70E0 , 548.75E0 , 551.64E0 , 574.02E0 , 623.86E0 , 21.46E0 , 24.33E0 , 33.43E0 , 39.22E0 , 44.18E0 , 55.02E0 , 94.33E0 , 96.44E0 , 118.82E0 , 128.48E0 , +141.94E0 , 156.92E0 , 171.65E0 , 190.00E0 , 223.26E0 , 223.88E0 , 231.50E0 , 265.05E0 , 269.44E0 , 271.78E0 , 273.46E0 , 334.61E0 , 339.79E0 , 349.52E0 , 358.18E0 , 377.98E0 , 394.77E0 , 429.66E0 , 468.22E0 , 487.27E0 , 519.54E0 , 523.03E0 , 612.99E0 , 638.59E0 , 641.36E0 , 622.05E0 , 631.50E0 , 663.97E0 , 646.9E0 , 748.29E0 , 749.21E0 , 750.14E0 , 647.04E0 , 646.89E0 , 746.9E0 , 748.43E0 , 747.35E0 , 749.27E0 , 647.61E0 , 747.78E0 , 750.51E0 , 851.37E0 , 845.97E0 , 847.54E0 , 849.93E0 , 851.61E0 , 849.75E0 , 850.98E0 , 848.23E0}; // http://www.itl.nist.gov/div898/strd/nls/data/hahn1.shtml void testNistHahn1(void) @@ -1485,8 +1491,11 @@ return 0; } }; -const double Bennett5_functor::x[154] = { 7.447168E0, 8.102586E0, 8.452547E0, 8.711278E0, 8.916774E0, 9.087155E0, 9.232590E0, 9.359535E0, 9.472166E0, 9.573384E0, 9.665293E0, 9.749461E0, 9.827092E0, 9.899128E0, 9.966321E0, 10.029280E0, 10.088510E0, 10.144430E0, 10.197380E0, 10.247670E0, 10.295560E0, 10.341250E0, 10.384950E0, 10.426820E0, 10.467000E0, 10.505640E0, 10.542830E0, 10.578690E0, 10.613310E0, 10.646780E0, 10.679150E0, 10.710520E0, 10.740920E0, 10.770440E0, 10.799100E0, 10.826970E0, 10.854080E0, 10.880470E0, 10.906190E0, 10.931260E0, 10.955720E0, 10.979590E0, 11.002910E0, 11.025700E0, 11.047980E0, 11.069770E0, 11.091100E0, 11.111980E0, 11.132440E0, 11.152480E0, 11.172130E0, 11.191410E0, 11.210310E0, 11.228870E0, 11.247090E0, 11.264980E0, 11.282560E0, 11.299840E0, 11.316820E0, 11.333520E0, 11.349940E0, 11.366100E0, 11.382000E0, 11.397660E0, 11.413070E0, 11.428240E0, 11.443200E0, 11.457930E0, 11.472440E0, 11.486750E0, 11.500860E0, 11.514770E0, 11.528490E0, 11.542020E0, 11.555380E0, 11.568550E0, 11.581560E0, 11.594420E0, 11.607121E0, 11.619640E0, 11.632000E0, 11.644210E0, 11.656280E0, 11.668200E0, 11.679980E0, 11.691620E0, 11.703130E0, 11.714510E0, 11.725760E0, 11.736880E0, 11.747890E0, 11.758780E0, 11.769550E0, 11.780200E0, 11.790730E0, 11.801160E0, 11.811480E0, 11.821700E0, 11.831810E0, 11.841820E0, 11.851730E0, 11.861550E0, 11.871270E0, 11.880890E0, 11.890420E0, 11.899870E0, 11.909220E0, 11.918490E0, 11.927680E0, 11.936780E0, 11.945790E0, 11.954730E0, 11.963590E0, 11.972370E0, 11.981070E0, 11.989700E0, 11.998260E0, 12.006740E0, 12.015150E0, 12.023490E0, 12.031760E0, 12.039970E0, 12.048100E0, 12.056170E0, 12.064180E0, 12.072120E0, 12.080010E0, 12.087820E0, 12.095580E0, 12.103280E0, 12.110920E0, 12.118500E0, 12.126030E0, 12.133500E0, 12.140910E0, 12.148270E0, 12.155570E0, 12.162830E0, 12.170030E0, 12.177170E0, 12.184270E0, 12.191320E0, 12.198320E0, 12.205270E0, 12.212170E0, 12.219030E0, 12.225840E0, 12.232600E0, 12.239320E0, 12.245990E0, 12.252620E0, 12.259200E0, 12.265750E0, 12.272240E0 }; -const double Bennett5_functor::y[154] = { -34.834702E0 ,-34.393200E0 ,-34.152901E0 ,-33.979099E0 ,-33.845901E0 ,-33.732899E0 ,-33.640301E0 ,-33.559200E0 ,-33.486801E0 ,-33.423100E0 ,-33.365101E0 ,-33.313000E0 ,-33.260899E0 ,-33.217400E0 ,-33.176899E0 ,-33.139198E0 ,-33.101601E0 ,-33.066799E0 ,-33.035000E0 ,-33.003101E0 ,-32.971298E0 ,-32.942299E0 ,-32.916302E0 ,-32.890202E0 ,-32.864101E0 ,-32.841000E0 ,-32.817799E0 ,-32.797501E0 ,-32.774300E0 ,-32.757000E0 ,-32.733799E0 ,-32.716400E0 ,-32.699100E0 ,-32.678799E0 ,-32.661400E0 ,-32.644001E0 ,-32.626701E0 ,-32.612202E0 ,-32.597698E0 ,-32.583199E0 ,-32.568699E0 ,-32.554298E0 ,-32.539799E0 ,-32.525299E0 ,-32.510799E0 ,-32.499199E0 ,-32.487598E0 ,-32.473202E0 ,-32.461601E0 ,-32.435501E0 ,-32.435501E0 ,-32.426800E0 ,-32.412300E0 ,-32.400799E0 ,-32.392101E0 ,-32.380501E0 ,-32.366001E0 ,-32.357300E0 ,-32.348598E0 ,-32.339901E0 ,-32.328400E0 ,-32.319698E0 ,-32.311001E0 ,-32.299400E0 ,-32.290699E0 ,-32.282001E0 ,-32.273300E0 ,-32.264599E0 ,-32.256001E0 ,-32.247299E0 ,-32.238602E0 ,-32.229900E0 ,-32.224098E0 ,-32.215401E0 ,-32.203800E0 ,-32.198002E0 ,-32.189400E0 ,-32.183601E0 ,-32.174900E0 ,-32.169102E0 ,-32.163300E0 ,-32.154598E0 ,-32.145901E0 ,-32.140099E0 ,-32.131401E0 ,-32.125599E0 ,-32.119801E0 ,-32.111198E0 ,-32.105400E0 ,-32.096699E0 ,-32.090900E0 ,-32.088001E0 ,-32.079300E0 ,-32.073502E0 ,-32.067699E0 ,-32.061901E0 ,-32.056099E0 ,-32.050301E0 ,-32.044498E0 ,-32.038799E0 ,-32.033001E0 ,-32.027199E0 ,-32.024300E0 ,-32.018501E0 ,-32.012699E0 ,-32.004002E0 ,-32.001099E0 ,-31.995300E0 ,-31.989500E0 ,-31.983700E0 ,-31.977900E0 ,-31.972099E0 ,-31.969299E0 ,-31.963501E0 ,-31.957701E0 ,-31.951900E0 ,-31.946100E0 ,-31.940300E0 ,-31.937401E0 ,-31.931601E0 ,-31.925800E0 ,-31.922899E0 ,-31.917101E0 ,-31.911301E0 ,-31.908400E0 ,-31.902599E0 ,-31.896900E0 ,-31.893999E0 ,-31.888201E0 ,-31.885300E0 ,-31.882401E0 ,-31.876600E0 ,-31.873699E0 ,-31.867901E0 ,-31.862101E0 ,-31.859200E0 ,-31.856300E0 ,-31.850500E0 ,-31.844700E0 ,-31.841801E0 ,-31.838900E0 ,-31.833099E0 ,-31.830200E0 ,-31.827299E0 ,-31.821600E0 ,-31.818701E0 ,-31.812901E0 ,-31.809999E0 ,-31.807100E0 ,-31.801300E0 ,-31.798401E0 ,-31.795500E0 ,-31.789700E0 ,-31.786800E0 }; +const double Bennett5_functor::x[154] = { 7.447168E0, 8.102586E0, 8.452547E0, 8.711278E0, 8.916774E0, 9.087155E0, 9.232590E0, 9.359535E0, 9.472166E0, 9.573384E0, 9.665293E0, 9.749461E0, 9.827092E0, 9.899128E0, 9.966321E0, 10.029280E0, 10.088510E0, 10.144430E0, 10.197380E0, 10.247670E0, 10.295560E0, 10.341250E0, 10.384950E0, 10.426820E0, 10.467000E0, 10.505640E0, 10.542830E0, 10.578690E0, 10.613310E0, 10.646780E0, 10.679150E0, 10.710520E0, 10.740920E0, 10.770440E0, 10.799100E0, 10.826970E0, 10.854080E0, 10.880470E0, 10.906190E0, 10.931260E0, 10.955720E0, 10.979590E0, 11.002910E0, 11.025700E0, 11.047980E0, 11.069770E0, 11.091100E0, 11.111980E0, 11.132440E0, 11.152480E0, 11.172130E0, 11.191410E0, 11.210310E0, 11.228870E0, 11.247090E0, 11.264980E0, 11.282560E0, 11.299840E0, 11.316820E0, 11.333520E0, 11.349940E0, 11.366100E0, 11.382000E0, 11.397660E0, 11.413070E0, 11.428240E0, 11.443200E0, 11.457930E0, 11.472440E0, 11.486750E0, 11.500860E0, 11.514770E0, 11.528490E0, 11.542020E0, 11.555380E0, 11.568550E0, +11.581560E0, 11.594420E0, 11.607121E0, 11.619640E0, 11.632000E0, 11.644210E0, 11.656280E0, 11.668200E0, 11.679980E0, 11.691620E0, 11.703130E0, 11.714510E0, 11.725760E0, 11.736880E0, 11.747890E0, 11.758780E0, 11.769550E0, 11.780200E0, 11.790730E0, 11.801160E0, 11.811480E0, 11.821700E0, 11.831810E0, 11.841820E0, 11.851730E0, 11.861550E0, 11.871270E0, 11.880890E0, 11.890420E0, 11.899870E0, 11.909220E0, 11.918490E0, 11.927680E0, 11.936780E0, 11.945790E0, 11.954730E0, 11.963590E0, 11.972370E0, 11.981070E0, 11.989700E0, 11.998260E0, 12.006740E0, 12.015150E0, 12.023490E0, 12.031760E0, 12.039970E0, 12.048100E0, 12.056170E0, 12.064180E0, 12.072120E0, 12.080010E0, 12.087820E0, 12.095580E0, 12.103280E0, 12.110920E0, 12.118500E0, 12.126030E0, 12.133500E0, 12.140910E0, 12.148270E0, 12.155570E0, 12.162830E0, 12.170030E0, 12.177170E0, 12.184270E0, 12.191320E0, 12.198320E0, 12.205270E0, 12.212170E0, 12.219030E0, 12.225840E0, 12.232600E0, 12.239320E0, 12.245990E0, 12.252620E0, 12.259200E0, 12.265750E0, 12.272240E0 }; +const double Bennett5_functor::y[154] = { -34.834702E0 ,-34.393200E0 ,-34.152901E0 ,-33.979099E0 ,-33.845901E0 ,-33.732899E0 ,-33.640301E0 ,-33.559200E0 ,-33.486801E0 ,-33.423100E0 ,-33.365101E0 ,-33.313000E0 ,-33.260899E0 ,-33.217400E0 ,-33.176899E0 ,-33.139198E0 ,-33.101601E0 ,-33.066799E0 ,-33.035000E0 ,-33.003101E0 ,-32.971298E0 ,-32.942299E0 ,-32.916302E0 ,-32.890202E0 ,-32.864101E0 ,-32.841000E0 ,-32.817799E0 ,-32.797501E0 ,-32.774300E0 ,-32.757000E0 ,-32.733799E0 ,-32.716400E0 ,-32.699100E0 ,-32.678799E0 ,-32.661400E0 ,-32.644001E0 ,-32.626701E0 ,-32.612202E0 ,-32.597698E0 ,-32.583199E0 ,-32.568699E0 ,-32.554298E0 ,-32.539799E0 ,-32.525299E0 ,-32.510799E0 ,-32.499199E0 ,-32.487598E0 ,-32.473202E0 ,-32.461601E0 ,-32.435501E0 ,-32.435501E0 ,-32.426800E0 ,-32.412300E0 ,-32.400799E0 ,-32.392101E0 ,-32.380501E0 ,-32.366001E0 ,-32.357300E0 ,-32.348598E0 ,-32.339901E0 ,-32.328400E0 ,-32.319698E0 ,-32.311001E0 ,-32.299400E0 ,-32.290699E0 ,-32.282001E0 ,-32.273300E0 ,-32.264599E0 ,-32.256001E0 ,-32.247299E0 +,-32.238602E0 ,-32.229900E0 ,-32.224098E0 ,-32.215401E0 ,-32.203800E0 ,-32.198002E0 ,-32.189400E0 ,-32.183601E0 ,-32.174900E0 ,-32.169102E0 ,-32.163300E0 ,-32.154598E0 ,-32.145901E0 ,-32.140099E0 ,-32.131401E0 ,-32.125599E0 ,-32.119801E0 ,-32.111198E0 ,-32.105400E0 ,-32.096699E0 ,-32.090900E0 ,-32.088001E0 ,-32.079300E0 ,-32.073502E0 ,-32.067699E0 ,-32.061901E0 ,-32.056099E0 ,-32.050301E0 ,-32.044498E0 ,-32.038799E0 ,-32.033001E0 ,-32.027199E0 ,-32.024300E0 ,-32.018501E0 ,-32.012699E0 ,-32.004002E0 ,-32.001099E0 ,-31.995300E0 ,-31.989500E0 ,-31.983700E0 ,-31.977900E0 ,-31.972099E0 ,-31.969299E0 ,-31.963501E0 ,-31.957701E0 ,-31.951900E0 ,-31.946100E0 ,-31.940300E0 ,-31.937401E0 ,-31.931601E0 ,-31.925800E0 ,-31.922899E0 ,-31.917101E0 ,-31.911301E0 ,-31.908400E0 ,-31.902599E0 ,-31.896900E0 ,-31.893999E0 ,-31.888201E0 ,-31.885300E0 ,-31.882401E0 ,-31.876600E0 ,-31.873699E0 ,-31.867901E0 ,-31.862101E0 ,-31.859200E0 ,-31.856300E0 ,-31.850500E0 ,-31.844700E0 ,-31.841801E0 ,-31.838900E0 ,-31.833099E0 ,-31.830200E0 , +-31.827299E0 ,-31.821600E0 ,-31.818701E0 ,-31.812901E0 ,-31.809999E0 ,-31.807100E0 ,-31.801300E0 ,-31.798401E0 ,-31.795500E0 ,-31.789700E0 ,-31.786800E0 }; // http://www.itl.nist.gov/div898/strd/nls/data/bennett5.shtml void testNistBennett5(void)
diff --git a/unsupported/test/minres.cpp b/unsupported/test/minres.cpp index 46eb2f0..fd12da5 100644 --- a/unsupported/test/minres.cpp +++ b/unsupported/test/minres.cpp
@@ -7,6 +7,7 @@ // This Source Code Form is subject to the terms of the Mozilla // Public License v. 2.0. If a copy of the MPL was not distributed // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. +#include <cmath> #include "../../test/sparse_solver.h" #include <Eigen/IterativeSolvers>
diff --git a/unsupported/test/mpreal/mpreal.h b/unsupported/test/mpreal/mpreal.h index 5afe479..ca243ac 100644 --- a/unsupported/test/mpreal/mpreal.h +++ b/unsupported/test/mpreal/mpreal.h
@@ -3194,7 +3194,7 @@ } } - inline static mpfr::mpreal min(mp_prec_t precision = mpfr::mpreal::get_default_prec()) + inline static mpfr::mpreal (min)(mp_prec_t precision = mpfr::mpreal::get_default_prec()) { // min = 1/2*2^emin = 2^(emin-1) return mpfr::mpreal(1, precision) << mpfr::mpreal::get_emin()-1; @@ -3205,7 +3205,7 @@ return (-(max)(precision)); } - inline static mpfr::mpreal max(mp_prec_t precision = mpfr::mpreal::get_default_prec()) + inline static mpfr::mpreal (max)(mp_prec_t precision = mpfr::mpreal::get_default_prec()) { // max = (1-eps)*2^emax, eps is machine epsilon return (mpfr::mpreal(1, precision) - epsilon(precision)) << mpfr::mpreal::get_emax();
diff --git a/unsupported/test/mpreal_support.cpp b/unsupported/test/mpreal_support.cpp index af5587a..0de546a 100644 --- a/unsupported/test/mpreal_support.cpp +++ b/unsupported/test/mpreal_support.cpp
@@ -5,7 +5,6 @@ #include <sstream> using namespace mpfr; -using namespace std; using namespace Eigen; void test_mpreal_support()
diff --git a/unsupported/test/polynomialsolver.cpp b/unsupported/test/polynomialsolver.cpp index fefeaff..c31104f 100644 --- a/unsupported/test/polynomialsolver.cpp +++ b/unsupported/test/polynomialsolver.cpp
@@ -92,6 +92,7 @@ template< int Deg, typename POLYNOMIAL, typename ROOTS, typename REAL_ROOTS > void evalSolverSugarFunction( const POLYNOMIAL& pols, const ROOTS& roots, const REAL_ROOTS& real_roots ) { + using std::sqrt; typedef typename POLYNOMIAL::Scalar Scalar; typedef PolynomialSolver<Scalar, Deg > PolynomialSolverType; @@ -115,7 +116,7 @@ psolve.realRoots( calc_realRoots ); VERIFY( calc_realRoots.size() == (size_t)real_roots.size() ); - const Scalar psPrec = internal::sqrt( test_precision<Scalar>() ); + const Scalar psPrec = sqrt( test_precision<Scalar>() ); for( size_t i=0; i<calc_realRoots.size(); ++i ) { @@ -130,24 +131,24 @@ //Test greatestRoot VERIFY( internal::isApprox( roots.array().abs().maxCoeff(), - internal::abs( psolve.greatestRoot() ), psPrec ) ); + abs( psolve.greatestRoot() ), psPrec ) ); //Test smallestRoot VERIFY( internal::isApprox( roots.array().abs().minCoeff(), - internal::abs( psolve.smallestRoot() ), psPrec ) ); + abs( psolve.smallestRoot() ), psPrec ) ); bool hasRealRoot; //Test absGreatestRealRoot Real r = psolve.absGreatestRealRoot( hasRealRoot ); VERIFY( hasRealRoot == (real_roots.size() > 0 ) ); if( hasRealRoot ){ - VERIFY( internal::isApprox( real_roots.array().abs().maxCoeff(), internal::abs(r), psPrec ) ); } + VERIFY( internal::isApprox( real_roots.array().abs().maxCoeff(), abs(r), psPrec ) ); } //Test absSmallestRealRoot r = psolve.absSmallestRealRoot( hasRealRoot ); VERIFY( hasRealRoot == (real_roots.size() > 0 ) ); if( hasRealRoot ){ - VERIFY( internal::isApprox( real_roots.array().abs().minCoeff(), internal::abs( r ), psPrec ) ); } + VERIFY( internal::isApprox( real_roots.array().abs().minCoeff(), abs( r ), psPrec ) ); } //Test greatestRealRoot r = psolve.greatestRealRoot( hasRealRoot );