From 1b2049fbdad3d9ac292e6a71836a16329fcaf02a Mon Sep 17 00:00:00 2001
From: Gael Guennebaud <g.gael@free.fr>
Date: Mon, 25 Jul 2016 12:35:10 +0200
Subject: [PATCH] Enforce scalar types in calls to max/min (helps with
 expression template scalar types)

---
 Eigen/src/Eigenvalues/RealSchur.h | 4 ++--
 Eigen/src/SVD/BDCSVD.h            | 2 +-
 Eigen/src/SVD/JacobiSVD.h         | 2 +-
 Eigen/src/SVD/SVDBase.h           | 3 +--
 test/eigensolver_selfadjoint.cpp  | 2 +-
 test/qr.cpp                       | 2 +-
 6 files changed, 7 insertions(+), 8 deletions(-)

diff --git a/Eigen/src/Eigenvalues/RealSchur.h b/Eigen/src/Eigenvalues/RealSchur.h
index 1f333f64b..9d9063004 100644
--- a/Eigen/src/Eigenvalues/RealSchur.h
+++ b/Eigen/src/Eigenvalues/RealSchur.h
@@ -304,7 +304,7 @@ RealSchur<MatrixType>& RealSchur<MatrixType>::computeFromHessenberg(const HessMa
       {
         m_matT.coeffRef(iu,iu) = m_matT.coeff(iu,iu) + exshift;
         // keep track of the largest diagonal coefficient
-        maxDiagEntry = numext::maxi(maxDiagEntry,abs(m_matT.coeffRef(iu,iu)));
+        maxDiagEntry = numext::maxi<Scalar>(maxDiagEntry,abs(m_matT.coeffRef(iu,iu)));
         if (iu > 0)
           m_matT.coeffRef(iu, iu-1) = Scalar(0);
         iu--;
@@ -314,7 +314,7 @@ RealSchur<MatrixType>& RealSchur<MatrixType>::computeFromHessenberg(const HessMa
       {
         splitOffTwoRows(iu, computeU, exshift);
         // keep track of the largest diagonal coefficient
-        maxDiagEntry = numext::maxi(maxDiagEntry,numext::maxi(abs(m_matT.coeff(iu,iu)), abs(m_matT.coeff(iu-1,iu-1))));
+        maxDiagEntry = numext::maxi<Scalar>(maxDiagEntry,numext::maxi(abs(m_matT.coeff(iu,iu)), abs(m_matT.coeff(iu-1,iu-1))));
         iu -= 2;
         iter = 0;
       }
diff --git a/Eigen/src/SVD/BDCSVD.h b/Eigen/src/SVD/BDCSVD.h
index 799e81bd7..25fca6f4d 100644
--- a/Eigen/src/SVD/BDCSVD.h
+++ b/Eigen/src/SVD/BDCSVD.h
@@ -1052,7 +1052,7 @@ void BDCSVD<MatrixType>::deflation(Index firstCol, Index lastCol, Index k, Index
   
   const RealScalar considerZero = (std::numeric_limits<RealScalar>::min)();
   RealScalar maxDiag = diag.tail((std::max)(Index(1),length-1)).cwiseAbs().maxCoeff();
-  RealScalar epsilon_strict = numext::maxi(considerZero,NumTraits<RealScalar>::epsilon() * maxDiag);
+  RealScalar epsilon_strict = numext::maxi<RealScalar>(considerZero,NumTraits<RealScalar>::epsilon() * maxDiag);
   RealScalar epsilon_coarse = 8 * NumTraits<RealScalar>::epsilon() * numext::maxi<RealScalar>(col0.cwiseAbs().maxCoeff(), maxDiag);
   
 #ifdef EIGEN_BDCSVD_SANITY_CHECKS
diff --git a/Eigen/src/SVD/JacobiSVD.h b/Eigen/src/SVD/JacobiSVD.h
index a0e8cf27a..605c1a2a6 100644
--- a/Eigen/src/SVD/JacobiSVD.h
+++ b/Eigen/src/SVD/JacobiSVD.h
@@ -727,7 +727,7 @@ JacobiSVD<MatrixType, QRPreconditioner>::compute(const MatrixType& matrix, unsig
             if(computeV()) m_matrixV.applyOnTheRight(p,q,j_right);
 
             // keep track of the largest diagonal coefficient
-            maxDiagEntry = numext::maxi(maxDiagEntry,numext::maxi(abs(m_workMatrix.coeff(p,p)), abs(m_workMatrix.coeff(q,q))));
+            maxDiagEntry = numext::maxi<RealScalar>(maxDiagEntry,numext::maxi(abs(m_workMatrix.coeff(p,p)), abs(m_workMatrix.coeff(q,q))));
           }
         }
       }
diff --git a/Eigen/src/SVD/SVDBase.h b/Eigen/src/SVD/SVDBase.h
index e2d77a761..cc90a3b75 100644
--- a/Eigen/src/SVD/SVDBase.h
+++ b/Eigen/src/SVD/SVDBase.h
@@ -130,10 +130,9 @@ public:
   inline Index rank() const
   {
     using std::abs;
-    using std::max;
     eigen_assert(m_isInitialized && "JacobiSVD is not initialized.");
     if(m_singularValues.size()==0) return 0;
-    RealScalar premultiplied_threshold = (max)(m_singularValues.coeff(0) * threshold(), (std::numeric_limits<RealScalar>::min)());
+    RealScalar premultiplied_threshold = numext::maxi<RealScalar>(m_singularValues.coeff(0) * threshold(), (std::numeric_limits<RealScalar>::min)());
     Index i = m_nonzeroSingularValues-1;
     while(i>=0 && m_singularValues.coeff(i) < premultiplied_threshold) --i;
     return i+1;
diff --git a/test/eigensolver_selfadjoint.cpp b/test/eigensolver_selfadjoint.cpp
index cd0ae5c2f..af2b33331 100644
--- a/test/eigensolver_selfadjoint.cpp
+++ b/test/eigensolver_selfadjoint.cpp
@@ -19,7 +19,7 @@ template<typename MatrixType> void selfadjointeigensolver_essential_check(const
 {
   typedef typename MatrixType::Scalar Scalar;
   typedef typename NumTraits<Scalar>::Real RealScalar;
-  RealScalar eival_eps = (std::min)(test_precision<RealScalar>(),  NumTraits<Scalar>::dummy_precision()*20000);
+  RealScalar eival_eps = numext::mini<RealScalar>(test_precision<RealScalar>(),  NumTraits<Scalar>::dummy_precision()*20000);
   
   SelfAdjointEigenSolver<MatrixType> eiSymm(m);
   VERIFY_IS_EQUAL(eiSymm.info(), Success);
diff --git a/test/qr.cpp b/test/qr.cpp
index 98738777f..dfcc1e8f9 100644
--- a/test/qr.cpp
+++ b/test/qr.cpp
@@ -86,7 +86,7 @@ template<typename MatrixType> void qr_invertible()
   VERIFY_IS_APPROX(log(absdet), qr.logAbsDeterminant());
   // This test is tricky if the determinant becomes too small.
   // Since we generate random numbers with magnitude rrange [0,1], the average determinant is 0.5^size
-  VERIFY_IS_MUCH_SMALLER_THAN( abs(absdet-qr.absDeterminant()), (max)(RealScalar(pow(0.5,size)),(max)(abs(absdet),abs(qr.absDeterminant()))) );
+  VERIFY_IS_MUCH_SMALLER_THAN( abs(absdet-qr.absDeterminant()), numext::maxi(RealScalar(pow(0.5,size)),numext::maxi<RealScalar>(abs(absdet),abs(qr.absDeterminant()))) );
   
 }