From 3411146984316c97f56543333a46f47aeb7f9d35 Mon Sep 17 00:00:00 2001
From: Sergey Sharybin <sergey.vfx@gmail.com>
Date: Fri, 21 Mar 2014 16:04:53 +0600
Subject: Update Eigen to version 3.2.1

Main purpose of this is to have SparseLU solver which
we can use now as a replacement to opennl library.
---
 extern/Eigen3/Eigen/src/Core/CwiseBinaryOp.h | 22 +++++++++++-----------
 1 file changed, 11 insertions(+), 11 deletions(-)

(limited to 'extern/Eigen3/Eigen/src/Core/CwiseBinaryOp.h')

diff --git a/extern/Eigen3/Eigen/src/Core/CwiseBinaryOp.h b/extern/Eigen3/Eigen/src/Core/CwiseBinaryOp.h
index 1b93af31b60..586f77aaf32 100644
--- a/extern/Eigen3/Eigen/src/Core/CwiseBinaryOp.h
+++ b/extern/Eigen3/Eigen/src/Core/CwiseBinaryOp.h
@@ -94,8 +94,8 @@ struct traits<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >
 // So allowing mixing different types gives very unexpected errors when enabling vectorization, when the user tries to
 // add together a float matrix and a double matrix.
 #define EIGEN_CHECK_BINARY_COMPATIBILIY(BINOP,LHS,RHS) \
-  EIGEN_STATIC_ASSERT((internal::functor_allows_mixing_real_and_complex<BINOP>::ret \
-                        ? int(internal::is_same<typename NumTraits<LHS>::Real, typename NumTraits<RHS>::Real>::value) \
+  EIGEN_STATIC_ASSERT((internal::functor_is_product_like<BINOP>::ret \
+                        ? int(internal::scalar_product_traits<LHS, RHS>::Defined) \
                         : int(internal::is_same<LHS, RHS>::value)), \
     YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY)
 
@@ -122,13 +122,13 @@ class CwiseBinaryOp : internal::no_assignment_operator,
     typedef typename internal::remove_reference<LhsNested>::type _LhsNested;
     typedef typename internal::remove_reference<RhsNested>::type _RhsNested;
 
-    EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& lhs, const Rhs& rhs, const BinaryOp& func = BinaryOp())
-      : m_lhs(lhs), m_rhs(rhs), m_functor(func)
+    EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& aLhs, const Rhs& aRhs, const BinaryOp& func = BinaryOp())
+      : m_lhs(aLhs), m_rhs(aRhs), m_functor(func)
     {
       EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp,typename Lhs::Scalar,typename Rhs::Scalar);
       // require the sizes to match
       EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs)
-      eigen_assert(lhs.rows() == rhs.rows() && lhs.cols() == rhs.cols());
+      eigen_assert(aLhs.rows() == aRhs.rows() && aLhs.cols() == aRhs.cols());
     }
 
     EIGEN_STRONG_INLINE Index rows() const {
@@ -169,17 +169,17 @@ class CwiseBinaryOpImpl<BinaryOp, Lhs, Rhs, Dense>
     typedef typename internal::dense_xpr_base<CwiseBinaryOp<BinaryOp, Lhs, Rhs> >::type Base;
     EIGEN_DENSE_PUBLIC_INTERFACE( Derived )
 
-    EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const
+    EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const
     {
-      return derived().functor()(derived().lhs().coeff(row, col),
-                                 derived().rhs().coeff(row, col));
+      return derived().functor()(derived().lhs().coeff(rowId, colId),
+                                 derived().rhs().coeff(rowId, colId));
     }
 
     template<int LoadMode>
-    EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const
+    EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const
     {
-      return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(row, col),
-                                          derived().rhs().template packet<LoadMode>(row, col));
+      return derived().functor().packetOp(derived().lhs().template packet<LoadMode>(rowId, colId),
+                                          derived().rhs().template packet<LoadMode>(rowId, colId));
     }
 
     EIGEN_STRONG_INLINE const Scalar coeff(Index index) const
-- 
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