* Introduce EIGEN_DEFAULT_TO_ROW_MAJOR tests option

---> Now only product_large fails with EIGEN_DEFAULT_TO_ROW_MAJOR.
* Fix EIGEN_NO_ASSERTION_CHECKING tests option
* Fix a crash in Tridiagonalization on row-major matrices + SSE
* Fix inverse test (numeric stability noise)
* Extend map test (see previous fixes in MapBase)
* Fix vectorization_logic test for row-major
* Disable sparse tests with EIGEN_DEFAULT_TO_ROW_MAJOR

Eigen/src/QR/Tridiagonalization.h

@@ -293,7 +293,7 @@ void Tridiagonalization<MatrixType>::_compute(MatrixType& matA, CoeffVectorType&
       {
         int starti = i+1;
         int alignedEnd = starti;
-        if (PacketSize>1)
+        if (PacketSize>1 && (int(MatrixType::Flags)&RowMajor) == 0)
         {
           int alignedStart = (starti) + ei_alignmentOffset(&matA.coeffRef(starti,j1), n-starti);
           alignedEnd = alignedStart + ((n-alignedStart)/PacketSize)*PacketSize;

test/CMakeLists.txt

@@ -1,3 +1,7 @@
+option(EIGEN_DEFAULT_TO_ROW_MAJOR "Use row-major as default matrix storage order" OFF)
+if(EIGEN_DEFAULT_TO_ROW_MAJOR)
+  add_definitions("-DEIGEN_DEFAULT_TO_ROW_MAJOR")
+endif()
 
 find_package(GSL)
 if(GSL_FOUND AND GSL_VERSION_MINOR LESS 9)
@@ -93,12 +97,20 @@ else(CMAKE_COMPILER_IS_GNUCXX)
 endif(CMAKE_COMPILER_IS_GNUCXX)
 
 option(EIGEN_NO_ASSERTION_CHECKING "Disable checking of assertions" OFF)
+if(EIGEN_NO_ASSERTION_CHECKING)
+  add_definitions("-DEIGEN_NO_ASSERTION_CHECKING=1")
+endif()
+
 
 # similar to set_target_properties but append the property instead of overwriting it
 macro(ei_add_target_property target prop value)
 
   get_target_property(previous ${target} ${prop})
+  if(previous MATCHES "NOTFOUND")
+    set_target_properties(${target} PROPERTIES ${prop} "${value}")
+  else()
     set_target_properties(${target} PROPERTIES ${prop} "${previous} ${value}")
+  endif()
 
 endmacro(ei_add_target_property)
 
@@ -134,13 +146,9 @@ macro(ei_add_test testname)
 
     option(EIGEN_DEBUG_ASSERTS "Enable debuging of assertions" OFF)
     if(EIGEN_DEBUG_ASSERTS)
-      set_target_properties(${targetname} PROPERTIES COMPILE_DEFINITIONS "-DEIGEN_DEBUG_ASSERTS=1")
+      set_target_properties(${targetname} PROPERTIES COMPILE_DEFINITIONS "EIGEN_DEBUG_ASSERTS=1")
     endif(EIGEN_DEBUG_ASSERTS)
 
-  else(NOT EIGEN_NO_ASSERTION_CHECKING)
-
-    set_target_properties(${targetname} PROPERTIES COMPILE_DEFINITIONS "-DEIGEN_NO_ASSERTION_CHECKING=1")
-
   endif(NOT EIGEN_NO_ASSERTION_CHECKING)
 
   if(${ARGC} GREATER 1)
@@ -201,7 +209,7 @@ ei_add_test(array)
 ei_add_test(triangular)
 ei_add_test(cholesky " " "${GSL_LIBRARIES}")
 ei_add_test(lu ${EI_OFLAG})
-ei_add_test(determinant)
+ei_add_test(determinant ${EI_OFLAG})
 ei_add_test(inverse)
 ei_add_test(qr)
 ei_add_test(eigensolver " " "${GSL_LIBRARIES}")
@@ -216,10 +224,12 @@ ei_add_test(newstdvector)
 if(QT4_FOUND)
   ei_add_test(qtvector " " "${QT_QTCORE_LIBRARY}")
 endif(QT4_FOUND)
-ei_add_test(sparse_vector)
-ei_add_test(sparse_basic)
-ei_add_test(sparse_solvers " " "${SPARSE_LIBS}")
-ei_add_test(sparse_product)
+if(NOT EIGEN_DEFAULT_TO_ROW_MAJOR)
+  ei_add_test(sparse_vector)
+  ei_add_test(sparse_basic)
+  ei_add_test(sparse_solvers " " "${SPARSE_LIBS}")
+  ei_add_test(sparse_product)
+endif()
 ei_add_test(swap)
 ei_add_test(visitor)
 
@@ -268,6 +278,12 @@ else(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION)
   message("Explicit vec:      AUTO")
 endif(EIGEN_TEST_NO_EXPLICIT_VECTORIZATION)
 
+if(EIGEN_DEFAULT_TO_ROW_MAJOR)
+  message("Default order:     Row-major")
+else()
+  message("Default order:     Column-major")
+endif()
+
   message("CXX:               ${CMAKE_CXX_COMPILER}")
 if(CMAKE_COMPILER_IS_GNUCXX)
   execute_process(COMMAND ${CMAKE_CXX_COMPILER} --version COMMAND head -n 1 OUTPUT_VARIABLE EIGEN_CXX_VERSION_STRING OUTPUT_STRIP_TRAILING_WHITESPACE)

test/inverse.cpp

@@ -43,11 +43,9 @@ template<typename MatrixType> void inverse(const MatrixType& m)
              mzero = MatrixType::Zero(rows, cols),
              identity = MatrixType::Identity(rows, rows);
 
-  if (ei_is_same_type<RealScalar,float>::ret)
+  while(ei_abs(m1.determinant()) < RealScalar(0.1) && rows <= 8)
   {
-    // let's build a more stable to inverse matrix
-    MatrixType a = MatrixType::Random(rows,cols);
-    m1 += m1 * m1.adjoint() + a * a.adjoint();
+    m1 = MatrixType::Random(rows, cols);
   }
 
   m2 = m1.inverse();

test/map.cpp

@@ -1,7 +1,7 @@
 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra. Eigen itself is part of the KDE project.
 //
-// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
+// Copyright (C) 2007-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // Eigen is free software; you can redistribute it and/or
 // modify it under the terms of the GNU Lesser General Public
@@ -24,7 +24,7 @@
 
 #include "main.h"
 
-template<typename VectorType> void map_class(const VectorType& m)
+template<typename VectorType> void map_class_vector(const VectorType& m)
 {
   typedef typename VectorType::Scalar Scalar;
 
@@ -50,6 +50,34 @@ template<typename VectorType> void map_class(const VectorType& m)
   delete[] array3;
 }
 
+template<typename MatrixType> void map_class_matrix(const MatrixType& m)
+{
+  typedef typename MatrixType::Scalar Scalar;
+
+  int rows = m.rows(), cols = m.cols(), size = rows*cols;
+
+  // test Map.h
+  Scalar* array1 = ei_aligned_new<Scalar>(size);
+  for(int i = 0; i < size; i++) array1[i] = Scalar(1);
+  Scalar* array2 = ei_aligned_new<Scalar>(size);
+  for(int i = 0; i < size; i++) array2[i] = Scalar(1);
+  Scalar* array3 = new Scalar[size+1];
+  for(int i = 0; i < size+1; i++) array3[i] = Scalar(1);
+  Scalar* array3unaligned = size_t(array3)%16 == 0 ? array3+1 : array3;
+  Map<MatrixType, Aligned>(array1, rows, cols) = MatrixType::Ones(rows,cols);
+  Map<MatrixType>(array2, rows, cols) = Map<MatrixType>(array1, rows, cols);
+  Map<MatrixType>(array3unaligned, rows, cols) = Map<MatrixType>(array1, rows, cols);
+  MatrixType ma1 = Map<MatrixType>(array1, rows, cols);
+  MatrixType ma2 = Map<MatrixType, Aligned>(array2, rows, cols);
+  VERIFY_IS_APPROX(ma1, ma2);
+  MatrixType ma3 = Map<MatrixType>(array3unaligned, rows, cols);
+  VERIFY_IS_APPROX(ma1, ma3);
+  
+  ei_aligned_delete(array1, size);
+  ei_aligned_delete(array2, size);
+  delete[] array3;
+}
+
 template<typename VectorType> void map_static_methods(const VectorType& m)
 {
   typedef typename VectorType::Scalar Scalar;
@@ -80,11 +108,17 @@ template<typename VectorType> void map_static_methods(const VectorType& m)
 void test_map()
 {
   for(int i = 0; i < g_repeat; i++) {
-    CALL_SUBTEST( map_class(Matrix<float, 1, 1>()) );
-    CALL_SUBTEST( map_class(Vector4d()) );
-    CALL_SUBTEST( map_class(RowVector4f()) );
-    CALL_SUBTEST( map_class(VectorXcf(8)) );
-    CALL_SUBTEST( map_class(VectorXi(12)) );
+    CALL_SUBTEST( map_class_vector(Matrix<float, 1, 1>()) );
+    CALL_SUBTEST( map_class_vector(Vector4d()) );
+    CALL_SUBTEST( map_class_vector(RowVector4f()) );
+    CALL_SUBTEST( map_class_vector(VectorXcf(8)) );
+    CALL_SUBTEST( map_class_vector(VectorXi(12)) );
+
+    CALL_SUBTEST( map_class_matrix(Matrix<float, 1, 1>()) );
+    CALL_SUBTEST( map_class_matrix(Matrix4d()) );
+    CALL_SUBTEST( map_class_matrix(Matrix<float,3,5>()) );
+    CALL_SUBTEST( map_class_matrix(MatrixXcf(ei_random<int>(1,10),ei_random<int>(1,10))) );
+    CALL_SUBTEST( map_class_matrix(MatrixXi(ei_random<int>(1,10),ei_random<int>(1,10))) );
 
     CALL_SUBTEST( map_static_methods(Matrix<double, 1, 1>()) );
     CALL_SUBTEST( map_static_methods(Vector3f()) );

test/product.h

@@ -46,7 +46,7 @@ template<typename MatrixType> void product(const MatrixType& m)
   typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::RowsAtCompileTime> RowSquareMatrixType;
   typedef Matrix<Scalar, MatrixType::ColsAtCompileTime, MatrixType::ColsAtCompileTime> ColSquareMatrixType;
   typedef Matrix<Scalar, MatrixType::RowsAtCompileTime, MatrixType::ColsAtCompileTime,
-                         MatrixType::Flags&RowMajorBit> OtherMajorMatrixType;
+                         MatrixType::Options^RowMajor> OtherMajorMatrixType;
 
   int rows = m.rows();
   int cols = m.cols();
@@ -137,6 +137,7 @@ template<typename MatrixType> void product(const MatrixType& m)
   res2 = square2;
   res2 += (m1.transpose() * m2).lazy();
   VERIFY_IS_APPROX(res2, square2 + m1.transpose() * m2);
+
   if (NumTraits<Scalar>::HasFloatingPoint && std::min(rows,cols)>1)
   {
     VERIFY(areNotApprox(res2,square2 + m2.transpose() * m1));

test/vectorization_logic.cpp

@@ -44,12 +44,21 @@ void test_vectorization_logic()
 
 #ifdef EIGEN_VECTORIZE
 
+#ifdef  EIGEN_DEFAULT_TO_ROW_MAJOR
+  VERIFY(test_assign(Vector4f(),Vector4f(),
+    LinearVectorization,CompleteUnrolling));
+  VERIFY(test_assign(Vector4f(),Vector4f()+Vector4f(),
+    LinearVectorization,CompleteUnrolling));
+  VERIFY(test_assign(Vector4f(),Vector4f().cwise() * Vector4f(),
+    LinearVectorization,CompleteUnrolling));
+#else
   VERIFY(test_assign(Vector4f(),Vector4f(),
     InnerVectorization,CompleteUnrolling));
   VERIFY(test_assign(Vector4f(),Vector4f()+Vector4f(),
     InnerVectorization,CompleteUnrolling));
   VERIFY(test_assign(Vector4f(),Vector4f().cwise() * Vector4f(),
     InnerVectorization,CompleteUnrolling));
+#endif
 
   VERIFY(test_assign(Matrix4f(),Matrix4f(),
     InnerVectorization,CompleteUnrolling));
@@ -92,8 +101,10 @@ void test_vectorization_logic()
   VERIFY(test_sum(Matrix<float,16,16>().block<4,4>(1,2),
     NoVectorization,CompleteUnrolling));
 
+#ifndef EIGEN_DEFAULT_TO_ROW_MAJOR
   VERIFY(test_sum(Matrix<float,16,16>().block<8,1>(1,2),
     LinearVectorization,CompleteUnrolling));
+#endif
 
   VERIFY(test_sum(Matrix<double,7,3>(),
     NoVectorization,CompleteUnrolling));