test/mapped_matrix.cpp - eigen - Git at Google

 // This file is part of Eigen, a lightweight C++ template library
 // for linear algebra.
 //
 // Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
 //
 // 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 "main.h"

 #define EIGEN_TESTMAP_MAX_SIZE 256

 template <typename VectorType>
 void map_class_vector(const VectorType& m) {
   typedef typename VectorType::Scalar Scalar;

   Index size = m.size();

   Scalar* array1 = internal::aligned_new<Scalar>(size);
   Scalar* array2 = internal::aligned_new<Scalar>(size);
   Scalar* array3 = new Scalar[size + 1];
   // In case of no alignment, avoid division by zero.
   constexpr int alignment = (std::max<int>)(EIGEN_MAX_ALIGN_BYTES, 1);
   Scalar* array3unaligned = (std::uintptr_t(array3) % alignment) == 0 ? array3 + 1 : array3;
   Scalar array4[EIGEN_TESTMAP_MAX_SIZE];

   Map<VectorType, AlignedMax>(array1, size) = VectorType::Random(size);
   Map<VectorType, AlignedMax>(array2, size) = Map<VectorType, AlignedMax>(array1, size);
   Map<VectorType>(array3unaligned, size) = Map<VectorType>(array1, size);
   Map<VectorType>(array4, size) = Map<VectorType, AlignedMax>(array1, size);
   VectorType ma1 = Map<VectorType, AlignedMax>(array1, size);
   VectorType ma2 = Map<VectorType, AlignedMax>(array2, size);
   VectorType ma3 = Map<VectorType>(array3unaligned, size);
   VectorType ma4 = Map<VectorType>(array4, size);
   VERIFY_IS_EQUAL(ma1, ma2);
   VERIFY_IS_EQUAL(ma1, ma3);
   VERIFY_IS_EQUAL(ma1, ma4);
 #ifdef EIGEN_VECTORIZE
   if (internal::packet_traits<Scalar>::Vectorizable && size >= AlignedMax)
     VERIFY_RAISES_ASSERT((Map<VectorType, AlignedMax>(array3unaligned, size)))
 #endif

   internal::aligned_delete(array1, size);
   internal::aligned_delete(array2, size);
   delete[] array3;
 }

 template <typename MatrixType>
 void map_class_matrix(const MatrixType& m) {
   typedef typename MatrixType::Scalar Scalar;

   Index rows = m.rows(), cols = m.cols(), size = rows * cols;
   Scalar s1 = internal::random<Scalar>();

   // array1 and array2 -> aligned heap allocation
   Scalar* array1 = internal::aligned_new<Scalar>(size);
   for (int i = 0; i < size; i++) array1[i] = Scalar(1);
   Scalar* array2 = internal::aligned_new<Scalar>(size);
   for (int i = 0; i < size; i++) array2[i] = Scalar(1);
   // array3unaligned -> unaligned pointer to heap
   Scalar* array3 = new Scalar[size + 1];
   Index sizep1 = size + 1;  // <- without this temporary MSVC 2103 generates bad code
   for (Index i = 0; i < sizep1; i++) array3[i] = Scalar(1);
   // In case of no alignment, avoid division by zero.
   constexpr int alignment = (std::max<int>)(EIGEN_MAX_ALIGN_BYTES, 1);
   Scalar* array3unaligned = (std::uintptr_t(array3) % alignment) == 0 ? array3 + 1 : array3;
   Scalar array4[256];
   if (size <= 256)
     for (int i = 0; i < size; i++) array4[i] = Scalar(1);

   Map<MatrixType> map1(array1, rows, cols);
   Map<MatrixType, AlignedMax> map2(array2, rows, cols);
   Map<MatrixType> map3(array3unaligned, rows, cols);
   Map<MatrixType> map4(array4, rows, cols);

   VERIFY_IS_EQUAL(map1, MatrixType::Ones(rows, cols));
   map1.setConstant(s1);
   VERIFY_IS_EQUAL(map1, MatrixType::Constant(rows, cols, s1));
   map1.setZero();
   VERIFY_IS_EQUAL(map1, MatrixType::Zero(rows, cols));

   VERIFY_IS_EQUAL(map2, MatrixType::Ones(rows, cols));
   map2.setConstant(s1);
   VERIFY_IS_EQUAL(map2, MatrixType::Constant(rows, cols, s1));
   map2.setZero();
   VERIFY_IS_EQUAL(map2, MatrixType::Zero(rows, cols));

   VERIFY_IS_EQUAL(map3, MatrixType::Ones(rows, cols));
   map3.setConstant(s1);
   VERIFY_IS_EQUAL(map3, MatrixType::Constant(rows, cols, s1));
   map3.setZero();
   VERIFY_IS_EQUAL(map3, MatrixType::Zero(rows, cols));

   map1 = MatrixType::Random(rows, cols);
   map2 = map1;
   map3 = map1;
   MatrixType ma1 = map1;
   MatrixType ma2 = map2;
   MatrixType ma3 = map3;
   VERIFY_IS_EQUAL(map1, map2);
   VERIFY_IS_EQUAL(map1, map3);
   VERIFY_IS_EQUAL(ma1, ma2);
   VERIFY_IS_EQUAL(ma1, ma3);
   VERIFY_IS_EQUAL(ma1, map3);

   VERIFY_IS_APPROX(s1 * map1, s1 * map2);
   VERIFY_IS_APPROX(s1 * ma1, s1 * ma2);
   VERIFY_IS_EQUAL(s1 * ma1, s1 * ma3);
   VERIFY_IS_APPROX(s1 * map1, s1 * map3);

   map2 *= s1;
   map3 *= s1;
   VERIFY_IS_APPROX(s1 * map1, map2);
   VERIFY_IS_APPROX(s1 * map1, map3);

   if (size <= 256) {
     VERIFY_IS_EQUAL(map4, MatrixType::Ones(rows, cols));
     map4 = map1;
     MatrixType ma4 = map4;
     VERIFY_IS_EQUAL(map1, map4);
     VERIFY_IS_EQUAL(ma1, map4);
     VERIFY_IS_EQUAL(ma1, ma4);
     VERIFY_IS_APPROX(s1 * map1, s1 * map4);

     map4 *= s1;
     VERIFY_IS_APPROX(s1 * map1, map4);
   }

   internal::aligned_delete(array1, size);
   internal::aligned_delete(array2, size);
   delete[] array3;
 }

 template <typename VectorType>
 void map_static_methods(const VectorType& m) {
   typedef typename VectorType::Scalar Scalar;

   Index size = m.size();

   Scalar* array1 = internal::aligned_new<Scalar>(size);
   Scalar* array2 = internal::aligned_new<Scalar>(size);
   Scalar* array3 = new Scalar[size + 1];
   // In case of no alignment, avoid division by zero.
   constexpr int alignment = (std::max<int>)(EIGEN_MAX_ALIGN_BYTES, 1);
   Scalar* array3unaligned = (std::uintptr_t(array3) % alignment) == 0 ? array3 + 1 : array3;

   VectorType::MapAligned(array1, size) = VectorType::Random(size);
   VectorType::Map(array2, size) = VectorType::Map(array1, size);
   VectorType::Map(array3unaligned, size) = VectorType::Map(array1, size);
   VectorType ma1 = VectorType::Map(array1, size);
   VectorType ma2 = VectorType::MapAligned(array2, size);
   VectorType ma3 = VectorType::Map(array3unaligned, size);
   VERIFY_IS_EQUAL(ma1, ma2);
   VERIFY_IS_EQUAL(ma1, ma3);

   internal::aligned_delete(array1, size);
   internal::aligned_delete(array2, size);
   delete[] array3;
 }

 template <typename PlainObjectType>
 void check_const_correctness(const PlainObjectType&) {
   // there's a lot that we can't test here while still having this test compile!
   // the only possible approach would be to run a script trying to compile stuff and checking that it fails.
   // CMake can help with that.

   // verify that map-to-const don't have LvalueBit
   typedef std::add_const_t<PlainObjectType> ConstPlainObjectType;
   VERIFY(!(internal::traits<Map<ConstPlainObjectType>>::Flags & LvalueBit));
   VERIFY(!(internal::traits<Map<ConstPlainObjectType, AlignedMax>>::Flags & LvalueBit));
   VERIFY(!(Map<ConstPlainObjectType>::Flags & LvalueBit));
   VERIFY(!(Map<ConstPlainObjectType, AlignedMax>::Flags & LvalueBit));
 }

 // Test Map with InnerStride at vectorization boundary sizes.
 // Strided Maps exercise different traversal paths (SliceVectorized or Default)
 // in assignment and reductions.
 template <typename Scalar>
 void map_inner_stride_boundary() {
   const Index PS = internal::packet_traits<Scalar>::size;
   const Index sizes[] = {1, 2, 3, PS - 1, PS, PS + 1, 2 * PS, 2 * PS + 1, 4 * PS, 4 * PS + 1};
   for (int si = 0; si < 10; ++si) {
     const Index n = sizes[si];
     if (n <= 0) continue;
     typedef Matrix<Scalar, Dynamic, 1> Vec;
     // InnerStride<2>: every other element
     Vec data = Vec::Random(2 * n);
     Map<Vec, 0, InnerStride<2>> strided(data.data(), n);

     // Test assignment to/from strided map
     Vec dense = strided;
     for (Index k = 0; k < n; ++k) VERIFY_IS_APPROX(dense(k), data(2 * k));

     // Test scalar operations on strided map
     Vec result = Scalar(2) * strided;
     for (Index k = 0; k < n; ++k) VERIFY_IS_APPROX(result(k), Scalar(2) * data(2 * k));

     // Test strided map + dense vector
     Vec other = Vec::Random(n);
     Vec sum_result = strided + other;
     for (Index k = 0; k < n; ++k) VERIFY_IS_APPROX(sum_result(k), data(2 * k) + other(k));

     // Test writing to strided map
     Map<Vec, 0, InnerStride<2>> strided_dst(data.data(), n);
     strided_dst = other;
     for (Index k = 0; k < n; ++k) VERIFY_IS_APPROX(data(2 * k), other(k));
   }
 }

 // Test Map with OuterStride on matrices at boundary sizes.
 template <typename Scalar>
 void map_outer_stride_boundary() {
   const Index PS = internal::packet_traits<Scalar>::size;
   typedef Matrix<Scalar, Dynamic, Dynamic> Mat;
   // Test various inner dimensions around packet size
   const Index inner_sizes[] = {1, PS - 1, PS, PS + 1, 2 * PS, 2 * PS + 1};
   const Index outer_stride = 64;  // large enough for any inner size
   const Index cols = 4;

   for (int si = 0; si < 6; ++si) {
     Index rows = inner_sizes[si];
     if (rows <= 0) continue;
     typedef Matrix<Scalar, Dynamic, 1> Vec;
     Vec data = Vec::Random(outer_stride * cols);
     Map<Mat, 0, OuterStride<>> mapped(data.data(), rows, cols, OuterStride<>(outer_stride));

     // Test that mapped values match expected layout
     Mat dense = mapped;
     for (Index j = 0; j < cols; ++j)
       for (Index i = 0; i < rows; ++i) VERIFY_IS_APPROX(dense(i, j), data(j * outer_stride + i));

     // Test reduction on mapped matrix
     Scalar ref_sum(0);
     for (Index j = 0; j < cols; ++j)
       for (Index i = 0; i < rows; ++i) ref_sum += data(j * outer_stride + i);
     VERIFY_IS_APPROX(mapped.sum(), ref_sum);

     // Test matrix product with mapped matrix
     Vec x = Vec::Random(cols);
     Vec y = mapped * x;
     Vec y_ref = dense * x;
     VERIFY_IS_APPROX(y, y_ref);
   }
 }

 EIGEN_DECLARE_TEST(mapped_matrix) {
   for (int i = 0; i < g_repeat; i++) {
     CALL_SUBTEST_1(map_class_vector(Matrix<float, 1, 1>()));
     CALL_SUBTEST_1(check_const_correctness(Matrix<float, 1, 1>()));
     CALL_SUBTEST_2(map_class_vector(Vector4d()));
     CALL_SUBTEST_2(map_class_vector(VectorXd(13)));
     CALL_SUBTEST_2(check_const_correctness(Matrix4d()));
     CALL_SUBTEST_3(map_class_vector(RowVector4f()));
     CALL_SUBTEST_4(map_class_vector(VectorXcf(8)));
     CALL_SUBTEST_5(map_class_vector(VectorXi(12)));
     CALL_SUBTEST_5(check_const_correctness(VectorXi(12)));

     CALL_SUBTEST_1(map_class_matrix(Matrix<float, 1, 1>()));
     CALL_SUBTEST_2(map_class_matrix(Matrix4d()));
     CALL_SUBTEST_11(map_class_matrix(Matrix<float, 3, 5>()));
     CALL_SUBTEST_4(map_class_matrix(MatrixXcf(internal::random<int>(1, 10), internal::random<int>(1, 10))));
     CALL_SUBTEST_5(map_class_matrix(MatrixXi(internal::random<int>(1, 10), internal::random<int>(1, 10))));

     CALL_SUBTEST_6(map_static_methods(Matrix<double, 1, 1>()));
     CALL_SUBTEST_7(map_static_methods(Vector3f()));
     CALL_SUBTEST_8(map_static_methods(RowVector3d()));
     CALL_SUBTEST_9(map_static_methods(VectorXcd(8)));
     CALL_SUBTEST_10(map_static_methods(VectorXf(12)));
   }

   // Strided map tests at vectorization boundaries (deterministic, outside g_repeat).
   CALL_SUBTEST_12(map_inner_stride_boundary<float>());
   CALL_SUBTEST_12(map_inner_stride_boundary<double>());
   CALL_SUBTEST_13(map_outer_stride_boundary<float>());
   CALL_SUBTEST_13(map_outer_stride_boundary<double>());
 }
	// This file is part of Eigen, a lightweight C++ template library
	// for linear algebra.
	//
	// Copyright (C) 2006-2010 Benoit Jacob <jacob.benoit.1@gmail.com>
	//
	// 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 "main.h"

	#define EIGEN_TESTMAP_MAX_SIZE 256

	template <typename VectorType>
	void map_class_vector(const VectorType& m) {
	typedef typename VectorType::Scalar Scalar;

	Index size = m.size();

	Scalar* array1 = internal::aligned_new<Scalar>(size);
	Scalar* array2 = internal::aligned_new<Scalar>(size);
	Scalar* array3 = new Scalar[size + 1];
	// In case of no alignment, avoid division by zero.
	constexpr int alignment = (std::max<int>)(EIGEN_MAX_ALIGN_BYTES, 1);
	Scalar* array3unaligned = (std::uintptr_t(array3) % alignment) == 0 ? array3 + 1 : array3;
	Scalar array4[EIGEN_TESTMAP_MAX_SIZE];

	Map<VectorType, AlignedMax>(array1, size) = VectorType::Random(size);
	Map<VectorType, AlignedMax>(array2, size) = Map<VectorType, AlignedMax>(array1, size);
	Map<VectorType>(array3unaligned, size) = Map<VectorType>(array1, size);
	Map<VectorType>(array4, size) = Map<VectorType, AlignedMax>(array1, size);
	VectorType ma1 = Map<VectorType, AlignedMax>(array1, size);
	VectorType ma2 = Map<VectorType, AlignedMax>(array2, size);
	VectorType ma3 = Map<VectorType>(array3unaligned, size);
	VectorType ma4 = Map<VectorType>(array4, size);
	VERIFY_IS_EQUAL(ma1, ma2);
	VERIFY_IS_EQUAL(ma1, ma3);
	VERIFY_IS_EQUAL(ma1, ma4);
	#ifdef EIGEN_VECTORIZE
	if (internal::packet_traits<Scalar>::Vectorizable && size >= AlignedMax)
	VERIFY_RAISES_ASSERT((Map<VectorType, AlignedMax>(array3unaligned, size)))
	#endif

	internal::aligned_delete(array1, size);
	internal::aligned_delete(array2, size);
	delete[] array3;
	}

	template <typename MatrixType>
	void map_class_matrix(const MatrixType& m) {
	typedef typename MatrixType::Scalar Scalar;

	Index rows = m.rows(), cols = m.cols(), size = rows * cols;
	Scalar s1 = internal::random<Scalar>();

	// array1 and array2 -> aligned heap allocation
	Scalar* array1 = internal::aligned_new<Scalar>(size);
	for (int i = 0; i < size; i++) array1[i] = Scalar(1);
	Scalar* array2 = internal::aligned_new<Scalar>(size);
	for (int i = 0; i < size; i++) array2[i] = Scalar(1);
	// array3unaligned -> unaligned pointer to heap
	Scalar* array3 = new Scalar[size + 1];
	Index sizep1 = size + 1; // <- without this temporary MSVC 2103 generates bad code
	for (Index i = 0; i < sizep1; i++) array3[i] = Scalar(1);
	// In case of no alignment, avoid division by zero.
	constexpr int alignment = (std::max<int>)(EIGEN_MAX_ALIGN_BYTES, 1);
	Scalar* array3unaligned = (std::uintptr_t(array3) % alignment) == 0 ? array3 + 1 : array3;
	Scalar array4[256];
	if (size <= 256)
	for (int i = 0; i < size; i++) array4[i] = Scalar(1);

	Map<MatrixType> map1(array1, rows, cols);
	Map<MatrixType, AlignedMax> map2(array2, rows, cols);
	Map<MatrixType> map3(array3unaligned, rows, cols);
	Map<MatrixType> map4(array4, rows, cols);

	VERIFY_IS_EQUAL(map1, MatrixType::Ones(rows, cols));
	map1.setConstant(s1);
	VERIFY_IS_EQUAL(map1, MatrixType::Constant(rows, cols, s1));
	map1.setZero();
	VERIFY_IS_EQUAL(map1, MatrixType::Zero(rows, cols));

	VERIFY_IS_EQUAL(map2, MatrixType::Ones(rows, cols));
	map2.setConstant(s1);
	VERIFY_IS_EQUAL(map2, MatrixType::Constant(rows, cols, s1));
	map2.setZero();
	VERIFY_IS_EQUAL(map2, MatrixType::Zero(rows, cols));

	VERIFY_IS_EQUAL(map3, MatrixType::Ones(rows, cols));
	map3.setConstant(s1);
	VERIFY_IS_EQUAL(map3, MatrixType::Constant(rows, cols, s1));
	map3.setZero();
	VERIFY_IS_EQUAL(map3, MatrixType::Zero(rows, cols));

	map1 = MatrixType::Random(rows, cols);
	map2 = map1;
	map3 = map1;
	MatrixType ma1 = map1;
	MatrixType ma2 = map2;
	MatrixType ma3 = map3;
	VERIFY_IS_EQUAL(map1, map2);
	VERIFY_IS_EQUAL(map1, map3);
	VERIFY_IS_EQUAL(ma1, ma2);
	VERIFY_IS_EQUAL(ma1, ma3);
	VERIFY_IS_EQUAL(ma1, map3);

	VERIFY_IS_APPROX(s1 * map1, s1 * map2);
	VERIFY_IS_APPROX(s1 * ma1, s1 * ma2);
	VERIFY_IS_EQUAL(s1 * ma1, s1 * ma3);
	VERIFY_IS_APPROX(s1 * map1, s1 * map3);

	map2 *= s1;
	map3 *= s1;
	VERIFY_IS_APPROX(s1 * map1, map2);
	VERIFY_IS_APPROX(s1 * map1, map3);

	if (size <= 256) {
	VERIFY_IS_EQUAL(map4, MatrixType::Ones(rows, cols));
	map4 = map1;
	MatrixType ma4 = map4;
	VERIFY_IS_EQUAL(map1, map4);
	VERIFY_IS_EQUAL(ma1, map4);
	VERIFY_IS_EQUAL(ma1, ma4);
	VERIFY_IS_APPROX(s1 * map1, s1 * map4);

	map4 *= s1;
	VERIFY_IS_APPROX(s1 * map1, map4);
	}

	internal::aligned_delete(array1, size);
	internal::aligned_delete(array2, size);
	delete[] array3;
	}

	template <typename VectorType>
	void map_static_methods(const VectorType& m) {
	typedef typename VectorType::Scalar Scalar;

	Index size = m.size();

	Scalar* array1 = internal::aligned_new<Scalar>(size);
	Scalar* array2 = internal::aligned_new<Scalar>(size);
	Scalar* array3 = new Scalar[size + 1];
	// In case of no alignment, avoid division by zero.
	constexpr int alignment = (std::max<int>)(EIGEN_MAX_ALIGN_BYTES, 1);
	Scalar* array3unaligned = (std::uintptr_t(array3) % alignment) == 0 ? array3 + 1 : array3;

	VectorType::MapAligned(array1, size) = VectorType::Random(size);
	VectorType::Map(array2, size) = VectorType::Map(array1, size);
	VectorType::Map(array3unaligned, size) = VectorType::Map(array1, size);
	VectorType ma1 = VectorType::Map(array1, size);
	VectorType ma2 = VectorType::MapAligned(array2, size);
	VectorType ma3 = VectorType::Map(array3unaligned, size);
	VERIFY_IS_EQUAL(ma1, ma2);
	VERIFY_IS_EQUAL(ma1, ma3);

	internal::aligned_delete(array1, size);
	internal::aligned_delete(array2, size);
	delete[] array3;
	}

	template <typename PlainObjectType>
	void check_const_correctness(const PlainObjectType&) {
	// there's a lot that we can't test here while still having this test compile!
	// the only possible approach would be to run a script trying to compile stuff and checking that it fails.
	// CMake can help with that.

	// verify that map-to-const don't have LvalueBit
	typedef std::add_const_t<PlainObjectType> ConstPlainObjectType;
	VERIFY(!(internal::traits<Map<ConstPlainObjectType>>::Flags & LvalueBit));
	VERIFY(!(internal::traits<Map<ConstPlainObjectType, AlignedMax>>::Flags & LvalueBit));
	VERIFY(!(Map<ConstPlainObjectType>::Flags & LvalueBit));
	VERIFY(!(Map<ConstPlainObjectType, AlignedMax>::Flags & LvalueBit));
	}

	// Test Map with InnerStride at vectorization boundary sizes.
	// Strided Maps exercise different traversal paths (SliceVectorized or Default)
	// in assignment and reductions.
	template <typename Scalar>
	void map_inner_stride_boundary() {
	const Index PS = internal::packet_traits<Scalar>::size;
	const Index sizes[] = {1, 2, 3, PS - 1, PS, PS + 1, 2 * PS, 2 * PS + 1, 4 * PS, 4 * PS + 1};
	for (int si = 0; si < 10; ++si) {
	const Index n = sizes[si];
	if (n <= 0) continue;
	typedef Matrix<Scalar, Dynamic, 1> Vec;
	// InnerStride<2>: every other element
	Vec data = Vec::Random(2 * n);
	Map<Vec, 0, InnerStride<2>> strided(data.data(), n);

	// Test assignment to/from strided map
	Vec dense = strided;
	for (Index k = 0; k < n; ++k) VERIFY_IS_APPROX(dense(k), data(2 * k));

	// Test scalar operations on strided map
	Vec result = Scalar(2) * strided;
	for (Index k = 0; k < n; ++k) VERIFY_IS_APPROX(result(k), Scalar(2) * data(2 * k));

	// Test strided map + dense vector
	Vec other = Vec::Random(n);
	Vec sum_result = strided + other;
	for (Index k = 0; k < n; ++k) VERIFY_IS_APPROX(sum_result(k), data(2 * k) + other(k));

	// Test writing to strided map
	Map<Vec, 0, InnerStride<2>> strided_dst(data.data(), n);
	strided_dst = other;
	for (Index k = 0; k < n; ++k) VERIFY_IS_APPROX(data(2 * k), other(k));
	}
	}

	// Test Map with OuterStride on matrices at boundary sizes.
	template <typename Scalar>
	void map_outer_stride_boundary() {
	const Index PS = internal::packet_traits<Scalar>::size;
	typedef Matrix<Scalar, Dynamic, Dynamic> Mat;
	// Test various inner dimensions around packet size
	const Index inner_sizes[] = {1, PS - 1, PS, PS + 1, 2 * PS, 2 * PS + 1};
	const Index outer_stride = 64; // large enough for any inner size
	const Index cols = 4;

	for (int si = 0; si < 6; ++si) {
	Index rows = inner_sizes[si];
	if (rows <= 0) continue;
	typedef Matrix<Scalar, Dynamic, 1> Vec;
	Vec data = Vec::Random(outer_stride * cols);
	Map<Mat, 0, OuterStride<>> mapped(data.data(), rows, cols, OuterStride<>(outer_stride));

	// Test that mapped values match expected layout
	Mat dense = mapped;
	for (Index j = 0; j < cols; ++j)
	for (Index i = 0; i < rows; ++i) VERIFY_IS_APPROX(dense(i, j), data(j * outer_stride + i));

	// Test reduction on mapped matrix
	Scalar ref_sum(0);
	for (Index j = 0; j < cols; ++j)
	for (Index i = 0; i < rows; ++i) ref_sum += data(j * outer_stride + i);
	VERIFY_IS_APPROX(mapped.sum(), ref_sum);

	// Test matrix product with mapped matrix
	Vec x = Vec::Random(cols);
	Vec y = mapped * x;
	Vec y_ref = dense * x;
	VERIFY_IS_APPROX(y, y_ref);
	}
	}

	EIGEN_DECLARE_TEST(mapped_matrix) {
	for (int i = 0; i < g_repeat; i++) {
	CALL_SUBTEST_1(map_class_vector(Matrix<float, 1, 1>()));
	CALL_SUBTEST_1(check_const_correctness(Matrix<float, 1, 1>()));
	CALL_SUBTEST_2(map_class_vector(Vector4d()));
	CALL_SUBTEST_2(map_class_vector(VectorXd(13)));
	CALL_SUBTEST_2(check_const_correctness(Matrix4d()));
	CALL_SUBTEST_3(map_class_vector(RowVector4f()));
	CALL_SUBTEST_4(map_class_vector(VectorXcf(8)));
	CALL_SUBTEST_5(map_class_vector(VectorXi(12)));
	CALL_SUBTEST_5(check_const_correctness(VectorXi(12)));

	CALL_SUBTEST_1(map_class_matrix(Matrix<float, 1, 1>()));
	CALL_SUBTEST_2(map_class_matrix(Matrix4d()));
	CALL_SUBTEST_11(map_class_matrix(Matrix<float, 3, 5>()));
	CALL_SUBTEST_4(map_class_matrix(MatrixXcf(internal::random<int>(1, 10), internal::random<int>(1, 10))));
	CALL_SUBTEST_5(map_class_matrix(MatrixXi(internal::random<int>(1, 10), internal::random<int>(1, 10))));

	CALL_SUBTEST_6(map_static_methods(Matrix<double, 1, 1>()));
	CALL_SUBTEST_7(map_static_methods(Vector3f()));
	CALL_SUBTEST_8(map_static_methods(RowVector3d()));
	CALL_SUBTEST_9(map_static_methods(VectorXcd(8)));
	CALL_SUBTEST_10(map_static_methods(VectorXf(12)));
	}

	// Strided map tests at vectorization boundaries (deterministic, outside g_repeat).
	CALL_SUBTEST_12(map_inner_stride_boundary<float>());
	CALL_SUBTEST_12(map_inner_stride_boundary<double>());
	CALL_SUBTEST_13(map_outer_stride_boundary<float>());
	CALL_SUBTEST_13(map_outer_stride_boundary<double>());
	}