Squashed 'third_party/eigen/' content from commit 61d72f6
Change-Id: Iccc90fa0b55ab44037f018046d2fcffd90d9d025
git-subtree-dir: third_party/eigen
git-subtree-split: 61d72f6383cfa842868c53e30e087b0258177257
diff --git a/test/eigen2/eigen2_map.cpp b/test/eigen2/eigen2_map.cpp
new file mode 100644
index 0000000..4a1c4e1
--- /dev/null
+++ b/test/eigen2/eigen2_map.cpp
@@ -0,0 +1,114 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra. Eigen itself is part of the KDE project.
+//
+// Copyright (C) 2007-2010 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"
+
+template<typename VectorType> void map_class_vector(const VectorType& m)
+{
+ typedef typename VectorType::Scalar Scalar;
+
+ int size = m.size();
+
+ // test Map.h
+ Scalar* array1 = ei_aligned_new<Scalar>(size);
+ Scalar* array2 = ei_aligned_new<Scalar>(size);
+ Scalar* array3 = new Scalar[size+1];
+ Scalar* array3unaligned = std::size_t(array3)%16 == 0 ? array3+1 : array3;
+
+ Map<VectorType, Aligned>(array1, size) = VectorType::Random(size);
+ Map<VectorType>(array2, size) = Map<VectorType>(array1, size);
+ Map<VectorType>(array3unaligned, size) = Map<VectorType>((const Scalar*)array1, size); // test non-const-correctness support in eigen2
+ VectorType ma1 = Map<VectorType>(array1, size);
+ VectorType ma2 = Map<VectorType, Aligned>(array2, size);
+ VectorType ma3 = Map<VectorType>(array3unaligned, size);
+ VERIFY_IS_APPROX(ma1, ma2);
+ VERIFY_IS_APPROX(ma1, ma3);
+
+ ei_aligned_delete(array1, size);
+ ei_aligned_delete(array2, size);
+ 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 = std::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>((const Scalar*)array1, rows, cols); // test non-const-correctness support in eigen2
+ 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;
+
+ int size = m.size();
+
+ // test Map.h
+ Scalar* array1 = ei_aligned_new<Scalar>(size);
+ Scalar* array2 = ei_aligned_new<Scalar>(size);
+ Scalar* array3 = new Scalar[size+1];
+ Scalar* array3unaligned = std::size_t(array3)%16 == 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_APPROX(ma1, ma2);
+ VERIFY_IS_APPROX(ma1, ma3);
+
+ ei_aligned_delete(array1, size);
+ ei_aligned_delete(array2, size);
+ delete[] array3;
+}
+
+
+void test_eigen2_map()
+{
+ for(int i = 0; i < g_repeat; i++) {
+ CALL_SUBTEST_1( map_class_vector(Matrix<float, 1, 1>()) );
+ CALL_SUBTEST_2( map_class_vector(Vector4d()) );
+ 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_1( map_class_matrix(Matrix<float, 1, 1>()) );
+ CALL_SUBTEST_2( map_class_matrix(Matrix4d()) );
+ CALL_SUBTEST_6( map_class_matrix(Matrix<float,3,5>()) );
+ CALL_SUBTEST_4( map_class_matrix(MatrixXcf(ei_random<int>(1,10),ei_random<int>(1,10))) );
+ CALL_SUBTEST_5( map_class_matrix(MatrixXi(ei_random<int>(1,10),ei_random<int>(1,10))) );
+
+ CALL_SUBTEST_1( map_static_methods(Matrix<double, 1, 1>()) );
+ CALL_SUBTEST_2( map_static_methods(Vector3f()) );
+ CALL_SUBTEST_7( map_static_methods(RowVector3d()) );
+ CALL_SUBTEST_4( map_static_methods(VectorXcd(8)) );
+ CALL_SUBTEST_5( map_static_methods(VectorXf(12)) );
+ }
+}