/**************************************************************************** * * Copyright (C) 2022 PX4 Development Team. All rights reserved. * * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * * 1. Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * 2. Redistributions in binary form must reproduce the above copyright * notice, this list of conditions and the following disclaimer in * the documentation and/or other materials provided with the * distribution. * 3. Neither the name PX4 nor the names of its contributors may be * used to endorse or promote products derived from this software * without specific prior written permission. * * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE * COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS * OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED * AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE * POSSIBILITY OF SUCH DAMAGE. * ****************************************************************************/ #include #include using namespace matrix; TEST(MatrixSparseVectorTest, defaultConstruction) { SparseVectorf<24, 4, 6> a; EXPECT_EQ(a.non_zeros(), 2); EXPECT_EQ(a.index(0), 4); EXPECT_EQ(a.index(1), 6); a.at<4>() = 1.f; a.at<6>() = 2.f; } TEST(MatrixSparseVectorTest, initializationWithData) { const float data[3] = {1.f, 2.f, 3.f}; SparseVectorf<24, 4, 6, 22> a(data); EXPECT_EQ(a.non_zeros(), 3); EXPECT_EQ(a.index(0), 4); EXPECT_EQ(a.index(1), 6); EXPECT_EQ(a.index(2), 22); EXPECT_FLOAT_EQ(a.at<4>(), data[0]); EXPECT_FLOAT_EQ(a.at<6>(), data[1]); EXPECT_FLOAT_EQ(a.at<22>(), data[2]); } TEST(MatrixSparseVectorTest, initialisationFromVector) { const Vector3f vec(1.f, 2.f, 3.f); const SparseVectorf<3, 0, 2> a(vec); EXPECT_FLOAT_EQ(a.at<0>(), vec(0)); EXPECT_FLOAT_EQ(a.at<2>(), vec(2)); } TEST(MatrixSparseVectorTest, accessDataWithCompressedIndices) { const Vector3f vec(1.f, 2.f, 3.f); SparseVectorf<3, 0, 2> a(vec); for (size_t i = 0; i < a.non_zeros(); i++) { a.atCompressedIndex(i) = static_cast(i); } EXPECT_FLOAT_EQ(a.at<0>(), a.atCompressedIndex(0)); EXPECT_FLOAT_EQ(a.at<2>(), a.atCompressedIndex(1)); } TEST(MatrixSparseVectorTest, setZero) { const float data[3] = {1.f, 2.f, 3.f}; SparseVectorf<24, 4, 6, 22> a(data); a.setZero(); EXPECT_FLOAT_EQ(a.at<4>(), 0.f); EXPECT_FLOAT_EQ(a.at<6>(), 0.f); EXPECT_FLOAT_EQ(a.at<22>(), 0.f); } TEST(MatrixSparseVectorTest, additionWithDenseVector) { Vector dense_vec; dense_vec.setAll(1.f); const float data[3] = {1.f, 2.f, 3.f}; const SparseVectorf<4, 1, 2, 3> sparse_vec(data); const Vector res = sparse_vec + dense_vec; EXPECT_FLOAT_EQ(res(0), 1.f); EXPECT_FLOAT_EQ(res(1), 2.f); EXPECT_FLOAT_EQ(res(2), 3.f); EXPECT_FLOAT_EQ(res(3), 4.f); } TEST(MatrixSparseVectorTest, addScalar) { const float data[3] = {1.f, 2.f, 3.f}; SparseVectorf<4, 1, 2, 3> sparse_vec(data); sparse_vec += 2.f; EXPECT_FLOAT_EQ(sparse_vec.at<1>(), 3.f); EXPECT_FLOAT_EQ(sparse_vec.at<2>(), 4.f); EXPECT_FLOAT_EQ(sparse_vec.at<3>(), 5.f); } TEST(MatrixSparseVectorTest, dotProductWithDenseVector) { Vector dense_vec; dense_vec.setAll(3.f); const float data[3] = {1.f, 2.f, 3.f}; const SparseVectorf<4, 1, 2, 3> sparse_vec(data); float res = sparse_vec.dot(dense_vec); EXPECT_FLOAT_EQ(res, 18.f); } TEST(MatrixSparseVectorTest, multiplicationWithDenseMatrix) { Matrix dense_matrix; dense_matrix.setAll(2.f); dense_matrix(1, 1) = 3.f; const Vector3f dense_vec(0.f, 1.f, 5.f); const SparseVectorf<3, 1, 2> sparse_vec(dense_vec); const Vector res_sparse = dense_matrix * sparse_vec; const Vector res_dense = dense_matrix * dense_vec; EXPECT_TRUE(isEqual(res_dense, res_sparse)); } TEST(MatrixSparseVectorTest, quadraticForm) { float matrix_data[9] = {1, 2, 3, 2, 4, 5, 3, 5, 6 }; const SquareMatrix dense_matrix(matrix_data); const Vector3f dense_vec(0.f, 1.f, 5.f); const SparseVectorf<3, 1, 2> sparse_vec(dense_vec); EXPECT_FLOAT_EQ(quadraticForm(dense_matrix, sparse_vec), 204.f); } TEST(MatrixSparseVectorTest, norms) { const float data[2] = {3.f, 4.f}; const SparseVectorf<4, 1, 3> sparse_vec(data); EXPECT_FLOAT_EQ(sparse_vec.norm_squared(), 25.f); EXPECT_FLOAT_EQ(sparse_vec.norm(), 5.f); EXPECT_TRUE(sparse_vec.longerThan(4.5f)); EXPECT_FALSE(sparse_vec.longerThan(5.5f)); }