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163 lines
5.3 KiB
C++
163 lines
5.3 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra.
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//
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// Copyright (C) 2009 Hauke Heibel <hauke.heibel@gmail.com>
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//
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// This Source Code Form is subject to the terms of the Mozilla
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// Public License v. 2.0. If a copy of the MPL was not distributed
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// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.
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#include "main.h"
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#include <Eigen/Core>
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#include "AnnoyingScalar.h"
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using namespace Eigen;
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template <typename Scalar, int Storage>
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void run_matrix_tests() {
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typedef Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic, Storage> MatrixType;
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MatrixType m, n;
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// boundary cases ...
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m = n = MatrixType::Random(50, 50);
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m.conservativeResize(1, 50);
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VERIFY_IS_APPROX(m, n.block(0, 0, 1, 50));
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m = n = MatrixType::Random(50, 50);
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m.conservativeResize(50, 1);
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VERIFY_IS_APPROX(m, n.block(0, 0, 50, 1));
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m = n = MatrixType::Random(50, 50);
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m.conservativeResize(50, 50);
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VERIFY_IS_APPROX(m, n.block(0, 0, 50, 50));
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// random shrinking ...
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for (int i = 0; i < 25; ++i) {
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const Index rows = internal::random<Index>(1, 50);
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const Index cols = internal::random<Index>(1, 50);
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m = n = MatrixType::Random(50, 50);
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m.conservativeResize(rows, cols);
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VERIFY_IS_APPROX(m, n.block(0, 0, rows, cols));
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}
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// random growing with zeroing ...
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for (int i = 0; i < 25; ++i) {
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const Index rows = internal::random<Index>(50, 75);
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const Index cols = internal::random<Index>(50, 75);
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m = n = MatrixType::Random(50, 50);
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m.conservativeResizeLike(MatrixType::Zero(rows, cols));
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VERIFY_IS_APPROX(m.block(0, 0, n.rows(), n.cols()), n);
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VERIFY(rows <= 50 || m.block(50, 0, rows - 50, cols).sum() == Scalar(0));
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VERIFY(cols <= 50 || m.block(0, 50, rows, cols - 50).sum() == Scalar(0));
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}
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}
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template <typename Scalar>
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void run_vector_tests() {
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typedef Matrix<Scalar, 1, Eigen::Dynamic> VectorType;
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VectorType m, n;
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// boundary cases ...
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m = n = VectorType::Random(50);
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m.conservativeResize(1);
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VERIFY_IS_APPROX(m, n.segment(0, 1));
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m = n = VectorType::Random(50);
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m.conservativeResize(50);
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VERIFY_IS_APPROX(m, n.segment(0, 50));
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m = n = VectorType::Random(50);
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m.conservativeResize(m.rows(), 1);
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VERIFY_IS_APPROX(m, n.segment(0, 1));
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m = n = VectorType::Random(50);
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m.conservativeResize(m.rows(), 50);
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VERIFY_IS_APPROX(m, n.segment(0, 50));
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// random shrinking ...
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for (int i = 0; i < 50; ++i) {
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const int size = internal::random<int>(1, 50);
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m = n = VectorType::Random(50);
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m.conservativeResize(size);
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VERIFY_IS_APPROX(m, n.segment(0, size));
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m = n = VectorType::Random(50);
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m.conservativeResize(m.rows(), size);
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VERIFY_IS_APPROX(m, n.segment(0, size));
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}
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// random growing with zeroing ...
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for (int i = 0; i < 50; ++i) {
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const int size = internal::random<int>(50, 100);
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m = n = VectorType::Random(50);
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m.conservativeResizeLike(VectorType::Zero(size));
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VERIFY_IS_APPROX(m.segment(0, 50), n);
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VERIFY(size <= 50 || m.segment(50, size - 50).sum() == Scalar(0));
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m = n = VectorType::Random(50);
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m.conservativeResizeLike(Matrix<Scalar, Dynamic, Dynamic>::Zero(1, size));
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VERIFY_IS_APPROX(m.segment(0, 50), n);
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VERIFY(size <= 50 || m.segment(50, size - 50).sum() == Scalar(0));
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}
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}
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// Basic memory leak check with a non-copyable scalar type
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template <int>
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void noncopyable() {
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typedef Eigen::Matrix<AnnoyingScalar, Dynamic, 1> VectorType;
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typedef Eigen::Matrix<AnnoyingScalar, Dynamic, Dynamic> MatrixType;
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{
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#ifndef EIGEN_TEST_ANNOYING_SCALAR_DONT_THROW
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AnnoyingScalar::dont_throw = true;
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#endif
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int n = 50;
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VectorType v0(n), v1(n);
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MatrixType m0(n, n), m1(n, n), m2(n, n);
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v0.setOnes();
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v1.setOnes();
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m0.setOnes();
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m1.setOnes();
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m2.setOnes();
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VERIFY(m0 == m1);
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m0.conservativeResize(2 * n, 2 * n);
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VERIFY(m0.topLeftCorner(n, n) == m1);
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VERIFY(v0.head(n) == v1);
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v0.conservativeResize(2 * n);
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VERIFY(v0.head(n) == v1);
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}
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VERIFY(AnnoyingScalar::instances == 0 && "global memory leak detected in noncopyable");
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}
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EIGEN_DECLARE_TEST(conservative_resize) {
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for (int i = 0; i < g_repeat; ++i) {
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CALL_SUBTEST_1((run_matrix_tests<int, Eigen::RowMajor>()));
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CALL_SUBTEST_1((run_matrix_tests<int, Eigen::ColMajor>()));
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CALL_SUBTEST_2((run_matrix_tests<float, Eigen::RowMajor>()));
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CALL_SUBTEST_2((run_matrix_tests<float, Eigen::ColMajor>()));
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CALL_SUBTEST_3((run_matrix_tests<double, Eigen::RowMajor>()));
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CALL_SUBTEST_3((run_matrix_tests<double, Eigen::ColMajor>()));
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CALL_SUBTEST_4((run_matrix_tests<std::complex<float>, Eigen::RowMajor>()));
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CALL_SUBTEST_4((run_matrix_tests<std::complex<float>, Eigen::ColMajor>()));
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CALL_SUBTEST_5((run_matrix_tests<std::complex<double>, Eigen::RowMajor>()));
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CALL_SUBTEST_5((run_matrix_tests<std::complex<double>, Eigen::ColMajor>()));
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CALL_SUBTEST_1((run_matrix_tests<int, Eigen::RowMajor | Eigen::DontAlign>()));
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CALL_SUBTEST_1((run_vector_tests<int>()));
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CALL_SUBTEST_2((run_vector_tests<float>()));
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CALL_SUBTEST_3((run_vector_tests<double>()));
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CALL_SUBTEST_4((run_vector_tests<std::complex<float> >()));
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CALL_SUBTEST_5((run_vector_tests<std::complex<double> >()));
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#ifndef EIGEN_TEST_ANNOYING_SCALAR_DONT_THROW
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AnnoyingScalar::dont_throw = true;
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#endif
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CALL_SUBTEST_6((run_vector_tests<AnnoyingScalar>()));
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CALL_SUBTEST_6((noncopyable<0>()));
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}
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}
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