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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2009 Hauke Heibel <hauke.heibel@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"
#include <Eigen/Core>
#include "AnnoyingScalar.h"
using namespace Eigen;
template <typename Scalar, int Storage>
void run_matrix_tests() {
typedef Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic, Storage> MatrixType;
MatrixType m, n;
// boundary cases ...
m = n = MatrixType::Random(50, 50);
m.conservativeResize(1, 50);
VERIFY_IS_APPROX(m, n.block(0, 0, 1, 50));
m = n = MatrixType::Random(50, 50);
m.conservativeResize(50, 1);
VERIFY_IS_APPROX(m, n.block(0, 0, 50, 1));
m = n = MatrixType::Random(50, 50);
m.conservativeResize(50, 50);
VERIFY_IS_APPROX(m, n.block(0, 0, 50, 50));
// random shrinking ...
for (int i = 0; i < 25; ++i) {
const Index rows = internal::random<Index>(1, 50);
const Index cols = internal::random<Index>(1, 50);
m = n = MatrixType::Random(50, 50);
m.conservativeResize(rows, cols);
VERIFY_IS_APPROX(m, n.block(0, 0, rows, cols));
}
// random growing with zeroing ...
for (int i = 0; i < 25; ++i) {
const Index rows = internal::random<Index>(50, 75);
const Index cols = internal::random<Index>(50, 75);
m = n = MatrixType::Random(50, 50);
m.conservativeResizeLike(MatrixType::Zero(rows, cols));
VERIFY_IS_APPROX(m.block(0, 0, n.rows(), n.cols()), n);
VERIFY(rows <= 50 || m.block(50, 0, rows - 50, cols).sum() == Scalar(0));
VERIFY(cols <= 50 || m.block(0, 50, rows, cols - 50).sum() == Scalar(0));
}
}
template <typename Scalar>
void run_vector_tests() {
typedef Matrix<Scalar, 1, Eigen::Dynamic> VectorType;
VectorType m, n;
// boundary cases ...
m = n = VectorType::Random(50);
m.conservativeResize(1);
VERIFY_IS_APPROX(m, n.segment(0, 1));
m = n = VectorType::Random(50);
m.conservativeResize(50);
VERIFY_IS_APPROX(m, n.segment(0, 50));
m = n = VectorType::Random(50);
m.conservativeResize(m.rows(), 1);
VERIFY_IS_APPROX(m, n.segment(0, 1));
m = n = VectorType::Random(50);
m.conservativeResize(m.rows(), 50);
VERIFY_IS_APPROX(m, n.segment(0, 50));
// random shrinking ...
for (int i = 0; i < 50; ++i) {
const int size = internal::random<int>(1, 50);
m = n = VectorType::Random(50);
m.conservativeResize(size);
VERIFY_IS_APPROX(m, n.segment(0, size));
m = n = VectorType::Random(50);
m.conservativeResize(m.rows(), size);
VERIFY_IS_APPROX(m, n.segment(0, size));
}
// random growing with zeroing ...
for (int i = 0; i < 50; ++i) {
const int size = internal::random<int>(50, 100);
m = n = VectorType::Random(50);
m.conservativeResizeLike(VectorType::Zero(size));
VERIFY_IS_APPROX(m.segment(0, 50), n);
VERIFY(size <= 50 || m.segment(50, size - 50).sum() == Scalar(0));
m = n = VectorType::Random(50);
m.conservativeResizeLike(Matrix<Scalar, Dynamic, Dynamic>::Zero(1, size));
VERIFY_IS_APPROX(m.segment(0, 50), n);
VERIFY(size <= 50 || m.segment(50, size - 50).sum() == Scalar(0));
}
}
// Basic memory leak check with a non-copyable scalar type
template <int>
void noncopyable() {
typedef Eigen::Matrix<AnnoyingScalar, Dynamic, 1> VectorType;
typedef Eigen::Matrix<AnnoyingScalar, Dynamic, Dynamic> MatrixType;
{
#ifndef EIGEN_TEST_ANNOYING_SCALAR_DONT_THROW
AnnoyingScalar::dont_throw = true;
#endif
int n = 50;
VectorType v0(n), v1(n);
MatrixType m0(n, n), m1(n, n), m2(n, n);
v0.setOnes();
v1.setOnes();
m0.setOnes();
m1.setOnes();
m2.setOnes();
VERIFY(m0 == m1);
m0.conservativeResize(2 * n, 2 * n);
VERIFY(m0.topLeftCorner(n, n) == m1);
VERIFY(v0.head(n) == v1);
v0.conservativeResize(2 * n);
VERIFY(v0.head(n) == v1);
}
VERIFY(AnnoyingScalar::instances == 0 && "global memory leak detected in noncopyable");
}
EIGEN_DECLARE_TEST(conservative_resize) {
for (int i = 0; i < g_repeat; ++i) {
CALL_SUBTEST_1((run_matrix_tests<int, Eigen::RowMajor>()));
CALL_SUBTEST_1((run_matrix_tests<int, Eigen::ColMajor>()));
CALL_SUBTEST_2((run_matrix_tests<float, Eigen::RowMajor>()));
CALL_SUBTEST_2((run_matrix_tests<float, Eigen::ColMajor>()));
CALL_SUBTEST_3((run_matrix_tests<double, Eigen::RowMajor>()));
CALL_SUBTEST_3((run_matrix_tests<double, Eigen::ColMajor>()));
CALL_SUBTEST_4((run_matrix_tests<std::complex<float>, Eigen::RowMajor>()));
CALL_SUBTEST_4((run_matrix_tests<std::complex<float>, Eigen::ColMajor>()));
CALL_SUBTEST_5((run_matrix_tests<std::complex<double>, Eigen::RowMajor>()));
CALL_SUBTEST_5((run_matrix_tests<std::complex<double>, Eigen::ColMajor>()));
CALL_SUBTEST_1((run_matrix_tests<int, Eigen::RowMajor | Eigen::DontAlign>()));
CALL_SUBTEST_1((run_vector_tests<int>()));
CALL_SUBTEST_2((run_vector_tests<float>()));
CALL_SUBTEST_3((run_vector_tests<double>()));
CALL_SUBTEST_4((run_vector_tests<std::complex<float> >()));
CALL_SUBTEST_5((run_vector_tests<std::complex<double> >()));
#ifndef EIGEN_TEST_ANNOYING_SCALAR_DONT_THROW
AnnoyingScalar::dont_throw = true;
#endif
CALL_SUBTEST_6((run_vector_tests<AnnoyingScalar>()));
CALL_SUBTEST_6((noncopyable<0>()));
}
}