| // 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; | 
 |    | 
 |   { | 
 |     AnnoyingScalar::dont_throw = true; | 
 |     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_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> >())); | 
 |  | 
 |     AnnoyingScalar::dont_throw = true; | 
 |     CALL_SUBTEST_6(( run_vector_tests<AnnoyingScalar>() )); | 
 |     CALL_SUBTEST_6(( noncopyable<0>() )); | 
 |   } | 
 | } |