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87 lines
2.9 KiB
C++
87 lines
2.9 KiB
C++
// This file is part of Eigen, a lightweight C++ template library
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// for linear algebra. Eigen itself is part of the KDE project.
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//
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// Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@gmail.com>
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//
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// Eigen is free software; you can redistribute it and/or
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// modify it under the terms of the GNU Lesser General Public
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// License as published by the Free Software Foundation; either
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// version 3 of the License, or (at your option) any later version.
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//
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// Alternatively, you can redistribute it and/or
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// modify it under the terms of the GNU General Public License as
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// published by the Free Software Foundation; either version 2 of
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// the License, or (at your option) any later version.
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//
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// Eigen is distributed in the hope that it will be useful, but WITHOUT ANY
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// WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
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// FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public
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// License and a copy of the GNU General Public License along with
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// Eigen. If not, see <http://www.gnu.org/licenses/>.
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#include "main.h"
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template<typename MatrixType> void matrixSum(const MatrixType& m)
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{
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typedef typename MatrixType::Scalar Scalar;
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int rows = m.rows();
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int cols = m.cols();
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MatrixType m1 = MatrixType::Random(rows, cols);
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VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows, cols).sum(), Scalar(1));
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VERIFY_IS_APPROX(MatrixType::Ones(rows, cols).sum(), Scalar(float(rows*cols))); // the float() here to shut up excessive MSVC warning about int->complex conversion being lossy
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Scalar x = Scalar(0);
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for(int i = 0; i < rows; i++) for(int j = 0; j < cols; j++) x += m1(i,j);
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VERIFY_IS_APPROX(m1.sum(), x);
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}
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template<typename VectorType> void vectorSum(const VectorType& w)
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{
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typedef typename VectorType::Scalar Scalar;
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int size = w.size();
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VectorType v = VectorType::Random(size);
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for(int i = 1; i < size; i++)
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{
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Scalar s = Scalar(0);
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for(int j = 0; j < i; j++) s += v[j];
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VERIFY_IS_APPROX(s, v.start(i).sum());
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}
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for(int i = 0; i < size-1; i++)
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{
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Scalar s = Scalar(0);
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for(int j = i; j < size; j++) s += v[j];
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VERIFY_IS_APPROX(s, v.end(size-i).sum());
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}
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for(int i = 0; i < size/2; i++)
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{
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Scalar s = Scalar(0);
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for(int j = i; j < size-i; j++) s += v[j];
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VERIFY_IS_APPROX(s, v.segment(i, size-2*i).sum());
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}
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}
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void test_eigen2_sum()
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{
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_1( matrixSum(Matrix<float, 1, 1>()) );
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CALL_SUBTEST_2( matrixSum(Matrix2f()) );
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CALL_SUBTEST_3( matrixSum(Matrix4d()) );
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CALL_SUBTEST_4( matrixSum(MatrixXcf(3, 3)) );
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CALL_SUBTEST_5( matrixSum(MatrixXf(8, 12)) );
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CALL_SUBTEST_6( matrixSum(MatrixXi(8, 12)) );
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}
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for(int i = 0; i < g_repeat; i++) {
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CALL_SUBTEST_5( vectorSum(VectorXf(5)) );
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CALL_SUBTEST_7( vectorSum(VectorXd(10)) );
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CALL_SUBTEST_5( vectorSum(VectorXf(33)) );
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}
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}
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