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							71 lines
						
					
					
						
							2.2 KiB
						
					
					
				| // This file is part of Eigen, a lightweight C++ template library | |
| // for linear algebra. Eigen itself is part of the KDE project. | |
| // | |
| // Copyright (C) 2008 Benoit Jacob <jacob.benoit.1@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" | |
|  | |
| template<typename MatrixType> void matrixSum(const MatrixType& m) | |
| { | |
|   typedef typename MatrixType::Scalar Scalar; | |
| 
 | |
|   int rows = m.rows(); | |
|   int cols = m.cols(); | |
| 
 | |
|   MatrixType m1 = MatrixType::Random(rows, cols); | |
| 
 | |
|   VERIFY_IS_MUCH_SMALLER_THAN(MatrixType::Zero(rows, cols).sum(), Scalar(1)); | |
|   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 | |
|   Scalar x = Scalar(0); | |
|   for(int i = 0; i < rows; i++) for(int j = 0; j < cols; j++) x += m1(i,j); | |
|   VERIFY_IS_APPROX(m1.sum(), x); | |
| } | |
| 
 | |
| template<typename VectorType> void vectorSum(const VectorType& w) | |
| { | |
|   typedef typename VectorType::Scalar Scalar; | |
|   int size = w.size(); | |
| 
 | |
|   VectorType v = VectorType::Random(size); | |
|   for(int i = 1; i < size; i++) | |
|   { | |
|     Scalar s = Scalar(0); | |
|     for(int j = 0; j < i; j++) s += v[j]; | |
|     VERIFY_IS_APPROX(s, v.start(i).sum()); | |
|   } | |
| 
 | |
|   for(int i = 0; i < size-1; i++) | |
|   { | |
|     Scalar s = Scalar(0); | |
|     for(int j = i; j < size; j++) s += v[j]; | |
|     VERIFY_IS_APPROX(s, v.end(size-i).sum()); | |
|   } | |
| 
 | |
|   for(int i = 0; i < size/2; i++) | |
|   { | |
|     Scalar s = Scalar(0); | |
|     for(int j = i; j < size-i; j++) s += v[j]; | |
|     VERIFY_IS_APPROX(s, v.segment(i, size-2*i).sum()); | |
|   } | |
| } | |
| 
 | |
| void test_eigen2_sum() | |
| { | |
|   for(int i = 0; i < g_repeat; i++) { | |
|     CALL_SUBTEST_1( matrixSum(Matrix<float, 1, 1>()) ); | |
|     CALL_SUBTEST_2( matrixSum(Matrix2f()) ); | |
|     CALL_SUBTEST_3( matrixSum(Matrix4d()) ); | |
|     CALL_SUBTEST_4( matrixSum(MatrixXcf(3, 3)) ); | |
|     CALL_SUBTEST_5( matrixSum(MatrixXf(8, 12)) ); | |
|     CALL_SUBTEST_6( matrixSum(MatrixXi(8, 12)) ); | |
|   } | |
|   for(int i = 0; i < g_repeat; i++) { | |
|     CALL_SUBTEST_5( vectorSum(VectorXf(5)) ); | |
|     CALL_SUBTEST_7( vectorSum(VectorXd(10)) ); | |
|     CALL_SUBTEST_5( vectorSum(VectorXf(33)) ); | |
|   } | |
| }
 |