| // This file is part of Eigen, a lightweight C++ template library |
| // for linear algebra. |
| // |
| // Copyright (C) 2008-2009 Gael Guennebaud <g.gael@free.fr> |
| // |
| // Eigen is free software; you can redistribute it and/or |
| // modify it under the terms of the GNU Lesser General Public |
| // License as published by the Free Software Foundation; either |
| // version 3 of the License, or (at your option) any later version. |
| // |
| // Alternatively, you can redistribute it and/or |
| // modify it under the terms of the GNU General Public License as |
| // published by the Free Software Foundation; either version 2 of |
| // the License, or (at your option) any later version. |
| // |
| // Eigen is distributed in the hope that it will be useful, but WITHOUT ANY |
| // WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS |
| // FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License or the |
| // GNU General Public License for more details. |
| // |
| // You should have received a copy of the GNU Lesser General Public |
| // License and a copy of the GNU General Public License along with |
| // Eigen. If not, see <http://www.gnu.org/licenses/>. |
| |
| #include "main.h" |
| |
| template<typename MatrixType> void array(const MatrixType& m) |
| { |
| typedef typename MatrixType::Scalar Scalar; |
| typedef typename NumTraits<Scalar>::Real RealScalar; |
| typedef Array<Scalar, MatrixType::RowsAtCompileTime, 1> ColVectorType; |
| typedef Array<Scalar, 1, MatrixType::ColsAtCompileTime> RowVectorType; |
| |
| int rows = m.rows(); |
| int cols = m.cols(); |
| |
| MatrixType m1 = MatrixType::Random(rows, cols), |
| m2 = MatrixType::Random(rows, cols), |
| m3(rows, cols); |
| |
| ColVectorType cv1 = ColVectorType::Random(rows); |
| RowVectorType rv1 = RowVectorType::Random(cols); |
| |
| Scalar s1 = ei_random<Scalar>(), |
| s2 = ei_random<Scalar>(); |
| |
| // scalar addition |
| VERIFY_IS_APPROX(m1 + s1, s1 + m1); |
| VERIFY_IS_APPROX(m1 + s1, MatrixType::Constant(rows,cols,s1) + m1); |
| VERIFY_IS_APPROX(s1 - m1, (-m1)+s1 ); |
| VERIFY_IS_APPROX(m1 - s1, m1 - MatrixType::Constant(rows,cols,s1)); |
| VERIFY_IS_APPROX(s1 - m1, MatrixType::Constant(rows,cols,s1) - m1); |
| VERIFY_IS_APPROX((m1*Scalar(2)) - s2, (m1+m1) - MatrixType::Constant(rows,cols,s2) ); |
| m3 = m1; |
| m3 += s2; |
| VERIFY_IS_APPROX(m3, m1 + s2); |
| m3 = m1; |
| m3 -= s1; |
| VERIFY_IS_APPROX(m3, m1 - s1); |
| |
| // reductions |
| VERIFY_IS_APPROX(m1.colwise().sum().sum(), m1.sum()); |
| VERIFY_IS_APPROX(m1.rowwise().sum().sum(), m1.sum()); |
| if (!ei_isApprox(m1.sum(), (m1+m2).sum())) |
| VERIFY_IS_NOT_APPROX(((m1+m2).rowwise().sum()).sum(), m1.sum()); |
| VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(ei_scalar_sum_op<Scalar>())); |
| |
| // vector-wise ops |
| m3 = m1; |
| VERIFY_IS_APPROX(m3.colwise() += cv1, m1.colwise() + cv1); |
| m3 = m1; |
| VERIFY_IS_APPROX(m3.colwise() -= cv1, m1.colwise() - cv1); |
| m3 = m1; |
| VERIFY_IS_APPROX(m3.rowwise() += rv1, m1.rowwise() + rv1); |
| m3 = m1; |
| VERIFY_IS_APPROX(m3.rowwise() -= rv1, m1.rowwise() - rv1); |
| } |
| |
| template<typename MatrixType> void comparisons(const MatrixType& m) |
| { |
| typedef typename MatrixType::Scalar Scalar; |
| typedef typename NumTraits<Scalar>::Real RealScalar; |
| typedef Array<Scalar, MatrixType::RowsAtCompileTime, 1> VectorType; |
| |
| int rows = m.rows(); |
| int cols = m.cols(); |
| |
| int r = ei_random<int>(0, rows-1), |
| c = ei_random<int>(0, cols-1); |
| |
| MatrixType m1 = MatrixType::Random(rows, cols), |
| m2 = MatrixType::Random(rows, cols), |
| m3(rows, cols); |
| |
| VERIFY(((m1 + Scalar(1)) > m1).all()); |
| VERIFY(((m1 - Scalar(1)) < m1).all()); |
| if (rows*cols>1) |
| { |
| m3 = m1; |
| m3(r,c) += 1; |
| VERIFY(! (m1 < m3).all() ); |
| VERIFY(! (m1 > m3).all() ); |
| } |
| |
| // comparisons to scalar |
| VERIFY( (m1 != (m1(r,c)+1) ).any() ); |
| VERIFY( (m1 > (m1(r,c)-1) ).any() ); |
| VERIFY( (m1 < (m1(r,c)+1) ).any() ); |
| VERIFY( (m1 == m1(r,c) ).any() ); |
| |
| // test Select |
| VERIFY_IS_APPROX( (m1<m2).select(m1,m2), m1.cwiseMin(m2) ); |
| VERIFY_IS_APPROX( (m1>m2).select(m1,m2), m1.cwiseMax(m2) ); |
| Scalar mid = (m1.cwiseAbs().minCoeff() + m1.cwiseAbs().maxCoeff())/Scalar(2); |
| for (int j=0; j<cols; ++j) |
| for (int i=0; i<rows; ++i) |
| m3(i,j) = ei_abs(m1(i,j))<mid ? 0 : m1(i,j); |
| VERIFY_IS_APPROX( (m1.abs()<MatrixType::Constant(rows,cols,mid)) |
| .select(MatrixType::Zero(rows,cols),m1), m3); |
| // shorter versions: |
| VERIFY_IS_APPROX( (m1.abs()<MatrixType::Constant(rows,cols,mid)) |
| .select(0,m1), m3); |
| VERIFY_IS_APPROX( (m1.abs()>=MatrixType::Constant(rows,cols,mid)) |
| .select(m1,0), m3); |
| // even shorter version: |
| VERIFY_IS_APPROX( (m1.abs()<mid).select(0,m1), m3); |
| |
| // count |
| VERIFY(((m1.abs()+1)>RealScalar(0.1)).count() == rows*cols); |
| // TODO allows colwise/rowwise for array |
| VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).colwise().count(), ArrayXi::Constant(cols,rows).transpose()); |
| VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).rowwise().count(), ArrayXi::Constant(rows, cols)); |
| } |
| |
| void test_array() |
| { |
| for(int i = 0; i < g_repeat; i++) { |
| CALL_SUBTEST_1( array(Array<float, 1, 1>()) ); |
| CALL_SUBTEST_2( array(Array22f()) ); |
| CALL_SUBTEST_3( array(Array44d()) ); |
| CALL_SUBTEST_4( array(ArrayXXcf(3, 3)) ); |
| CALL_SUBTEST_5( array(ArrayXXf(8, 12)) ); |
| CALL_SUBTEST_6( array(ArrayXXi(8, 12)) ); |
| } |
| for(int i = 0; i < g_repeat; i++) { |
| CALL_SUBTEST_1( comparisons(Array<float, 1, 1>()) ); |
| CALL_SUBTEST_2( comparisons(Array22f()) ); |
| CALL_SUBTEST_3( comparisons(Array44d()) ); |
| CALL_SUBTEST_5( comparisons(ArrayXXf(8, 12)) ); |
| CALL_SUBTEST_6( comparisons(ArrayXXi(8, 12)) ); |
| } |
| } |