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Diffstat (limited to 'eigen/test/array.cpp')
| -rw-r--r-- | eigen/test/array.cpp | 308 |
1 files changed, 308 insertions, 0 deletions
diff --git a/eigen/test/array.cpp b/eigen/test/array.cpp new file mode 100644 index 0000000..68f6b3d --- /dev/null +++ b/eigen/test/array.cpp @@ -0,0 +1,308 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr> +// +// 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 ArrayType> void array(const ArrayType& m) +{ + typedef typename ArrayType::Index Index; + typedef typename ArrayType::Scalar Scalar; + typedef Array<Scalar, ArrayType::RowsAtCompileTime, 1> ColVectorType; + typedef Array<Scalar, 1, ArrayType::ColsAtCompileTime> RowVectorType; + + Index rows = m.rows(); + Index cols = m.cols(); + + ArrayType m1 = ArrayType::Random(rows, cols), + m2 = ArrayType::Random(rows, cols), + m3(rows, cols); + + ColVectorType cv1 = ColVectorType::Random(rows); + RowVectorType rv1 = RowVectorType::Random(cols); + + Scalar s1 = internal::random<Scalar>(), + s2 = internal::random<Scalar>(); + + // scalar addition + VERIFY_IS_APPROX(m1 + s1, s1 + m1); + VERIFY_IS_APPROX(m1 + s1, ArrayType::Constant(rows,cols,s1) + m1); + VERIFY_IS_APPROX(s1 - m1, (-m1)+s1 ); + VERIFY_IS_APPROX(m1 - s1, m1 - ArrayType::Constant(rows,cols,s1)); + VERIFY_IS_APPROX(s1 - m1, ArrayType::Constant(rows,cols,s1) - m1); + VERIFY_IS_APPROX((m1*Scalar(2)) - s2, (m1+m1) - ArrayType::Constant(rows,cols,s2) ); + m3 = m1; + m3 += s2; + VERIFY_IS_APPROX(m3, m1 + s2); + m3 = m1; + m3 -= s1; + VERIFY_IS_APPROX(m3, m1 - s1); + + // scalar operators via Maps + m3 = m1; + ArrayType::Map(m1.data(), m1.rows(), m1.cols()) -= ArrayType::Map(m2.data(), m2.rows(), m2.cols()); + VERIFY_IS_APPROX(m1, m3 - m2); + + m3 = m1; + ArrayType::Map(m1.data(), m1.rows(), m1.cols()) += ArrayType::Map(m2.data(), m2.rows(), m2.cols()); + VERIFY_IS_APPROX(m1, m3 + m2); + + m3 = m1; + ArrayType::Map(m1.data(), m1.rows(), m1.cols()) *= ArrayType::Map(m2.data(), m2.rows(), m2.cols()); + VERIFY_IS_APPROX(m1, m3 * m2); + + m3 = m1; + m2 = ArrayType::Random(rows,cols); + m2 = (m2==0).select(1,m2); + ArrayType::Map(m1.data(), m1.rows(), m1.cols()) /= ArrayType::Map(m2.data(), m2.rows(), m2.cols()); + VERIFY_IS_APPROX(m1, m3 / m2); + + // reductions + VERIFY_IS_APPROX(m1.abs().colwise().sum().sum(), m1.abs().sum()); + VERIFY_IS_APPROX(m1.abs().rowwise().sum().sum(), m1.abs().sum()); + using std::abs; + VERIFY_IS_MUCH_SMALLER_THAN(abs(m1.colwise().sum().sum() - m1.sum()), m1.abs().sum()); + VERIFY_IS_MUCH_SMALLER_THAN(abs(m1.rowwise().sum().sum() - m1.sum()), m1.abs().sum()); + if (!internal::isMuchSmallerThan(abs(m1.sum() - (m1+m2).sum()), m1.abs().sum(), test_precision<Scalar>())) + VERIFY_IS_NOT_APPROX(((m1+m2).rowwise().sum()).sum(), m1.sum()); + VERIFY_IS_APPROX(m1.colwise().sum(), m1.colwise().redux(internal::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 ArrayType> void comparisons(const ArrayType& m) +{ + using std::abs; + typedef typename ArrayType::Index Index; + typedef typename ArrayType::Scalar Scalar; + typedef typename NumTraits<Scalar>::Real RealScalar; + + Index rows = m.rows(); + Index cols = m.cols(); + + Index r = internal::random<Index>(0, rows-1), + c = internal::random<Index>(0, cols-1); + + ArrayType m1 = ArrayType::Random(rows, cols), + m2 = ArrayType::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() ); + } + VERIFY(!(m1 > m2 && m1 < m2).any()); + VERIFY((m1 <= m2 || m1 >= m2).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) = abs(m1(i,j))<mid ? 0 : m1(i,j); + VERIFY_IS_APPROX( (m1.abs()<ArrayType::Constant(rows,cols,mid)) + .select(ArrayType::Zero(rows,cols),m1), m3); + // shorter versions: + VERIFY_IS_APPROX( (m1.abs()<ArrayType::Constant(rows,cols,mid)) + .select(0,m1), m3); + VERIFY_IS_APPROX( (m1.abs()>=ArrayType::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); + + // and/or + VERIFY( (m1<RealScalar(0) && m1>RealScalar(0)).count() == 0); + VERIFY( (m1<RealScalar(0) || m1>=RealScalar(0)).count() == rows*cols); + RealScalar a = m1.abs().mean(); + VERIFY( (m1<-a || m1>a).count() == (m1.abs()>a).count()); + + typedef Array<typename ArrayType::Index, Dynamic, 1> ArrayOfIndices; + + // TODO allows colwise/rowwise for array + VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).colwise().count(), ArrayOfIndices::Constant(cols,rows).transpose()); + VERIFY_IS_APPROX(((m1.abs()+1)>RealScalar(0.1)).rowwise().count(), ArrayOfIndices::Constant(rows, cols)); +} + +template<typename ArrayType> void array_real(const ArrayType& m) +{ + using std::abs; + using std::sqrt; + typedef typename ArrayType::Index Index; + typedef typename ArrayType::Scalar Scalar; + typedef typename NumTraits<Scalar>::Real RealScalar; + + Index rows = m.rows(); + Index cols = m.cols(); + + ArrayType m1 = ArrayType::Random(rows, cols), + m2 = ArrayType::Random(rows, cols), + m3(rows, cols); + + Scalar s1 = internal::random<Scalar>(); + + // these tests are mostly to check possible compilation issues. + VERIFY_IS_APPROX(m1.sin(), sin(m1)); + VERIFY_IS_APPROX(m1.cos(), cos(m1)); + VERIFY_IS_APPROX(m1.asin(), asin(m1)); + VERIFY_IS_APPROX(m1.acos(), acos(m1)); + VERIFY_IS_APPROX(m1.tan(), tan(m1)); + + VERIFY_IS_APPROX(cos(m1+RealScalar(3)*m2), cos((m1+RealScalar(3)*m2).eval())); + + VERIFY_IS_APPROX(m1.abs().sqrt(), sqrt(abs(m1))); + VERIFY_IS_APPROX(m1.abs(), sqrt(numext::abs2(m1))); + + VERIFY_IS_APPROX(numext::abs2(numext::real(m1)) + numext::abs2(numext::imag(m1)), numext::abs2(m1)); + VERIFY_IS_APPROX(numext::abs2(real(m1)) + numext::abs2(imag(m1)), numext::abs2(m1)); + if(!NumTraits<Scalar>::IsComplex) + VERIFY_IS_APPROX(numext::real(m1), m1); + + // shift argument of logarithm so that it is not zero + Scalar smallNumber = NumTraits<Scalar>::dummy_precision(); + VERIFY_IS_APPROX((m1.abs() + smallNumber).log() , log(abs(m1) + smallNumber)); + + VERIFY_IS_APPROX(m1.exp() * m2.exp(), exp(m1+m2)); + VERIFY_IS_APPROX(m1.exp(), exp(m1)); + VERIFY_IS_APPROX(m1.exp() / m2.exp(),(m1-m2).exp()); + + VERIFY_IS_APPROX(m1.pow(2), m1.square()); + VERIFY_IS_APPROX(pow(m1,2), m1.square()); + + ArrayType exponents = ArrayType::Constant(rows, cols, RealScalar(2)); + VERIFY_IS_APPROX(Eigen::pow(m1,exponents), m1.square()); + + m3 = m1.abs(); + VERIFY_IS_APPROX(m3.pow(RealScalar(0.5)), m3.sqrt()); + VERIFY_IS_APPROX(pow(m3,RealScalar(0.5)), m3.sqrt()); + + // scalar by array division + const RealScalar tiny = sqrt(std::numeric_limits<RealScalar>::epsilon()); + s1 += Scalar(tiny); + m1 += ArrayType::Constant(rows,cols,Scalar(tiny)); + VERIFY_IS_APPROX(s1/m1, s1 * m1.inverse()); + + // check inplace transpose + m3 = m1; + m3.transposeInPlace(); + VERIFY_IS_APPROX(m3,m1.transpose()); + m3.transposeInPlace(); + VERIFY_IS_APPROX(m3,m1); +} + +template<typename ArrayType> void array_complex(const ArrayType& m) +{ + typedef typename ArrayType::Index Index; + + Index rows = m.rows(); + Index cols = m.cols(); + + ArrayType m1 = ArrayType::Random(rows, cols), + m2(rows, cols); + + for (Index i = 0; i < m.rows(); ++i) + for (Index j = 0; j < m.cols(); ++j) + m2(i,j) = sqrt(m1(i,j)); + + VERIFY_IS_APPROX(m1.sqrt(), m2); + VERIFY_IS_APPROX(m1.sqrt(), Eigen::sqrt(m1)); +} + +template<typename ArrayType> void min_max(const ArrayType& m) +{ + typedef typename ArrayType::Index Index; + typedef typename ArrayType::Scalar Scalar; + + Index rows = m.rows(); + Index cols = m.cols(); + + ArrayType m1 = ArrayType::Random(rows, cols); + + // min/max with array + Scalar maxM1 = m1.maxCoeff(); + Scalar minM1 = m1.minCoeff(); + + VERIFY_IS_APPROX(ArrayType::Constant(rows,cols, minM1), (m1.min)(ArrayType::Constant(rows,cols, minM1))); + VERIFY_IS_APPROX(m1, (m1.min)(ArrayType::Constant(rows,cols, maxM1))); + + VERIFY_IS_APPROX(ArrayType::Constant(rows,cols, maxM1), (m1.max)(ArrayType::Constant(rows,cols, maxM1))); + VERIFY_IS_APPROX(m1, (m1.max)(ArrayType::Constant(rows,cols, minM1))); + + // min/max with scalar input + VERIFY_IS_APPROX(ArrayType::Constant(rows,cols, minM1), (m1.min)( minM1)); + VERIFY_IS_APPROX(m1, (m1.min)( maxM1)); + + VERIFY_IS_APPROX(ArrayType::Constant(rows,cols, maxM1), (m1.max)( maxM1)); + VERIFY_IS_APPROX(m1, (m1.max)( minM1)); + +} + +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(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_5( array(ArrayXXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_6( array(ArrayXXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); + } + 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(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_6( comparisons(ArrayXXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); + } + for(int i = 0; i < g_repeat; i++) { + CALL_SUBTEST_1( min_max(Array<float, 1, 1>()) ); + CALL_SUBTEST_2( min_max(Array22f()) ); + CALL_SUBTEST_3( min_max(Array44d()) ); + CALL_SUBTEST_5( min_max(ArrayXXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); + CALL_SUBTEST_6( min_max(ArrayXXi(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); + } + for(int i = 0; i < g_repeat; i++) { + CALL_SUBTEST_1( array_real(Array<float, 1, 1>()) ); + CALL_SUBTEST_2( array_real(Array22f()) ); + CALL_SUBTEST_3( array_real(Array44d()) ); + CALL_SUBTEST_5( array_real(ArrayXXf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); + } + for(int i = 0; i < g_repeat; i++) { + CALL_SUBTEST_4( array_complex(ArrayXXcf(internal::random<int>(1,EIGEN_TEST_MAX_SIZE), internal::random<int>(1,EIGEN_TEST_MAX_SIZE))) ); + } + + VERIFY((internal::is_same< internal::global_math_functions_filtering_base<int>::type, int >::value)); + VERIFY((internal::is_same< internal::global_math_functions_filtering_base<float>::type, float >::value)); + VERIFY((internal::is_same< internal::global_math_functions_filtering_base<Array2i>::type, ArrayBase<Array2i> >::value)); + typedef CwiseUnaryOp<internal::scalar_sum_op<double>, ArrayXd > Xpr; + VERIFY((internal::is_same< internal::global_math_functions_filtering_base<Xpr>::type, + ArrayBase<Xpr> + >::value)); +} |