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// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2008 Gael Guennebaud <gael.guennebaud@inria.fr>
// Copyright (C) 2006-2008 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/.
// discard stack allocation as that too bypasses malloc
#define EIGEN_STACK_ALLOCATION_LIMIT 0
// heap allocation will raise an assert if enabled at runtime
#define EIGEN_RUNTIME_NO_MALLOC
#include "main.h"
#include <Eigen/Cholesky>
#include <Eigen/Eigenvalues>
#include <Eigen/LU>
#include <Eigen/QR>
#include <Eigen/SVD>
template<typename MatrixType> void nomalloc(const MatrixType& m){ /* this test check no dynamic memory allocation are issued with fixed-size matrices
*/ typedef typename MatrixType::Index Index; typedef typename MatrixType::Scalar Scalar;
Index rows = m.rows(); Index cols = m.cols();
MatrixType m1 = MatrixType::Random(rows, cols), m2 = MatrixType::Random(rows, cols), m3(rows, cols);
Scalar s1 = internal::random<Scalar>();
Index r = internal::random<Index>(0, rows-1), c = internal::random<Index>(0, cols-1);
VERIFY_IS_APPROX((m1+m2)*s1, s1*m1+s1*m2); VERIFY_IS_APPROX((m1+m2)(r,c), (m1(r,c))+(m2(r,c))); VERIFY_IS_APPROX(m1.cwiseProduct(m1.block(0,0,rows,cols)), (m1.array()*m1.array()).matrix()); VERIFY_IS_APPROX((m1*m1.transpose())*m2, m1*(m1.transpose()*m2)); m2.col(0).noalias() = m1 * m1.col(0); m2.col(0).noalias() -= m1.adjoint() * m1.col(0); m2.col(0).noalias() -= m1 * m1.row(0).adjoint(); m2.col(0).noalias() -= m1.adjoint() * m1.row(0).adjoint();
m2.row(0).noalias() = m1.row(0) * m1; m2.row(0).noalias() -= m1.row(0) * m1.adjoint(); m2.row(0).noalias() -= m1.col(0).adjoint() * m1; m2.row(0).noalias() -= m1.col(0).adjoint() * m1.adjoint(); VERIFY_IS_APPROX(m2,m2); m2.col(0).noalias() = m1.template triangularView<Upper>() * m1.col(0); m2.col(0).noalias() -= m1.adjoint().template triangularView<Upper>() * m1.col(0); m2.col(0).noalias() -= m1.template triangularView<Upper>() * m1.row(0).adjoint(); m2.col(0).noalias() -= m1.adjoint().template triangularView<Upper>() * m1.row(0).adjoint();
m2.row(0).noalias() = m1.row(0) * m1.template triangularView<Upper>(); m2.row(0).noalias() -= m1.row(0) * m1.adjoint().template triangularView<Upper>(); m2.row(0).noalias() -= m1.col(0).adjoint() * m1.template triangularView<Upper>(); m2.row(0).noalias() -= m1.col(0).adjoint() * m1.adjoint().template triangularView<Upper>(); VERIFY_IS_APPROX(m2,m2); m2.col(0).noalias() = m1.template selfadjointView<Upper>() * m1.col(0); m2.col(0).noalias() -= m1.adjoint().template selfadjointView<Upper>() * m1.col(0); m2.col(0).noalias() -= m1.template selfadjointView<Upper>() * m1.row(0).adjoint(); m2.col(0).noalias() -= m1.adjoint().template selfadjointView<Upper>() * m1.row(0).adjoint();
m2.row(0).noalias() = m1.row(0) * m1.template selfadjointView<Upper>(); m2.row(0).noalias() -= m1.row(0) * m1.adjoint().template selfadjointView<Upper>(); m2.row(0).noalias() -= m1.col(0).adjoint() * m1.template selfadjointView<Upper>(); m2.row(0).noalias() -= m1.col(0).adjoint() * m1.adjoint().template selfadjointView<Upper>(); VERIFY_IS_APPROX(m2,m2); m2.template selfadjointView<Lower>().rankUpdate(m1.col(0),-1); m2.template selfadjointView<Lower>().rankUpdate(m1.row(0),-1);
// The following fancy matrix-matrix products are not safe yet regarding static allocation
// m1 += m1.template triangularView<Upper>() * m2.col(;
// m1.template selfadjointView<Lower>().rankUpdate(m2);
// m1 += m1.template triangularView<Upper>() * m2;
// m1 += m1.template selfadjointView<Lower>() * m2;
// VERIFY_IS_APPROX(m1,m1);
}
template<typename Scalar>void ctms_decompositions(){ const int maxSize = 16; const int size = 12;
typedef StormEigen::Matrix<Scalar, StormEigen::Dynamic, StormEigen::Dynamic, 0, maxSize, maxSize> Matrix;
typedef StormEigen::Matrix<Scalar, StormEigen::Dynamic, 1, 0, maxSize, 1> Vector;
typedef StormEigen::Matrix<std::complex<Scalar>, StormEigen::Dynamic, StormEigen::Dynamic, 0, maxSize, maxSize> ComplexMatrix;
const Matrix A(Matrix::Random(size, size)), B(Matrix::Random(size, size)); Matrix X(size,size); const ComplexMatrix complexA(ComplexMatrix::Random(size, size)); const Matrix saA = A.adjoint() * A; const Vector b(Vector::Random(size)); Vector x(size);
// Cholesky module
StormEigen::LLT<Matrix> LLT; LLT.compute(A); X = LLT.solve(B); x = LLT.solve(b); StormEigen::LDLT<Matrix> LDLT; LDLT.compute(A); X = LDLT.solve(B); x = LDLT.solve(b);
// Eigenvalues module
StormEigen::HessenbergDecomposition<ComplexMatrix> hessDecomp; hessDecomp.compute(complexA); StormEigen::ComplexSchur<ComplexMatrix> cSchur(size); cSchur.compute(complexA); StormEigen::ComplexEigenSolver<ComplexMatrix> cEigSolver; cEigSolver.compute(complexA); StormEigen::EigenSolver<Matrix> eigSolver; eigSolver.compute(A); StormEigen::SelfAdjointEigenSolver<Matrix> saEigSolver(size); saEigSolver.compute(saA); StormEigen::Tridiagonalization<Matrix> tridiag; tridiag.compute(saA);
// LU module
StormEigen::PartialPivLU<Matrix> ppLU; ppLU.compute(A); X = ppLU.solve(B); x = ppLU.solve(b); StormEigen::FullPivLU<Matrix> fpLU; fpLU.compute(A); X = fpLU.solve(B); x = fpLU.solve(b);
// QR module
StormEigen::HouseholderQR<Matrix> hQR; hQR.compute(A); X = hQR.solve(B); x = hQR.solve(b); StormEigen::ColPivHouseholderQR<Matrix> cpQR; cpQR.compute(A); X = cpQR.solve(B); x = cpQR.solve(b); StormEigen::FullPivHouseholderQR<Matrix> fpQR; fpQR.compute(A); // FIXME X = fpQR.solve(B);
x = fpQR.solve(b);
// SVD module
StormEigen::JacobiSVD<Matrix> jSVD; jSVD.compute(A, ComputeFullU | ComputeFullV);}
void test_zerosized() { // default constructors:
StormEigen::MatrixXd A; StormEigen::VectorXd v; // explicit zero-sized:
StormEigen::ArrayXXd A0(0,0); StormEigen::ArrayXd v0(0);
// assigning empty objects to each other:
A=A0; v=v0;}
template<typename MatrixType> void test_reference(const MatrixType& m) { typedef typename MatrixType::Scalar Scalar; enum { Flag = MatrixType::IsRowMajor ? StormEigen::RowMajor : StormEigen::ColMajor}; enum { TransposeFlag = !MatrixType::IsRowMajor ? StormEigen::RowMajor : StormEigen::ColMajor}; typename MatrixType::Index rows = m.rows(), cols=m.cols(); typedef StormEigen::Matrix<Scalar, StormEigen::Dynamic, Eigen::Dynamic, Flag > MatrixX; typedef StormEigen::Matrix<Scalar, StormEigen::Dynamic, Eigen::Dynamic, TransposeFlag> MatrixXT; // Dynamic reference:
typedef StormEigen::Ref<const MatrixX > Ref; typedef StormEigen::Ref<const MatrixXT > RefT;
Ref r1(m); Ref r2(m.block(rows/3, cols/4, rows/2, cols/2)); RefT r3(m.transpose()); RefT r4(m.topLeftCorner(rows/2, cols/2).transpose());
VERIFY_RAISES_ASSERT(RefT r5(m)); VERIFY_RAISES_ASSERT(Ref r6(m.transpose())); VERIFY_RAISES_ASSERT(Ref r7(Scalar(2) * m));
// Copy constructors shall also never malloc
Ref r8 = r1; RefT r9 = r3;
// Initializing from a compatible Ref shall also never malloc
StormEigen::Ref<const MatrixX, Unaligned, Stride<Dynamic, Dynamic> > r10=r8, r11=m;
// Initializing from an incompatible Ref will malloc:
typedef StormEigen::Ref<const MatrixX, Aligned> RefAligned; VERIFY_RAISES_ASSERT(RefAligned r12=r10); VERIFY_RAISES_ASSERT(Ref r13=r10); // r10 has more dynamic strides
}
void test_nomalloc(){ // create some dynamic objects
StormEigen::MatrixXd M1 = MatrixXd::Random(3,3); Ref<const MatrixXd> R1 = 2.0*M1; // Ref requires temporary
// from here on prohibit malloc:
StormEigen::internal::set_is_malloc_allowed(false);
// check that our operator new is indeed called:
VERIFY_RAISES_ASSERT(MatrixXd dummy(MatrixXd::Random(3,3))); CALL_SUBTEST_1(nomalloc(Matrix<float, 1, 1>()) ); CALL_SUBTEST_2(nomalloc(Matrix4d()) ); CALL_SUBTEST_3(nomalloc(Matrix<float,32,32>()) ); // Check decomposition modules with dynamic matrices that have a known compile-time max size (ctms)
CALL_SUBTEST_4(ctms_decompositions<float>());
CALL_SUBTEST_5(test_zerosized());
CALL_SUBTEST_6(test_reference(Matrix<float,32,32>())); CALL_SUBTEST_7(test_reference(R1)); CALL_SUBTEST_8(Ref<MatrixXd> R2 = M1.topRows<2>(); test_reference(R2));}
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