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This commit is contained in:
Gael Guennebaud
2014-08-29 15:20:31 +02:00
parent f29dbec321 aec3d90ca6
commit 124d12a915
41 changed files with 630 additions and 296 deletions
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8
test/CMakeLists.txt
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@@ -158,7 +158,9 @@ ei_add_test(basicstuff)
ei_add_test(linearstructure)
ei_add_test(integer_types)
ei_add_test(unalignedcount)
ei_add_test(exceptions)
if(NOT EIGEN_TEST_NO_EXCEPTIONS)
ei_add_test(exceptions)
endif()
ei_add_test(redux)
ei_add_test(visitor)
ei_add_test(block)
@@ -242,7 +244,9 @@ ei_add_test(nesting_ops "${CMAKE_CXX_FLAGS_DEBUG}")
ei_add_test(zerosized)
ei_add_test(dontalign)
ei_add_test(evaluators)
ei_add_test(sizeoverflow)
if(NOT EIGEN_TEST_NO_EXCEPTIONS)
ei_add_test(sizeoverflow)
endif()
ei_add_test(prec_inverse_4x4)
ei_add_test(vectorwiseop)
ei_add_test(special_numbers)

34
test/basicstuff.cpp
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@@ -183,6 +183,7 @@ void fixedSizeMatrixConstruction()
Scalar raw[4];
for(int k=0; k<4; ++k)
raw[k] = internal::random<Scalar>();
{
Matrix<Scalar,4,1> m(raw);
Array<Scalar,4,1> a(raw);
@@ -200,18 +201,40 @@ void fixedSizeMatrixConstruction()
VERIFY((a==Array<Scalar,3,1>(raw[0],raw[1],raw[2])).all());
}
{
Matrix<Scalar,2,1> m(raw);
Array<Scalar,2,1> a(raw);
Matrix<Scalar,2,1> m(raw), m2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) );
Array<Scalar,2,1> a(raw), a2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) );
for(int k=0; k<2; ++k) VERIFY(m(k) == raw[k]);
for(int k=0; k<2; ++k) VERIFY(a(k) == raw[k]);
VERIFY_IS_EQUAL(m,(Matrix<Scalar,2,1>(raw[0],raw[1])));
VERIFY((a==Array<Scalar,2,1>(raw[0],raw[1])).all());
for(int k=0; k<2; ++k) VERIFY(m2(k) == DenseIndex(raw[k]));
for(int k=0; k<2; ++k) VERIFY(a2(k) == DenseIndex(raw[k]));
}
{
Matrix<Scalar,1,1> m(raw);
Array<Scalar,1,1> a(raw);
Matrix<Scalar,1,2> m(raw),
m2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) ),
m3( (int(raw[0])), (int(raw[1])) ),
m4( (float(raw[0])), (float(raw[1])) );
Array<Scalar,1,2> a(raw), a2( (DenseIndex(raw[0])), (DenseIndex(raw[1])) );
for(int k=0; k<2; ++k) VERIFY(m(k) == raw[k]);
for(int k=0; k<2; ++k) VERIFY(a(k) == raw[k]);
VERIFY_IS_EQUAL(m,(Matrix<Scalar,1,2>(raw[0],raw[1])));
VERIFY((a==Array<Scalar,1,2>(raw[0],raw[1])).all());
for(int k=0; k<2; ++k) VERIFY(m2(k) == DenseIndex(raw[k]));
for(int k=0; k<2; ++k) VERIFY(a2(k) == DenseIndex(raw[k]));
for(int k=0; k<2; ++k) VERIFY(m3(k) == int(raw[k]));
for(int k=0; k<2; ++k) VERIFY(m4(k) == float(raw[k]));
}
{
Matrix<Scalar,1,1> m(raw), m1(raw[0]), m2( (DenseIndex(raw[0])) ), m3( (int(raw[0])) );
Array<Scalar,1,1> a(raw), a1(raw[0]), a2( (DenseIndex(raw[0])) );
VERIFY(m(0) == raw[0]);
VERIFY(a(0) == raw[0]);
VERIFY(m1(0) == raw[0]);
VERIFY(a1(0) == raw[0]);
VERIFY(m2(0) == DenseIndex(raw[0]));
VERIFY(a2(0) == DenseIndex(raw[0]));
VERIFY(m3(0) == int(raw[0]));
VERIFY_IS_EQUAL(m,(Matrix<Scalar,1,1>(raw[0])));
VERIFY((a==Array<Scalar,1,1>(raw[0])).all());
}
@@ -233,9 +256,10 @@ void test_basicstuff()
}
CALL_SUBTEST_1(fixedSizeMatrixConstruction<unsigned char>());
CALL_SUBTEST_1(fixedSizeMatrixConstruction<double>());
CALL_SUBTEST_1(fixedSizeMatrixConstruction<float>());
CALL_SUBTEST_1(fixedSizeMatrixConstruction<double>());
CALL_SUBTEST_1(fixedSizeMatrixConstruction<int>());
CALL_SUBTEST_1(fixedSizeMatrixConstruction<long int>());
CALL_SUBTEST_1(fixedSizeMatrixConstruction<std::ptrdiff_t>());
CALL_SUBTEST_2(casting());

51
test/ctorleak.cpp Normal file
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@@ -0,0 +1,51 @@
#include "main.h"
#include <exception> // std::exception
struct Foo
{
static unsigned object_count;
static unsigned object_limit;
int dummy;
Foo()
{
#ifdef EIGEN_EXCEPTIONS
// TODO: Is this the correct way to handle this?
if (Foo::object_count > Foo::object_limit) { throw Foo::Fail(); }
#endif
++Foo::object_count;
}
~Foo()
{
--Foo::object_count;
}
class Fail : public std::exception {};
};
unsigned Foo::object_count = 0;
unsigned Foo::object_limit = 0;
void test_ctorleak()
{
typedef DenseIndex Index;
Foo::object_count = 0;
for(int i = 0; i < g_repeat; i++) {
Index rows = internal::random<Index>(2,EIGEN_TEST_MAX_SIZE), cols = internal::random<Index>(2,EIGEN_TEST_MAX_SIZE);
Foo::object_limit = internal::random(0, rows*cols - 2);
#ifdef EIGEN_EXCEPTIONS
try
{
#endif
Matrix<Foo, Dynamic, Dynamic> m(rows, cols);
#ifdef EIGEN_EXCEPTIONS
VERIFY(false); // not reached if exceptions are enabled
}
catch (const Foo::Fail&) { /* ignore */ }
#endif
}
VERIFY_IS_EQUAL(static_cast<unsigned>(0), Foo::object_count);
}

33
test/dynalloc.cpp
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@@ -55,7 +55,7 @@ void check_aligned_new()
void check_aligned_stack_alloc()
{
for(int i = 1; i < 1000; i++)
for(int i = 1; i < 400; i++)
{
ei_declare_aligned_stack_constructed_variable(float,p,i,0);
VERIFY(size_t(p)%ALIGNMENT==0);
@@ -93,6 +93,32 @@ template<typename T> void check_dynaligned()
}
}
template<typename T> void check_custom_new_delete()
{
{
T* t = new T;
delete t;
}
{
std::size_t N = internal::random<std::size_t>(1,10);
T* t = new T[N];
delete[] t;
}
#ifdef EIGEN_ALIGN
{
T* t = static_cast<T *>((T::operator new)(sizeof(T)));
(T::operator delete)(t, sizeof(T));
}
{
T* t = static_cast<T *>((T::operator new)(sizeof(T)));
(T::operator delete)(t);
}
#endif
}
void test_dynalloc()
{
// low level dynamic memory allocation
@@ -109,6 +135,11 @@ void test_dynalloc()
CALL_SUBTEST(check_dynaligned<Vector4d>() );
CALL_SUBTEST(check_dynaligned<Vector4i>() );
CALL_SUBTEST(check_dynaligned<Vector8f>() );
CALL_SUBTEST( check_custom_new_delete<Vector4f>() );
CALL_SUBTEST( check_custom_new_delete<Vector2f>() );
CALL_SUBTEST( check_custom_new_delete<Matrix4f>() );
CALL_SUBTEST( check_custom_new_delete<MatrixXi>() );
}
// check static allocation, who knows ?

43
test/eigensolver_selfadjoint.cpp
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@@ -29,7 +29,21 @@ template<typename MatrixType> void selfadjointeigensolver(const MatrixType& m)
MatrixType a = MatrixType::Random(rows,cols);
MatrixType a1 = MatrixType::Random(rows,cols);
MatrixType symmA = a.adjoint() * a + a1.adjoint() * a1;
MatrixType symmC = symmA;
// randomly nullify some rows/columns
{
Index count = 1;//internal::random<Index>(-cols,cols);
for(Index k=0; k<count; ++k)
{
Index i = internal::random<Index>(0,cols-1);
symmA.row(i).setZero();
symmA.col(i).setZero();
}
}
symmA.template triangularView<StrictlyUpper>().setZero();
symmC.template triangularView<StrictlyUpper>().setZero();
MatrixType b = MatrixType::Random(rows,cols);
MatrixType b1 = MatrixType::Random(rows,cols);
@@ -40,7 +54,7 @@ template<typename MatrixType> void selfadjointeigensolver(const MatrixType& m)
SelfAdjointEigenSolver<MatrixType> eiDirect;
eiDirect.computeDirect(symmA);
// generalized eigen pb
GeneralizedSelfAdjointEigenSolver<MatrixType> eiSymmGen(symmA, symmB);
GeneralizedSelfAdjointEigenSolver<MatrixType> eiSymmGen(symmC, symmB);
VERIFY_IS_EQUAL(eiSymm.info(), Success);
VERIFY((symmA.template selfadjointView<Lower>() * eiSymm.eigenvectors()).isApprox(
@@ -57,27 +71,28 @@ template<typename MatrixType> void selfadjointeigensolver(const MatrixType& m)
VERIFY_IS_APPROX(eiSymm.eigenvalues(), eiSymmNoEivecs.eigenvalues());
// generalized eigen problem Ax = lBx
eiSymmGen.compute(symmA, symmB,Ax_lBx);
eiSymmGen.compute(symmC, symmB,Ax_lBx);
VERIFY_IS_EQUAL(eiSymmGen.info(), Success);
VERIFY((symmA.template selfadjointView<Lower>() * eiSymmGen.eigenvectors()).isApprox(
VERIFY((symmC.template selfadjointView<Lower>() * eiSymmGen.eigenvectors()).isApprox(
symmB.template selfadjointView<Lower>() * (eiSymmGen.eigenvectors() * eiSymmGen.eigenvalues().asDiagonal()), largerEps));
// generalized eigen problem BAx = lx
eiSymmGen.compute(symmA, symmB,BAx_lx);
eiSymmGen.compute(symmC, symmB,BAx_lx);
VERIFY_IS_EQUAL(eiSymmGen.info(), Success);
VERIFY((symmB.template selfadjointView<Lower>() * (symmA.template selfadjointView<Lower>() * eiSymmGen.eigenvectors())).isApprox(
VERIFY((symmB.template selfadjointView<Lower>() * (symmC.template selfadjointView<Lower>() * eiSymmGen.eigenvectors())).isApprox(
(eiSymmGen.eigenvectors() * eiSymmGen.eigenvalues().asDiagonal()), largerEps));
// generalized eigen problem ABx = lx
eiSymmGen.compute(symmA, symmB,ABx_lx);
eiSymmGen.compute(symmC, symmB,ABx_lx);
VERIFY_IS_EQUAL(eiSymmGen.info(), Success);
VERIFY((symmA.template selfadjointView<Lower>() * (symmB.template selfadjointView<Lower>() * eiSymmGen.eigenvectors())).isApprox(
VERIFY((symmC.template selfadjointView<Lower>() * (symmB.template selfadjointView<Lower>() * eiSymmGen.eigenvectors())).isApprox(
(eiSymmGen.eigenvectors() * eiSymmGen.eigenvalues().asDiagonal()), largerEps));
eiSymm.compute(symmC);
MatrixType sqrtSymmA = eiSymm.operatorSqrt();
VERIFY_IS_APPROX(MatrixType(symmA.template selfadjointView<Lower>()), sqrtSymmA*sqrtSymmA);
VERIFY_IS_APPROX(sqrtSymmA, symmA.template selfadjointView<Lower>()*eiSymm.operatorInverseSqrt());
VERIFY_IS_APPROX(MatrixType(symmC.template selfadjointView<Lower>()), sqrtSymmA*sqrtSymmA);
VERIFY_IS_APPROX(sqrtSymmA, symmC.template selfadjointView<Lower>()*eiSymm.operatorInverseSqrt());
MatrixType id = MatrixType::Identity(rows, cols);
VERIFY_IS_APPROX(id.template selfadjointView<Lower>().operatorNorm(), RealScalar(1));
@@ -95,9 +110,9 @@ template<typename MatrixType> void selfadjointeigensolver(const MatrixType& m)
VERIFY_RAISES_ASSERT(eiSymmUninitialized.operatorInverseSqrt());
// test Tridiagonalization's methods
Tridiagonalization<MatrixType> tridiag(symmA);
Tridiagonalization<MatrixType> tridiag(symmC);
// FIXME tridiag.matrixQ().adjoint() does not work
VERIFY_IS_APPROX(MatrixType(symmA.template selfadjointView<Lower>()), tridiag.matrixQ() * tridiag.matrixT().eval() * MatrixType(tridiag.matrixQ()).adjoint());
VERIFY_IS_APPROX(MatrixType(symmC.template selfadjointView<Lower>()), tridiag.matrixQ() * tridiag.matrixT().eval() * MatrixType(tridiag.matrixQ()).adjoint());
// Test computation of eigenvalues from tridiagonal matrix
if(rows > 1)
@@ -111,8 +126,8 @@ template<typename MatrixType> void selfadjointeigensolver(const MatrixType& m)
if (rows > 1)
{
// Test matrix with NaN
symmA(0,0) = std::numeric_limits<typename MatrixType::RealScalar>::quiet_NaN();
SelfAdjointEigenSolver<MatrixType> eiSymmNaN(symmA);
symmC(0,0) = std::numeric_limits<typename MatrixType::RealScalar>::quiet_NaN();
SelfAdjointEigenSolver<MatrixType> eiSymmNaN(symmC);
VERIFY_IS_EQUAL(eiSymmNaN.info(), NoConvergence);
}
}
@@ -122,8 +137,10 @@ void test_eigensolver_selfadjoint()
int s = 0;
for(int i = 0; i < g_repeat; i++) {
// very important to test 3x3 and 2x2 matrices since we provide special paths for them
CALL_SUBTEST_1( selfadjointeigensolver(Matrix2f()) );
CALL_SUBTEST_1( selfadjointeigensolver(Matrix2d()) );
CALL_SUBTEST_1( selfadjointeigensolver(Matrix3f()) );
CALL_SUBTEST_1( selfadjointeigensolver(Matrix3d()) );
CALL_SUBTEST_2( selfadjointeigensolver(Matrix4d()) );
s = internal::random<int>(1,EIGEN_TEST_MAX_SIZE/4);
CALL_SUBTEST_3( selfadjointeigensolver(MatrixXf(s,s)) );

20
test/main.h
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@@ -79,6 +79,10 @@ namespace Eigen
#define EIGEN_DEFAULT_IO_FORMAT IOFormat(4, 0, " ", "\n", "", "", "", "")
#if (defined(_CPPUNWIND) || defined(__EXCEPTIONS)) && !defined(__CUDA_ARCH__)
#define EIGEN_EXCEPTIONS
#endif
#ifndef EIGEN_NO_ASSERTION_CHECKING
namespace Eigen
@@ -120,13 +124,14 @@ namespace Eigen
if(report_on_cerr_on_assert_failure) \
std::cerr << #a << " " __FILE__ << "(" << __LINE__ << ")\n"; \
Eigen::no_more_assert = true; \
throw Eigen::eigen_assert_exception(); \
EIGEN_THROW_X(Eigen::eigen_assert_exception()); \
} \
else if (Eigen::internal::push_assert) \
{ \
eigen_assert_list.push_back(std::string(EI_PP_MAKE_STRING(__FILE__) " (" EI_PP_MAKE_STRING(__LINE__) ") : " #a) ); \
}
#ifdef EIGEN_EXCEPTIONS
#define VERIFY_RAISES_ASSERT(a) \
{ \
Eigen::no_more_assert = false; \
@@ -145,6 +150,7 @@ namespace Eigen
Eigen::report_on_cerr_on_assert_failure = true; \
Eigen::internal::push_assert = false; \
}
#endif //EIGEN_EXCEPTIONS
#elif !defined(__CUDACC__) // EIGEN_DEBUG_ASSERTS
// see bug 89. The copy_bool here is working around a bug in gcc <= 4.3
@@ -155,9 +161,10 @@ namespace Eigen
if(report_on_cerr_on_assert_failure) \
eigen_plain_assert(a); \
else \
throw Eigen::eigen_assert_exception(); \
EIGEN_THROW_X(Eigen::eigen_assert_exception()); \
}
#define VERIFY_RAISES_ASSERT(a) { \
#ifdef EIGEN_EXCEPTIONS
#define VERIFY_RAISES_ASSERT(a) { \
Eigen::no_more_assert = false; \
Eigen::report_on_cerr_on_assert_failure = false; \
try { \
@@ -167,9 +174,14 @@ namespace Eigen
catch (Eigen::eigen_assert_exception&) { VERIFY(true); } \
Eigen::report_on_cerr_on_assert_failure = true; \
}
#endif //EIGEN_EXCEPTIONS
#endif // EIGEN_DEBUG_ASSERTS
#ifndef VERIFY_RAISES_ASSERT
#define VERIFY_RAISES_ASSERT(a) \
std::cout << "Can't VERIFY_RAISES_ASSERT( " #a " ) with exceptions disabled\n";
#endif
#if !defined(__CUDACC__)
#define EIGEN_USE_CUSTOM_ASSERT
#endif

41
test/simplicial_cholesky.cpp
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@@ -11,26 +11,31 @@
template<typename T> void test_simplicial_cholesky_T()
{
SimplicialCholesky<SparseMatrix<T>, Lower> chol_colmajor_lower;
SimplicialCholesky<SparseMatrix<T>, Upper> chol_colmajor_upper;
SimplicialLLT<SparseMatrix<T>, Lower> llt_colmajor_lower;
SimplicialLDLT<SparseMatrix<T>, Upper> llt_colmajor_upper;
SimplicialLDLT<SparseMatrix<T>, Lower> ldlt_colmajor_lower;
SimplicialLDLT<SparseMatrix<T>, Upper> ldlt_colmajor_upper;
SimplicialCholesky<SparseMatrix<T>, Lower> chol_colmajor_lower_amd;
SimplicialCholesky<SparseMatrix<T>, Upper> chol_colmajor_upper_amd;
SimplicialLLT<SparseMatrix<T>, Lower> llt_colmajor_lower_amd;
SimplicialLLT<SparseMatrix<T>, Upper> llt_colmajor_upper_amd;
SimplicialLDLT<SparseMatrix<T>, Lower> ldlt_colmajor_lower_amd;
SimplicialLDLT<SparseMatrix<T>, Upper> ldlt_colmajor_upper_amd;
SimplicialLDLT<SparseMatrix<T>, Lower, NaturalOrdering<int> > ldlt_colmajor_lower_nat;
SimplicialLDLT<SparseMatrix<T>, Upper, NaturalOrdering<int> > ldlt_colmajor_upper_nat;
check_sparse_spd_solving(chol_colmajor_lower);
check_sparse_spd_solving(chol_colmajor_upper);
check_sparse_spd_solving(llt_colmajor_lower);
check_sparse_spd_solving(llt_colmajor_upper);
check_sparse_spd_solving(ldlt_colmajor_lower);
check_sparse_spd_solving(ldlt_colmajor_upper);
check_sparse_spd_solving(chol_colmajor_lower_amd);
check_sparse_spd_solving(chol_colmajor_upper_amd);
check_sparse_spd_solving(llt_colmajor_lower_amd);
check_sparse_spd_solving(llt_colmajor_upper_amd);
check_sparse_spd_solving(ldlt_colmajor_lower_amd);
check_sparse_spd_solving(ldlt_colmajor_upper_amd);
check_sparse_spd_determinant(chol_colmajor_lower);
check_sparse_spd_determinant(chol_colmajor_upper);
check_sparse_spd_determinant(llt_colmajor_lower);
check_sparse_spd_determinant(llt_colmajor_upper);
check_sparse_spd_determinant(ldlt_colmajor_lower);
check_sparse_spd_determinant(ldlt_colmajor_upper);
check_sparse_spd_determinant(chol_colmajor_lower_amd);
check_sparse_spd_determinant(chol_colmajor_upper_amd);
check_sparse_spd_determinant(llt_colmajor_lower_amd);
check_sparse_spd_determinant(llt_colmajor_upper_amd);
check_sparse_spd_determinant(ldlt_colmajor_lower_amd);
check_sparse_spd_determinant(ldlt_colmajor_upper_amd);
check_sparse_spd_solving(ldlt_colmajor_lower_nat);
check_sparse_spd_solving(ldlt_colmajor_upper_nat);
}
void test_simplicial_cholesky()

2
test/sparseqr.cpp
View File

@@ -54,6 +54,8 @@ template<typename Scalar> void test_sparseqr_scalar()
b = dA * DenseVector::Random(A.cols());
solver.compute(A);
if(internal::random<float>(0,1)>0.5)
solver.factorize(A); // this checks that calling analyzePattern is not needed if the pattern do not change.
if (solver.info() != Success)
{
std::cerr << "sparse QR factorization failed\n";