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Fix compiler warnings in tests.

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This commit is contained in:
Rasmus Munk Larsen 2023-02-14 02:29:03 +00:00
parent 4a03409569
commit 07aaa62e6f
4 changed files with 44 additions and 41 deletions
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4
test/array_cwise.cpp
View File

@ -251,9 +251,9 @@ void mixed_pow_test() {
unary_pow_test<double, long long>();
// The following cases will test promoting a wider exponent type
// to a narrower base type. This should compile but generate a
// to a narrower base type. This should compile but would generate a
// deprecation warning:
unary_pow_test<float, double>();
// unary_pow_test<float, double>();
}
void int_pow_test() {

30
test/fastmath.cpp
View File

@ -43,11 +43,11 @@ void check_inf_nan(bool dryrun) {
}
else
{
if( (std::isfinite)(m(3))) g_test_level=1; VERIFY( !(numext::isfinite)(m(3)) ); g_test_level=0;
if( (std::isinf) (m(3))) g_test_level=1; VERIFY( !(numext::isinf)(m(3)) ); g_test_level=0;
if(!(std::isnan) (m(3))) g_test_level=1; VERIFY( (numext::isnan)(m(3)) ); g_test_level=0;
if( (std::isfinite)(m(3))) g_test_level=1; VERIFY( !m.allFinite() ); g_test_level=0;
if(!(std::isnan) (m(3))) g_test_level=1; VERIFY( m.hasNaN() ); g_test_level=0;
if( (std::isfinite)(m(3))) { g_test_level=1; VERIFY( !(numext::isfinite)(m(3)) ); g_test_level=0; }
if( (std::isinf) (m(3))) { g_test_level=1; VERIFY( !(numext::isinf)(m(3)) ); g_test_level=0; }
if(!(std::isnan) (m(3))) { g_test_level=1; VERIFY( (numext::isnan)(m(3)) ); g_test_level=0; }
if( (std::isfinite)(m(3))) { g_test_level=1; VERIFY( !m.allFinite() ); g_test_level=0; }
if(!(std::isnan) (m(3))) { g_test_level=1; VERIFY( m.hasNaN() ); g_test_level=0; }
}
T hidden_zero = (std::numeric_limits<T>::min)()*(std::numeric_limits<T>::min)();
m(4) /= hidden_zero;
@ -62,11 +62,11 @@ void check_inf_nan(bool dryrun) {
}
else
{
if( (std::isfinite)(m(3))) g_test_level=1; VERIFY( !(numext::isfinite)(m(4)) ); g_test_level=0;
if(!(std::isinf) (m(3))) g_test_level=1; VERIFY( (numext::isinf)(m(4)) ); g_test_level=0;
if( (std::isnan) (m(3))) g_test_level=1; VERIFY( !(numext::isnan)(m(4)) ); g_test_level=0;
if( (std::isfinite)(m(3))) g_test_level=1; VERIFY( !m.allFinite() ); g_test_level=0;
if(!(std::isnan) (m(3))) g_test_level=1; VERIFY( m.hasNaN() ); g_test_level=0;
if( (std::isfinite)(m(3))) { g_test_level=1; VERIFY( !(numext::isfinite)(m(4)) ); g_test_level=0; }
if(!(std::isinf) (m(3))) { g_test_level=1; VERIFY( (numext::isinf)(m(4)) ); g_test_level=0; }
if( (std::isnan) (m(3))) { g_test_level=1; VERIFY( !(numext::isnan)(m(4)) ); g_test_level=0; }
if( (std::isfinite)(m(3))) { g_test_level=1; VERIFY( !m.allFinite() ); g_test_level=0; }
if(!(std::isnan) (m(3))) { g_test_level=1; VERIFY( m.hasNaN() ); g_test_level=0; }
}
m(3) = 0;
if(dryrun)
@ -80,11 +80,11 @@ void check_inf_nan(bool dryrun) {
}
else
{
if(!(std::isfinite)(m(3))) g_test_level=1; VERIFY( (numext::isfinite)(m(3)) ); g_test_level=0;
if( (std::isinf) (m(3))) g_test_level=1; VERIFY( !(numext::isinf)(m(3)) ); g_test_level=0;
if( (std::isnan) (m(3))) g_test_level=1; VERIFY( !(numext::isnan)(m(3)) ); g_test_level=0;
if( (std::isfinite)(m(3))) g_test_level=1; VERIFY( !m.allFinite() ); g_test_level=0;
if( (std::isnan) (m(3))) g_test_level=1; VERIFY( !m.hasNaN() ); g_test_level=0;
if(!(std::isfinite)(m(3))) { g_test_level=1; VERIFY( (numext::isfinite)(m(3)) ); g_test_level=0; }
if( (std::isinf) (m(3))) { g_test_level=1; VERIFY( !(numext::isinf)(m(3)) ); g_test_level=0; }
if( (std::isnan) (m(3))) { g_test_level=1; VERIFY( !(numext::isnan)(m(3)) ); g_test_level=0; }
if( (std::isfinite)(m(3))) { g_test_level=1; VERIFY( !m.allFinite() ); g_test_level=0; }
if( (std::isnan) (m(3))) { g_test_level=1; VERIFY( !m.hasNaN() ); g_test_level=0; }
}
}

2
test/sparse_basic.cpp
View File

@ -164,7 +164,7 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
// test sort
if (inner > 1) {
bool StorageOrdersMatch = DenseMatrix::IsRowMajor == SparseMatrixType::IsRowMajor;
bool StorageOrdersMatch = int(DenseMatrix::IsRowMajor) == int(SparseMatrixType::IsRowMajor);
DenseMatrix m1(rows, cols);
m1.setZero();
SparseMatrixType m2(rows, cols);

49
unsupported/test/NNLS.cpp
View File

@ -12,10 +12,11 @@
#include "main.h"
#include <unsupported/Eigen/NNLS>
/// Check that 'x' solves the NNLS optimization problem `min ||A*x-b|| s.t. 0 <= x`.
/// The \p tolerance parameter is the absolute tolerance on the gradient, A'*(A*x-b).
template <typename MatrixType, typename VectorB, typename VectorX, typename Scalar>
static void verify_nnls_optimality(const MatrixType &A, const VectorB &b, const VectorX &x, const Scalar tolerance) {
void verify_nnls_optimality(const MatrixType &A, const VectorB &b, const VectorX &x, const Scalar tolerance) {
// The NNLS optimality conditions are:
//
// * 0 = A'*A*x - A'*b - lambda
@ -38,7 +39,7 @@ static void verify_nnls_optimality(const MatrixType &A, const VectorB &b, const
}
template <typename MatrixType, typename VectorB, typename VectorX>
static void test_nnls_known_solution(const MatrixType &A, const VectorB &b, const VectorX &x_expected) {
void test_nnls_known_solution(const MatrixType &A, const VectorB &b, const VectorX &x_expected) {
using Scalar = typename MatrixType::Scalar;
using std::sqrt;
@ -53,7 +54,7 @@ static void test_nnls_known_solution(const MatrixType &A, const VectorB &b, cons
}
template <typename MatrixType>
static void test_nnls_random_problem() {
void test_nnls_random_problem() {
//
// SETUP
//
@ -101,7 +102,7 @@ static void test_nnls_random_problem() {
verify_nnls_optimality(A, b, x, tolerance);
}
static void test_nnls_handles_zero_rhs() {
void test_nnls_handles_zero_rhs() {
//
// SETUP
//
@ -124,7 +125,7 @@ static void test_nnls_handles_zero_rhs() {
VERIFY_IS_EQUAL(x, VectorXd::Zero(cols));
}
static void test_nnls_handles_Mx0_matrix() {
void test_nnls_handles_Mx0_matrix() {
//
// SETUP
//
@ -146,7 +147,7 @@ static void test_nnls_handles_Mx0_matrix() {
VERIFY_IS_EQUAL(x.size(), 0);
}
static void test_nnls_handles_0x0_matrix() {
void test_nnls_handles_0x0_matrix() {
//
// SETUP
//
@ -167,7 +168,7 @@ static void test_nnls_handles_0x0_matrix() {
VERIFY_IS_EQUAL(x.size(), 0);
}
static void test_nnls_handles_dependent_columns() {
void test_nnls_handles_dependent_columns() {
//
// SETUP
//
@ -197,7 +198,7 @@ static void test_nnls_handles_dependent_columns() {
}
}
static void test_nnls_handles_wide_matrix() {
void test_nnls_handles_wide_matrix() {
//
// SETUP
//
@ -230,7 +231,7 @@ static void test_nnls_handles_wide_matrix() {
}
// 4x2 problem, unconstrained solution positive
static void test_nnls_known_1() {
void test_nnls_known_1() {
Matrix<double, 4, 2> A(4, 2);
Matrix<double, 4, 1> b(4);
Matrix<double, 2, 1> x(2);
@ -242,7 +243,7 @@ static void test_nnls_known_1() {
}
// 4x3 problem, unconstrained solution positive
static void test_nnls_known_2() {
void test_nnls_known_2() {
Matrix<double, 4, 3> A(4, 3);
Matrix<double, 4, 1> b(4);
Matrix<double, 3, 1> x(3);
@ -255,7 +256,7 @@ static void test_nnls_known_2() {
}
// Simple 4x4 problem, unconstrained solution non-negative
static void test_nnls_known_3() {
void test_nnls_known_3() {
Matrix<double, 4, 4> A(4, 4);
Matrix<double, 4, 1> b(4);
Matrix<double, 4, 1> x(4);
@ -268,7 +269,7 @@ static void test_nnls_known_3() {
}
// Simple 4x3 problem, unconstrained solution non-negative
static void test_nnls_known_4() {
void test_nnls_known_4() {
Matrix<double, 4, 3> A(4, 3);
Matrix<double, 4, 1> b(4);
Matrix<double, 3, 1> x(3);
@ -281,7 +282,7 @@ static void test_nnls_known_4() {
}
// Simple 4x3 problem, unconstrained solution indefinite
static void test_nnls_known_5() {
void test_nnls_known_5() {
Matrix<double, 4, 3> A(4, 3);
Matrix<double, 4, 1> b(4);
Matrix<double, 3, 1> x(3);
@ -294,7 +295,7 @@ static void test_nnls_known_5() {
test_nnls_known_solution(A, b, x);
}
static void test_nnls_small_reference_problems() {
void test_nnls_small_reference_problems() {
test_nnls_known_1();
test_nnls_known_2();
test_nnls_known_3();
@ -302,7 +303,7 @@ static void test_nnls_small_reference_problems() {
test_nnls_known_5();
}
static void test_nnls_with_half_precision() {
void test_nnls_with_half_precision() {
// The random matrix generation tools don't work with `half`,
// so here's a simpler setup mostly just to check that NNLS compiles & runs with custom scalar types.
@ -319,7 +320,7 @@ static void test_nnls_with_half_precision() {
verify_nnls_optimality(A, b, x, half(1e-1));
}
static void test_nnls_special_case_solves_in_zero_iterations() {
void test_nnls_special_case_solves_in_zero_iterations() {
// The particular NNLS algorithm that is implemented starts with all variables
// in the active set.
// This test builds a system where all constraints are active at the solution,
@ -346,7 +347,7 @@ static void test_nnls_special_case_solves_in_zero_iterations() {
VERIFY(nnls.iterations() == 0);
}
static void test_nnls_special_case_solves_in_n_iterations() {
void test_nnls_special_case_solves_in_n_iterations() {
// The particular NNLS algorithm that is implemented starts with all variables
// in the active set and then adds one variable to the inactive set each iteration.
// This test builds a system where all variables are inactive at the solution,
@ -370,7 +371,7 @@ static void test_nnls_special_case_solves_in_n_iterations() {
VERIFY(nnls.iterations() == n);
}
static void test_nnls_returns_NoConvergence_when_maxIterations_is_too_low() {
void test_nnls_returns_NoConvergence_when_maxIterations_is_too_low() {
// Using the special case that takes `n` iterations,
// from `test_nnls_special_case_solves_in_n_iterations`,
// we can set max iterations too low and that should cause the solve to fail.
@ -391,7 +392,7 @@ static void test_nnls_returns_NoConvergence_when_maxIterations_is_too_low() {
VERIFY(nnls.iterations() == max_iters);
}
static void test_nnls_default_maxIterations_is_twice_column_count() {
void test_nnls_default_maxIterations_is_twice_column_count() {
const Index cols = internal::random<Index>(1, EIGEN_TEST_MAX_SIZE);
const Index rows = internal::random<Index>(cols, EIGEN_TEST_MAX_SIZE);
const MatrixXd A = MatrixXd::Random(rows, cols);
@ -401,7 +402,7 @@ static void test_nnls_default_maxIterations_is_twice_column_count() {
VERIFY_IS_EQUAL(nnls.maxIterations(), 2 * cols);
}
static void test_nnls_does_not_allocate_during_solve() {
void test_nnls_does_not_allocate_during_solve() {
const Index cols = internal::random<Index>(1, EIGEN_TEST_MAX_SIZE);
const Index rows = internal::random<Index>(cols, EIGEN_TEST_MAX_SIZE);
const MatrixXd A = MatrixXd::Random(rows, cols);
@ -414,7 +415,7 @@ static void test_nnls_does_not_allocate_during_solve() {
internal::set_is_malloc_allowed(true);
}
static void test_nnls_repeated_calls_to_compute_and_solve() {
void test_nnls_repeated_calls_to_compute_and_solve() {
const Index cols2 = internal::random<Index>(1, EIGEN_TEST_MAX_SIZE);
const Index rows2 = internal::random<Index>(cols2, EIGEN_TEST_MAX_SIZE);
const MatrixXd A2 = MatrixXd::Random(rows2, cols2);
@ -449,8 +450,10 @@ EIGEN_DECLARE_TEST(NNLS) {
// Essential NNLS properties, across different types.
CALL_SUBTEST_2(test_nnls_random_problem<MatrixXf>());
CALL_SUBTEST_3(test_nnls_random_problem<MatrixXd>());
using MatFixed = Matrix<double, 12, 5>;
CALL_SUBTEST_4(test_nnls_random_problem<MatFixed>());
{
using MatFixed = Matrix<double, 12, 5>;
CALL_SUBTEST_4(test_nnls_random_problem<MatFixed>());
}
CALL_SUBTEST_5(test_nnls_with_half_precision());
// Robustness tests: