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Enable and fix -Wdouble-conversion warnings

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This commit is contained in:
Christoph Hertzberg 2016-05-05 13:35:45 +02:00
parent 62b710072e
commit dacb469bc9
34 changed files with 86 additions and 80 deletions
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6
CMakeLists.txt
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@ -120,7 +120,7 @@ endmacro(ei_add_cxx_compiler_flag)
if(NOT MSVC)
# We assume that other compilers are partly compatible with GNUCC
# clang outputs some warnings for unknwon flags that are not caught by check_cxx_compiler_flag
# clang outputs some warnings for unknown flags that are not caught by check_cxx_compiler_flag
# adding -Werror turns such warnings into errors
check_cxx_compiler_flag("-Werror" COMPILER_SUPPORT_WERROR)
if(COMPILER_SUPPORT_WERROR)
@ -143,6 +143,8 @@ if(NOT MSVC)
ei_add_cxx_compiler_flag("-Wshorten-64-to-32")
ei_add_cxx_compiler_flag("-Wenum-conversion")
ei_add_cxx_compiler_flag("-Wc++11-extensions")
ei_add_cxx_compiler_flag("-Wdouble-promotion")
# ei_add_cxx_compiler_flag("-Wconversion")
# -Wshadow is insanely too strict with gcc, hopefully it will become usable with gcc 6
# if(NOT CMAKE_COMPILER_IS_GNUCXX OR (CMAKE_CXX_COMPILER_VERSION VERSION_GREATER "5.0.0"))
@ -158,7 +160,7 @@ if(NOT MSVC)
ei_add_cxx_compiler_flag("-fno-common")
ei_add_cxx_compiler_flag("-fstrict-aliasing")
ei_add_cxx_compiler_flag("-wd981") # disable ICC's "operands are evaluated in unspecified order" remark
ei_add_cxx_compiler_flag("-wd2304") # disbale ICC's "warning #2304: non-explicit constructor with single argument may cause implicit type conversion" produced by -Wnon-virtual-dtor
ei_add_cxx_compiler_flag("-wd2304") # disable ICC's "warning #2304: non-explicit constructor with single argument may cause implicit type conversion" produced by -Wnon-virtual-dtor
# The -ansi flag must be added last, otherwise it is also used as a linker flag by check_cxx_compiler_flag making it fails

2
Eigen/src/Core/MathFunctions.h
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@ -1192,7 +1192,7 @@ double tanh(const double &x) { return ::tanh(x); }
template <typename T>
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE
T fmod(const T& a, const T& b) {
EIGEN_USING_STD_MATH(floor);
EIGEN_USING_STD_MATH(fmod);
return fmod(a, b);
}

4
Eigen/src/Core/functors/UnaryFunctors.h
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@ -880,9 +880,9 @@ struct scalar_sign_op<Scalar,true> {
{
typedef typename NumTraits<Scalar>::Real real_type;
real_type aa = numext::abs(a);
if (aa==0)
if (aa==real_type(0))
return Scalar(0);
aa = 1./aa;
aa = real_type(1)/aa;
return Scalar(real(a)*aa, imag(a)*aa );
}
//TODO

10
Eigen/src/Geometry/Rotation2D.h
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@ -82,15 +82,15 @@ public:
/** \returns the rotation angle in [0,2pi] */
inline Scalar smallestPositiveAngle() const {
Scalar tmp = fmod(m_angle,Scalar(2)*EIGEN_PI);
return tmp<Scalar(0) ? tmp + Scalar(2)*EIGEN_PI : tmp;
Scalar tmp = numext::fmod(m_angle,Scalar(2*EIGEN_PI));
return tmp<Scalar(0) ? tmp + Scalar(2*EIGEN_PI) : tmp;
}
/** \returns the rotation angle in [-pi,pi] */
inline Scalar smallestAngle() const {
Scalar tmp = fmod(m_angle,Scalar(2)*EIGEN_PI);
if(tmp>Scalar(EIGEN_PI)) tmp -= Scalar(2)*Scalar(EIGEN_PI);
else if(tmp<-Scalar(EIGEN_PI)) tmp += Scalar(2)*Scalar(EIGEN_PI);
Scalar tmp = numext::fmod(m_angle,Scalar(2*EIGEN_PI));
if(tmp>Scalar(EIGEN_PI)) tmp -= Scalar(2*EIGEN_PI);
else if(tmp<-Scalar(EIGEN_PI)) tmp += Scalar(2*EIGEN_PI);
return tmp;
}

12
Eigen/src/SVD/BDCSVD.h
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@ -765,14 +765,14 @@ void BDCSVD<MatrixType>::computeSingVals(const ArrayRef& col0, const ArrayRef& d
RealScalar muPrev, muCur;
if (shift == left)
{
muPrev = (right - left) * 0.1;
muPrev = (right - left) * RealScalar(0.1);
if (k == actual_n-1) muCur = right - left;
else muCur = (right - left) * 0.5;
else muCur = (right - left) * RealScalar(0.5);
}
else
{
muPrev = -(right - left) * 0.1;
muCur = -(right - left) * 0.5;
muPrev = -(right - left) * RealScalar(0.1);
muCur = -(right - left) * RealScalar(0.5);
}
RealScalar fPrev = secularEq(muPrev, col0, diag, perm, diagShifted, shift);
@ -820,11 +820,11 @@ void BDCSVD<MatrixType>::computeSingVals(const ArrayRef& col0, const ArrayRef& d
leftShifted = (std::numeric_limits<RealScalar>::min)();
// I don't understand why the case k==0 would be special there:
// if (k == 0) rightShifted = right - left; else
rightShifted = (k==actual_n-1) ? right : ((right - left) * 0.6); // theoretically we can take 0.5, but let's be safe
rightShifted = (k==actual_n-1) ? right : ((right - left) * RealScalar(0.6)); // theoretically we can take 0.5, but let's be safe
}
else
{
leftShifted = -(right - left) * 0.6;
leftShifted = -(right - left) * RealScalar(0.6);
rightShifted = -(std::numeric_limits<RealScalar>::min)();
}

2
blas/single.cpp
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@ -19,4 +19,4 @@
#include "level3_impl.h"
float BLASFUNC(sdsdot)(int* n, float* alpha, float* x, int* incx, float* y, int* incy)
{ return *alpha + BLASFUNC(dsdot)(n, x, incx, y, incy); }
{ return double(*alpha) + BLASFUNC(dsdot)(n, x, incx, y, incy); }

2
test/fastmath.cpp
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@ -49,7 +49,7 @@ void check_inf_nan(bool dryrun) {
VERIFY( !m.allFinite() );
VERIFY( m.hasNaN() );
}
m(4) /= 0.0;
m(4) /= T(0.0);
if(dryrun)
{
std::cout << "std::isfinite(" << m(4) << ") = "; check((std::isfinite)(m(4)),false); std::cout << " ; numext::isfinite = "; check((numext::isfinite)(m(4)), false); std::cout << "\n";

10
test/geo_hyperplane.cpp
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@ -97,9 +97,9 @@ template<typename Scalar> void lines()
Vector u = Vector::Random();
Vector v = Vector::Random();
Scalar a = internal::random<Scalar>();
while (abs(a-1) < 1e-4) a = internal::random<Scalar>();
while (u.norm() < 1e-4) u = Vector::Random();
while (v.norm() < 1e-4) v = Vector::Random();
while (abs(a-1) < Scalar(1e-4)) a = internal::random<Scalar>();
while (u.norm() < Scalar(1e-4)) u = Vector::Random();
while (v.norm() < Scalar(1e-4)) v = Vector::Random();
HLine line_u = HLine::Through(center + u, center + a*u);
HLine line_v = HLine::Through(center + v, center + a*v);
@ -111,14 +111,14 @@ template<typename Scalar> void lines()
Vector result = line_u.intersection(line_v);
// the lines should intersect at the point we called "center"
if(abs(a-1) > 1e-2 && abs(v.normalized().dot(u.normalized()))<0.9)
if(abs(a-1) > Scalar(1e-2) && abs(v.normalized().dot(u.normalized()))<Scalar(0.9))
VERIFY_IS_APPROX(result, center);
// check conversions between two types of lines
PLine pl(line_u); // gcc 3.3 will commit suicide if we don't name this variable
HLine line_u2(pl);
CoeffsType converted_coeffs = line_u2.coeffs();
if(line_u2.normal().dot(line_u.normal())<0.)
if(line_u2.normal().dot(line_u.normal())<Scalar(0))
converted_coeffs = -line_u2.coeffs();
VERIFY(line_u.coeffs().isApprox(converted_coeffs));
}

6
test/geo_quaternion.cpp
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@ -30,7 +30,7 @@ template<typename QuatType> void check_slerp(const QuatType& q0, const QuatType&
Scalar largeEps = test_precision<Scalar>();
Scalar theta_tot = AA(q1*q0.inverse()).angle();
if(theta_tot>EIGEN_PI)
if(theta_tot>Scalar(EIGEN_PI))
theta_tot = Scalar(2.*EIGEN_PI)-theta_tot;
for(Scalar t=0; t<=Scalar(1.001); t+=Scalar(0.1))
{
@ -115,8 +115,8 @@ template<typename Scalar, int Options> void quaternion(void)
// Do not execute the test if the rotation angle is almost zero, or
// the rotation axis and v1 are almost parallel.
if (abs(aa.angle()) > 5*test_precision<Scalar>()
&& (aa.axis() - v1.normalized()).norm() < 1.99
&& (aa.axis() + v1.normalized()).norm() < 1.99)
&& (aa.axis() - v1.normalized()).norm() < Scalar(1.99)
&& (aa.axis() + v1.normalized()).norm() < Scalar(1.99))
{
VERIFY_IS_NOT_APPROX(q1 * v1, Quaternionx(AngleAxisx(aa.angle()*2,aa.axis())) * v1);
}

2
test/geo_transformations.cpp
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@ -466,7 +466,7 @@ template<typename Scalar, int Mode, int Options> void transformations()
Scalar a2 = R0.slerp(Scalar(k+1)/Scalar(path_steps), R1).angle();
l += std::abs(a2-a1);
}
VERIFY(l<=EIGEN_PI*(Scalar(1)+NumTraits<Scalar>::epsilon()*Scalar(path_steps/2)));
VERIFY(l<=Scalar(EIGEN_PI)*(Scalar(1)+NumTraits<Scalar>::epsilon()*Scalar(path_steps/2)));
// check basic features
{

3
test/linearstructure.cpp
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@ -21,6 +21,7 @@ template<typename MatrixType> void linearStructure(const MatrixType& m)
*/
typedef typename MatrixType::Index Index;
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
Index rows = m.rows();
Index cols = m.cols();
@ -32,7 +33,7 @@ template<typename MatrixType> void linearStructure(const MatrixType& m)
m3(rows, cols);
Scalar s1 = internal::random<Scalar>();
while (abs(s1)<1e-3) s1 = internal::random<Scalar>();
while (abs(s1)<RealScalar(1e-3)) s1 = internal::random<Scalar>();
Index r = internal::random<Index>(0, rows-1),
c = internal::random<Index>(0, cols-1);

2
test/packetmath.cpp
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@ -387,7 +387,7 @@ template<typename Scalar> void packetmath_real()
data2[i] = internal::random<Scalar>(0,1) * std::pow(Scalar(10), internal::random<Scalar>(-6,6));
}
if(internal::random<float>(0,1)<0.1)
if(internal::random<float>(0,1)<0.1f)
data1[internal::random<int>(0, PacketSize)] = 0;
CHECK_CWISE1_IF(PacketTraits::HasSqrt, std::sqrt, internal::psqrt);
CHECK_CWISE1_IF(PacketTraits::HasLog, std::log, internal::plog);

2
test/qr_colpivoting.cpp
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@ -206,7 +206,7 @@ template<typename MatrixType> void qr_kahan_matrix()
RealScalar c = std::sqrt(1 - s*s);
for (Index i = 0; i < rows; ++i) {
m1(i, i) = pow(s, i);
m1.row(i).tail(rows - i - 1) = -pow(s, i) * c * MatrixType::Ones(1, rows - i - 1);
m1.row(i).tail(rows - i - 1) = -RealScalar(pow(s, i)) * c * MatrixType::Ones(1, rows - i - 1);
}
m1 = (m1 + m1.transpose()).eval();
ColPivHouseholderQR<MatrixType> qr(m1);

4
test/sparse_basic.cpp
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@ -232,11 +232,11 @@ template<typename SparseMatrixType> void sparse_basic(const SparseMatrixType& re
for (Index i=0; i<m2.rows(); ++i)
{
float x = internal::random<float>(0,1);
if (x<0.1)
if (x<0.1f)
{
// do nothing
}
else if (x<0.5)
else if (x<0.5f)
{
countFalseNonZero++;
m2.insert(i,j) = Scalar(0);

2
test/sparse_block.cpp
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@ -150,7 +150,7 @@ template<typename SparseMatrixType> void sparse_block(const SparseMatrixType& re
DenseMatrix refMat2 = DenseMatrix::Zero(rows, cols);
SparseMatrixType m2(rows, cols);
initSparse<Scalar>(density, refMat2, m2);
if(internal::random<float>(0,1)>0.5) m2.makeCompressed();
if(internal::random<float>(0,1)>0.5f) m2.makeCompressed();
Index j0 = internal::random<Index>(0,outer-2);
Index j1 = internal::random<Index>(0,outer-2);
Index n0 = internal::random<Index>(1,outer-(std::max)(j0,j1));

2
test/sparse_product.cpp
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@ -245,7 +245,7 @@ template<typename SparseMatrixType> void sparse_product()
for (int k=0; k<mS.outerSize(); ++k)
for (typename SparseMatrixType::InnerIterator it(mS,k); it; ++it)
if (it.index() == k)
it.valueRef() *= 0.5;
it.valueRef() *= Scalar(0.5);
VERIFY_IS_APPROX(refS.adjoint(), refS);
VERIFY_IS_APPROX(mS.adjoint(), mS);

2
test/sparse_vector.cpp
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@ -12,7 +12,7 @@
template<typename Scalar,typename StorageIndex> void sparse_vector(int rows, int cols)
{
double densityMat = (std::max)(8./(rows*cols), 0.01);
double densityVec = (std::max)(8./float(rows), 0.1);
double densityVec = (std::max)(8./(rows), 0.1);
typedef Matrix<Scalar,Dynamic,Dynamic> DenseMatrix;
typedef Matrix<Scalar,Dynamic,1> DenseVector;
typedef SparseVector<Scalar,0,StorageIndex> SparseVectorType;

2
test/sparseqr.cpp
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@ -54,7 +54,7 @@ template<typename Scalar> void test_sparseqr_scalar()
b = dA * DenseVector::Random(A.cols());
solver.compute(A);
if(internal::random<float>(0,1)>0.5)
if(internal::random<float>(0,1)>0.5f)
solver.factorize(A); // this checks that calling analyzePattern is not needed if the pattern do not change.
if (solver.info() != Success)
{

4
test/svd_common.h
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@ -141,14 +141,14 @@ void svd_least_square(const MatrixType& m, unsigned int computationOptions)
using std::abs;
SolutionType y(x);
y.row(k) = (1.+2*NumTraits<RealScalar>::epsilon())*x.row(k);
y.row(k) = (RealScalar(1)+2*NumTraits<RealScalar>::epsilon())*x.row(k);
RealScalar residual_y = (m*y-rhs).norm();
VERIFY( test_isMuchSmallerThan(abs(residual_y-residual), rhs_norm) || residual < residual_y );
if(internal::is_same<RealScalar,float>::value) ++g_test_level;
VERIFY( test_isApprox(residual_y,residual) || residual < residual_y );
if(internal::is_same<RealScalar,float>::value) --g_test_level;
y.row(k) = (1.-2*NumTraits<RealScalar>::epsilon())*x.row(k);
y.row(k) = (RealScalar(1)-2*NumTraits<RealScalar>::epsilon())*x.row(k);
residual_y = (m*y-rhs).norm();
VERIFY( test_isMuchSmallerThan(abs(residual_y-residual), rhs_norm) || residual < residual_y );
if(internal::is_same<RealScalar,float>::value) ++g_test_level;

2
test/svd_fill.h
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@ -54,7 +54,7 @@ void svd_fill_random(MatrixType &m, int Option = 0)
}
Matrix<Scalar,Dynamic,1> samples(7);
samples << 0, 5.60844e-313, -5.60844e-313, 4.94e-324, -4.94e-324, -1./NumTraits<RealScalar>::highest(), 1./NumTraits<RealScalar>::highest();
samples << 0, 5.60844e-313, -5.60844e-313, 4.94e-324, -4.94e-324, -RealScalar(1)/NumTraits<RealScalar>::highest(), RealScalar(1)/NumTraits<RealScalar>::highest();
if(Option==Symmetric)
{

4
test/triangular.cpp
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@ -65,7 +65,7 @@ template<typename MatrixType> void triangular_square(const MatrixType& m)
m1 = MatrixType::Random(rows, cols);
for (int i=0; i<rows; ++i)
while (numext::abs2(m1(i,i))<1e-1) m1(i,i) = internal::random<Scalar>();
while (numext::abs2(m1(i,i))<RealScalar(1e-1)) m1(i,i) = internal::random<Scalar>();
Transpose<MatrixType> trm4(m4);
// test back and forward subsitution with a vector as the rhs
@ -78,7 +78,7 @@ template<typename MatrixType> void triangular_square(const MatrixType& m)
m3 = m1.template triangularView<Lower>();
VERIFY(v2.isApprox(m3.conjugate() * (m1.conjugate().template triangularView<Lower>().solve(v2)), largerEps));
// test back and forward subsitution with a matrix as the rhs
// test back and forward substitution with a matrix as the rhs
m3 = m1.template triangularView<Upper>();
VERIFY(m2.isApprox(m3.adjoint() * (m1.adjoint().template triangularView<Lower>().solve(m2)), largerEps));
m3 = m1.template triangularView<Lower>();

4
unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h
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@ -210,9 +210,9 @@ struct matrix_exp_computeUV<MatrixType, float>
using std::pow;
const float l1norm = arg.cwiseAbs().colwise().sum().maxCoeff();
squarings = 0;
if (l1norm < 4.258730016922831e-001) {
if (l1norm < 4.258730016922831e-001f) {
matrix_exp_pade3(arg, U, V);
} else if (l1norm < 1.880152677804762e+000) {
} else if (l1norm < 1.880152677804762e+000f) {
matrix_exp_pade5(arg, U, V);
} else {
const float maxnorm = 3.925724783138660f;

3
unsupported/Eigen/src/MatrixFunctions/MatrixFunction.h
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@ -132,6 +132,7 @@ template <typename EivalsType, typename Cluster>
void matrix_function_partition_eigenvalues(const EivalsType& eivals, std::list<Cluster>& clusters)
{
typedef typename EivalsType::Index Index;
typedef typename EivalsType::RealScalar RealScalar;
for (Index i=0; i<eivals.rows(); ++i) {
// Find cluster containing i-th ei'val, adding a new cluster if necessary
typename std::list<Cluster>::iterator qi = matrix_function_find_cluster(i, clusters);
@ -145,7 +146,7 @@ void matrix_function_partition_eigenvalues(const EivalsType& eivals, std::list<C
// Look for other element to add to the set
for (Index j=i+1; j<eivals.rows(); ++j) {
if (abs(eivals(j) - eivals(i)) <= matrix_function_separation
if (abs(eivals(j) - eivals(i)) <= RealScalar(matrix_function_separation)
&& std::find(qi->begin(), qi->end(), j) == qi->end()) {
typename std::list<Cluster>::iterator qj = matrix_function_find_cluster(j, clusters);
if (qj == clusters.end()) {

5
unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h
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@ -37,6 +37,7 @@ template <typename MatrixType>
void matrix_log_compute_2x2(const MatrixType& A, MatrixType& result)
{
typedef typename MatrixType::Scalar Scalar;
typedef typename MatrixType::RealScalar RealScalar;
using std::abs;
using std::ceil;
using std::imag;
@ -54,14 +55,14 @@ void matrix_log_compute_2x2(const MatrixType& A, MatrixType& result)
{
result(0,1) = A(0,1) / A(0,0);
}
else if ((abs(A(0,0)) < 0.5*abs(A(1,1))) || (abs(A(0,0)) > 2*abs(A(1,1))))
else if ((abs(A(0,0)) < RealScalar(0.5)*abs(A(1,1))) || (abs(A(0,0)) > 2*abs(A(1,1))))
{
result(0,1) = A(0,1) * (logA11 - logA00) / y;
}
else
{
// computation in previous branch is inaccurate if A(1,1) \approx A(0,0)
int unwindingNumber = static_cast<int>(ceil((imag(logA11 - logA00) - EIGEN_PI) / (2*EIGEN_PI)));
int unwindingNumber = static_cast<int>(ceil((imag(logA11 - logA00) - RealScalar(EIGEN_PI)) / RealScalar(2*EIGEN_PI)));
result(0,1) = A(0,1) * (numext::log1p(y/A(0,0)) + Scalar(0,2*EIGEN_PI*unwindingNumber)) / y;
}
}

2
unsupported/Eigen/src/MatrixFunctions/MatrixPower.h
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@ -298,7 +298,7 @@ MatrixPowerAtomic<MatrixType>::computeSuperDiag(const ComplexScalar& curr, const
ComplexScalar logCurr = log(curr);
ComplexScalar logPrev = log(prev);
int unwindingNumber = ceil((numext::imag(logCurr - logPrev) - EIGEN_PI) / (2*EIGEN_PI));
int unwindingNumber = ceil((numext::imag(logCurr - logPrev) - RealScalar(EIGEN_PI)) / RealScalar(2*EIGEN_PI));
ComplexScalar w = numext::log1p((curr-prev)/prev)/RealScalar(2) + ComplexScalar(0, EIGEN_PI*unwindingNumber);
return RealScalar(2) * exp(RealScalar(0.5) * p * (logCurr + logPrev)) * sinh(p * w) / (curr - prev);
}

4
unsupported/Eigen/src/Splines/Spline.h
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@ -394,7 +394,7 @@ namespace Eigen
Matrix<Scalar,Order,Order> ndu(p+1,p+1);
double saved, temp;
Scalar saved, temp; // FIXME These were double instead of Scalar. Was there a reason for that?
ndu(0,0) = 1.0;
@ -433,7 +433,7 @@ namespace Eigen
// Compute the k-th derivative
for (DenseIndex k=1; k<=static_cast<DenseIndex>(n); ++k)
{
double d = 0.0;
Scalar d = 0.0;
DenseIndex rk,pk,j1,j2;
rk = r-k; pk = p-k;

2
unsupported/test/FFTW.cpp
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@ -54,7 +54,7 @@ complex<long double> promote(long double x) { return complex<long double>( x);
long double difpower=0;
size_t n = (min)( buf1.size(),buf2.size() );
for (size_t k=0;k<n;++k) {
totalpower += (numext::abs2( buf1[k] ) + numext::abs2(buf2[k]) )/2.;
totalpower += (numext::abs2( buf1[k] ) + numext::abs2(buf2[k]) )/2;
difpower += numext::abs2(buf1[k] - buf2[k]);
}
return sqrt(difpower/totalpower);

3
unsupported/test/autodiff.cpp
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@ -16,7 +16,8 @@ EIGEN_DONT_INLINE Scalar foo(const Scalar& x, const Scalar& y)
using namespace std;
// return x+std::sin(y);
EIGEN_ASM_COMMENT("mybegin");
return static_cast<Scalar>(x*2 - 1 + pow(1+x,2) + 2*sqrt(y*y+0) - 4 * sin(0+x) + 2 * cos(y+0) - exp(-0.5*x*x+0));
// pow(float, int) promotes to pow(double, double)
return x*2 - 1 + static_cast<Scalar>(pow(1+x,2)) + 2*sqrt(y*y+0) - 4 * sin(0+x) + 2 * cos(y+0) - exp(Scalar(-0.5)*x*x+0);
//return x+2*y*x;//x*2 -std::pow(x,2);//(2*y/x);// - y*2;
EIGEN_ASM_COMMENT("myend");
}

4
unsupported/test/cxx11_float16.cpp
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@ -34,8 +34,8 @@ void test_conversion()
float val1 = float(half(__half(0x3c00)));
float val2 = float(half(__half(0x3c01)));
float val3 = float(half(__half(0x3c02)));
VERIFY_IS_EQUAL(half(0.5 * (val1 + val2)).x, 0x3c00);
VERIFY_IS_EQUAL(half(0.5 * (val2 + val3)).x, 0x3c02);
VERIFY_IS_EQUAL(half(0.5f * (val1 + val2)).x, 0x3c00);
VERIFY_IS_EQUAL(half(0.5f * (val2 + val3)).x, 0x3c02);
// Conversion from int.
VERIFY_IS_EQUAL(half(-1).x, 0xbc00);

24
unsupported/test/cxx11_tensor_expr.cpp
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@ -112,13 +112,13 @@ static void test_3d()
Tensor<float, 3> mat1(2,3,7);
Tensor<float, 3, RowMajor> mat2(2,3,7);
float val = 1.0;
float val = 1.0f;
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 7; ++k) {
mat1(i,j,k) = val;
mat2(i,j,k) = val;
val += 1.0;
val += 1.0f;
}
}
}
@ -142,7 +142,7 @@ static void test_3d()
Tensor<float, 3, RowMajor> mat11(2,3,7);
mat11 = mat2 / 3.14f;
val = 1.0;
val = 1.0f;
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 7; ++k) {
@ -155,7 +155,7 @@ static void test_3d()
VERIFY_IS_APPROX(mat9(i,j,k), val + 3.14f);
VERIFY_IS_APPROX(mat10(i,j,k), val - 3.14f);
VERIFY_IS_APPROX(mat11(i,j,k), val / 3.14f);
val += 1.0;
val += 1.0f;
}
}
}
@ -167,25 +167,25 @@ static void test_constants()
Tensor<float, 3> mat2(2,3,7);
Tensor<float, 3> mat3(2,3,7);
float val = 1.0;
float val = 1.0f;
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 7; ++k) {
mat1(i,j,k) = val;
val += 1.0;
val += 1.0f;
}
}
}
mat2 = mat1.constant(3.14f);
mat3 = mat1.cwiseMax(7.3f).exp();
val = 1.0;
val = 1.0f;
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 7; ++k) {
VERIFY_IS_APPROX(mat2(i,j,k), 3.14f);
VERIFY_IS_APPROX(mat3(i,j,k), expf((std::max)(val, 7.3f)));
val += 1.0;
val += 1.0f;
}
}
}
@ -228,25 +228,25 @@ static void test_functors()
Tensor<float, 3> mat2(2,3,7);
Tensor<float, 3> mat3(2,3,7);
float val = 1.0;
float val = 1.0f;
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 7; ++k) {
mat1(i,j,k) = val;
val += 1.0;
val += 1.0f;
}
}
}
mat2 = mat1.inverse().unaryExpr(&asinf);
mat3 = mat1.unaryExpr(&tanhf);
val = 1.0;
val = 1.0f;
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 7; ++k) {
VERIFY_IS_APPROX(mat2(i,j,k), asinf(1.0f / mat1(i,j,k)));
VERIFY_IS_APPROX(mat3(i,j,k), tanhf(mat1(i,j,k)));
val += 1.0;
val += 1.0f;
}
}
}

8
unsupported/test/cxx11_tensor_fft.cpp
View File

@ -205,15 +205,15 @@ static void test_fft_real_input_energy() {
VERIFY_IS_EQUAL(output.dimension(i), input.dimension(i));
}
float energy_original = 0.0;
float energy_after_fft = 0.0;
RealScalar energy_original = 0.0;
RealScalar energy_after_fft = 0.0;
for (int i = 0; i < total_size; ++i) {
energy_original += pow(std::abs(input(i)), 2);
energy_original += numext::abs2(input(i));
}
for (int i = 0; i < total_size; ++i) {
energy_after_fft += pow(std::abs(output(i)), 2);
energy_after_fft += numext::abs2(output(i));
}
if(FFTDirection == FFT_FORWARD) {

16
unsupported/test/cxx11_tensor_fixed_size.cpp
View File

@ -188,13 +188,13 @@ static void test_3d()
// VERIFY_IS_EQUAL((mat1.dimension(1)), 3);
// VERIFY_IS_EQUAL((mat1.dimension(2)), 7);
float val = 0.0;
float val = 0.0f;
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 7; ++k) {
mat1(i,j,k) = val;
mat2(i,j,k) = val;
val += 1.0;
val += 1.0f;
}
}
}
@ -210,13 +210,13 @@ static void test_3d()
// VERIFY_IS_EQUAL((mat3.dimension(2)), 7);
val = 0.0;
val = 0.0f;
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 7; ++k) {
VERIFY_IS_APPROX(mat3(i,j,k), sqrtf(val));
VERIFY_IS_APPROX(mat4(i,j,k), sqrtf(val));
val += 1.0;
val += 1.0f;
}
}
}
@ -226,12 +226,12 @@ static void test_3d()
static void test_array()
{
TensorFixedSize<float, Sizes<2, 3, 7> > mat1;
float val = 0.0;
float val = 0.0f;
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 7; ++k) {
mat1(i,j,k) = val;
val += 1.0;
val += 1.0f;
}
}
}
@ -239,12 +239,12 @@ static void test_array()
TensorFixedSize<float, Sizes<2, 3, 7> > mat3;
mat3 = mat1.pow(3.5f);
val = 0.0;
val = 0.0f;
for (int i = 0; i < 2; ++i) {
for (int j = 0; j < 3; ++j) {
for (int k = 0; k < 7; ++k) {
VERIFY_IS_APPROX(mat3(i,j,k), powf(val, 3.5f));
val += 1.0;
val += 1.0f;
}
}
}

4
unsupported/test/matrix_function.cpp
View File

@ -113,8 +113,8 @@ void testMatrixLogarithm(const MatrixType& A)
MatrixType scaledA;
RealScalar maxImagPartOfSpectrum = A.eigenvalues().imag().cwiseAbs().maxCoeff();
if (maxImagPartOfSpectrum >= 0.9 * EIGEN_PI)
scaledA = A * 0.9 * EIGEN_PI / maxImagPartOfSpectrum;
if (maxImagPartOfSpectrum >= RealScalar(0.9 * EIGEN_PI))
scaledA = A * RealScalar(0.9 * EIGEN_PI) / maxImagPartOfSpectrum;
else
scaledA = A;

2
unsupported/test/matrix_power.cpp
View File

@ -24,7 +24,7 @@ void test2dRotation(double tol)
s = std::sin(angle);
B << c, s, -s, c;
C = Apow(std::ldexp(angle,1) / EIGEN_PI);
C = Apow(std::ldexp(angle,1) / T(EIGEN_PI));
std::cout << "test2dRotation: i = " << i << " error powerm = " << relerr(C,B) << '\n';
VERIFY(C.isApprox(B, tol));
}