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-rw-r--r--unsupported/test/CMakeLists.txt16
-rw-r--r--unsupported/test/FFTW.cpp32
-rw-r--r--unsupported/test/autodiff.cpp32
-rw-r--r--unsupported/test/cxx11_float16.cpp247
-rw-r--r--unsupported/test/cxx11_tensor_dimension.cpp16
-rw-r--r--unsupported/test/cxx11_tensor_morphing.cpp48
-rw-r--r--unsupported/test/cxx11_tensor_of_float16_cuda.cu47
-rw-r--r--unsupported/test/cxx11_tensor_reduction.cpp29
-rw-r--r--unsupported/test/mpreal_support.cpp1
-rw-r--r--unsupported/test/special_functions.cpp345
10 files changed, 612 insertions, 201 deletions
diff --git a/unsupported/test/CMakeLists.txt b/unsupported/test/CMakeLists.txt
index c9a70d7a7..b29b694e7 100644
--- a/unsupported/test/CMakeLists.txt
+++ b/unsupported/test/CMakeLists.txt
@@ -109,6 +109,7 @@ ei_add_test(gmres)
ei_add_test(minres)
ei_add_test(levenberg_marquardt)
ei_add_test(kronecker_product)
+ei_add_test(special_functions)
# TODO: The following test names are prefixed with the cxx11 string, since historically
# the tests depended on c++11. This isn't the case anymore so we ought to rename them.
@@ -116,7 +117,6 @@ ei_add_test(kronecker_product)
# when using visual studio. We should make the check more strict to enable the tests for
# newer versions of MSVC.
if (NOT CMAKE_CXX_COMPILER_ID STREQUAL "MSVC")
-ei_add_test(cxx11_float16)
ei_add_test(cxx11_tensor_dimension)
ei_add_test(cxx11_tensor_map)
ei_add_test(cxx11_tensor_assign)
@@ -142,6 +142,9 @@ if(EIGEN_TEST_CXX11)
# older compiler that don't support cxx11.
set(CMAKE_CXX_STANDARD 11)
+ # Todo: remove the c++11 bits from this test to make it work with older compilers.
+ ei_add_test(cxx11_float16)
+
ei_add_test(cxx11_eventcount "-pthread" "${CMAKE_THREAD_LIBS_INIT}")
ei_add_test(cxx11_runqueue "-pthread" "${CMAKE_THREAD_LIBS_INIT}")
ei_add_test(cxx11_non_blocking_thread_pool "-pthread" "${CMAKE_THREAD_LIBS_INIT}")
@@ -191,10 +194,12 @@ if(CUDA_FOUND AND EIGEN_TEST_CUDA)
# Make sure to compile without the -pedantic, -Wundef, -Wnon-virtual-dtor
# and -fno-check-new flags since they trigger thousands of compilation warnings
# in the CUDA runtime
+ # Also remove -ansi that is incompatible with std=c++11.
string(REPLACE "-pedantic" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
string(REPLACE "-Wundef" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
string(REPLACE "-Wnon-virtual-dtor" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
string(REPLACE "-fno-check-new" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
+ string(REPLACE "-ansi" "" CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS}")
message(STATUS "Flags used to compile cuda code: " ${CMAKE_CXX_FLAGS})
@@ -210,7 +215,14 @@ if(CUDA_FOUND AND EIGEN_TEST_CUDA)
set(EIGEN_CUDA_RELAXED_CONSTEXPR "--relaxed-constexpr")
endif()
- set(CUDA_NVCC_FLAGS "-std=c++11 ${EIGEN_CUDA_RELAXED_CONSTEXPR} -arch compute_${EIGEN_CUDA_COMPUTE_ARCH} -Xcudafe \"--display_error_number\"")
+ if( (NOT EIGEN_TEST_CXX11) OR (CMAKE_VERSION VERSION_LESS 3.3))
+ set(EIGEN_CUDA_CXX11_FLAG "-std=c++11")
+ else()
+ # otherwise the flag has already been added because of the above set(CMAKE_CXX_STANDARD 11)
+ set(EIGEN_CUDA_CXX11_FLAG "")
+ endif()
+
+ set(CUDA_NVCC_FLAGS "${EIGEN_CUDA_CXX11_FLAG} ${EIGEN_CUDA_RELAXED_CONSTEXPR} -arch compute_${EIGEN_CUDA_COMPUTE_ARCH} -Xcudafe \"--display_error_number\" ${CUDA_NVCC_FLAGS}")
cuda_include_directories("${CMAKE_CURRENT_BINARY_DIR}" "${CUDA_TOOLKIT_ROOT_DIR}/include")
set(EIGEN_ADD_TEST_FILENAME_EXTENSION "cu")
diff --git a/unsupported/test/FFTW.cpp b/unsupported/test/FFTW.cpp
index 1dd6dc97d..8b7528fb7 100644
--- a/unsupported/test/FFTW.cpp
+++ b/unsupported/test/FFTW.cpp
@@ -18,11 +18,11 @@ using namespace Eigen;
template < typename T>
-complex<long double> promote(complex<T> x) { return complex<long double>(x.real(),x.imag()); }
+complex<long double> promote(complex<T> x) { return complex<long double>((long double)x.real(),(long double)x.imag()); }
-complex<long double> promote(float x) { return complex<long double>( x); }
-complex<long double> promote(double x) { return complex<long double>( x); }
-complex<long double> promote(long double x) { return complex<long double>( x); }
+complex<long double> promote(float x) { return complex<long double>((long double)x); }
+complex<long double> promote(double x) { return complex<long double>((long double)x); }
+complex<long double> promote(long double x) { return complex<long double>((long double)x); }
template <typename VT1,typename VT2>
@@ -33,7 +33,7 @@ complex<long double> promote(long double x) { return complex<long double>( x);
long double pi = acos((long double)-1 );
for (size_t k0=0;k0<(size_t)fftbuf.size();++k0) {
complex<long double> acc = 0;
- long double phinc = -2.*k0* pi / timebuf.size();
+ long double phinc = (long double)(-2.)*k0* pi / timebuf.size();
for (size_t k1=0;k1<(size_t)timebuf.size();++k1) {
acc += promote( timebuf[k1] ) * exp( complex<long double>(0,k1*phinc) );
}
@@ -54,8 +54,8 @@ 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;
- difpower += numext::abs2(buf1[k] - buf2[k]);
+ totalpower += (long double)((numext::abs2( buf1[k] ) + numext::abs2(buf2[k]) )/2);
+ difpower += (long double)(numext::abs2(buf1[k] - buf2[k]));
}
return sqrt(difpower/totalpower);
}
@@ -93,19 +93,19 @@ void test_scalar_generic(int nfft)
fft.SetFlag(fft.HalfSpectrum );
fft.fwd( freqBuf,tbuf);
VERIFY((size_t)freqBuf.size() == (size_t)( (nfft>>1)+1) );
- VERIFY( fft_rmse(freqBuf,tbuf) < test_precision<T>() );// gross check
+ VERIFY( T(fft_rmse(freqBuf,tbuf)) < test_precision<T>() );// gross check
fft.ClearFlag(fft.HalfSpectrum );
fft.fwd( freqBuf,tbuf);
VERIFY( (size_t)freqBuf.size() == (size_t)nfft);
- VERIFY( fft_rmse(freqBuf,tbuf) < test_precision<T>() );// gross check
+ VERIFY( T(fft_rmse(freqBuf,tbuf)) < test_precision<T>() );// gross check
if (nfft&1)
return; // odd FFTs get the wrong size inverse FFT
ScalarVector tbuf2;
fft.inv( tbuf2 , freqBuf);
- VERIFY( dif_rmse(tbuf,tbuf2) < test_precision<T>() );// gross check
+ VERIFY( T(dif_rmse(tbuf,tbuf2)) < test_precision<T>() );// gross check
// verify that the Unscaled flag takes effect
@@ -121,12 +121,12 @@ void test_scalar_generic(int nfft)
//for (size_t i=0;i<(size_t) tbuf.size();++i)
// cout << "freqBuf=" << freqBuf[i] << " in2=" << tbuf3[i] << " - in=" << tbuf[i] << " => " << (tbuf3[i] - tbuf[i] ) << endl;
- VERIFY( dif_rmse(tbuf,tbuf3) < test_precision<T>() );// gross check
+ VERIFY( T(dif_rmse(tbuf,tbuf3)) < test_precision<T>() );// gross check
// verify that ClearFlag works
fft.ClearFlag(fft.Unscaled);
fft.inv( tbuf2 , freqBuf);
- VERIFY( dif_rmse(tbuf,tbuf2) < test_precision<T>() );// gross check
+ VERIFY( T(dif_rmse(tbuf,tbuf2)) < test_precision<T>() );// gross check
}
template <typename T>
@@ -152,10 +152,10 @@ void test_complex_generic(int nfft)
inbuf[k]= Complex( (T)(rand()/(double)RAND_MAX - .5), (T)(rand()/(double)RAND_MAX - .5) );
fft.fwd( outbuf , inbuf);
- VERIFY( fft_rmse(outbuf,inbuf) < test_precision<T>() );// gross check
+ VERIFY( T(fft_rmse(outbuf,inbuf)) < test_precision<T>() );// gross check
fft.inv( buf3 , outbuf);
- VERIFY( dif_rmse(inbuf,buf3) < test_precision<T>() );// gross check
+ VERIFY( T(dif_rmse(inbuf,buf3)) < test_precision<T>() );// gross check
// verify that the Unscaled flag takes effect
ComplexVector buf4;
@@ -163,12 +163,12 @@ void test_complex_generic(int nfft)
fft.inv( buf4 , outbuf);
for (int k=0;k<nfft;++k)
buf4[k] *= T(1./nfft);
- VERIFY( dif_rmse(inbuf,buf4) < test_precision<T>() );// gross check
+ VERIFY( T(dif_rmse(inbuf,buf4)) < test_precision<T>() );// gross check
// verify that ClearFlag works
fft.ClearFlag(fft.Unscaled);
fft.inv( buf3 , outbuf);
- VERIFY( dif_rmse(inbuf,buf3) < test_precision<T>() );// gross check
+ VERIFY( T(dif_rmse(inbuf,buf3)) < test_precision<T>() );// gross check
}
template <typename T>
diff --git a/unsupported/test/autodiff.cpp b/unsupported/test/autodiff.cpp
index b59fd1c43..2da6dd8f3 100644
--- a/unsupported/test/autodiff.cpp
+++ b/unsupported/test/autodiff.cpp
@@ -205,6 +205,10 @@ void test_autodiff_hessian()
VERIFY_IS_APPROX(y.value().derivatives()(1), s4*std::cos(s1*s3+s2*s4));
VERIFY_IS_APPROX(y.derivatives()(0).derivatives(), -std::sin(s1*s3+s2*s4)*Vector2d(s3*s3,s4*s3));
VERIFY_IS_APPROX(y.derivatives()(1).derivatives(), -std::sin(s1*s3+s2*s4)*Vector2d(s3*s4,s4*s4));
+
+ ADD z = x(0)*x(1);
+ VERIFY_IS_APPROX(z.derivatives()(0).derivatives(), Vector2d(0,1));
+ VERIFY_IS_APPROX(z.derivatives()(1).derivatives(), Vector2d(1,0));
}
double bug_1222() {
@@ -234,6 +238,32 @@ double bug_1223() {
return t.value() + t2.value();
}
+// regression test for some compilation issues with specializations of ScalarBinaryOpTraits
+void bug_1260() {
+ Matrix4d A;
+ Vector4d v;
+ A*v;
+}
+
+// check a compilation issue with numext::max
+double bug_1261() {
+ typedef AutoDiffScalar<Matrix2d> AD;
+ typedef Matrix<AD,2,1> VectorAD;
+
+ VectorAD v;
+ const AD maxVal = v.maxCoeff();
+ const AD minVal = v.minCoeff();
+ return maxVal.value() + minVal.value();
+}
+
+double bug_1264() {
+ typedef AutoDiffScalar<Vector2d> AD;
+ const AD s;
+ const Matrix<AD, 3, 1> v1;
+ const Matrix<AD, 3, 1> v2 = (s + 3.0) * v1;
+ return v2(0).value();
+}
+
void test_autodiff()
{
for(int i = 0; i < g_repeat; i++) {
@@ -245,5 +275,7 @@ void test_autodiff()
bug_1222();
bug_1223();
+ bug_1260();
+ bug_1261();
}
diff --git a/unsupported/test/cxx11_float16.cpp b/unsupported/test/cxx11_float16.cpp
index e39a7f83c..f646c9750 100644
--- a/unsupported/test/cxx11_float16.cpp
+++ b/unsupported/test/cxx11_float16.cpp
@@ -8,194 +8,177 @@
#define EIGEN_TEST_NO_LONGDOUBLE
#define EIGEN_TEST_NO_COMPLEX
#define EIGEN_TEST_FUNC cxx11_float16
+#define EIGEN_DEFAULT_DENSE_INDEX_TYPE int
+#define EIGEN_USE_GPU
+
+// Make sure it's possible to forward declare Eigen::half
+//namespace Eigen {
+//struct half;
+//}
#include "main.h"
#include <Eigen/src/Core/arch/CUDA/Half.h>
-using Eigen::half;
-
void test_conversion()
{
// Conversion from float.
- VERIFY_IS_EQUAL(half(1.0f).x, 0x3c00);
- VERIFY_IS_EQUAL(half(0.5f).x, 0x3800);
- VERIFY_IS_EQUAL(half(0.33333f).x, 0x3555);
- VERIFY_IS_EQUAL(half(0.0f).x, 0x0000);
- VERIFY_IS_EQUAL(half(-0.0f).x, 0x8000);
- VERIFY_IS_EQUAL(half(65504.0f).x, 0x7bff);
- VERIFY_IS_EQUAL(half(65536.0f).x, 0x7c00); // Becomes infinity.
+ VERIFY_IS_EQUAL(Eigen::half(1.0f).x, 0x3c00);
+ VERIFY_IS_EQUAL(Eigen::half(0.5f).x, 0x3800);
+ VERIFY_IS_EQUAL(Eigen::half(0.33333f).x, 0x3555);
+ VERIFY_IS_EQUAL(Eigen::half(0.0f).x, 0x0000);
+ VERIFY_IS_EQUAL(Eigen::half(-0.0f).x, 0x8000);
+ VERIFY_IS_EQUAL(Eigen::half(65504.0f).x, 0x7bff);
+ VERIFY_IS_EQUAL(Eigen::half(65536.0f).x, 0x7c00); // Becomes infinity.
// Denormals.
- VERIFY_IS_EQUAL(half(-5.96046e-08f).x, 0x8001);
- VERIFY_IS_EQUAL(half(5.96046e-08f).x, 0x0001);
- VERIFY_IS_EQUAL(half(1.19209e-07f).x, 0x0002);
+ VERIFY_IS_EQUAL(Eigen::half(-5.96046e-08f).x, 0x8001);
+ VERIFY_IS_EQUAL(Eigen::half(5.96046e-08f).x, 0x0001);
+ VERIFY_IS_EQUAL(Eigen::half(1.19209e-07f).x, 0x0002);
// Verify round-to-nearest-even behavior.
- float val1 = float(half(__half(0x3c00)));
- float val2 = float(half(__half(0x3c01)));
- float val3 = float(half(__half(0x3c02)));
- VERIFY_IS_EQUAL(half(0.5f * (val1 + val2)).x, 0x3c00);
- VERIFY_IS_EQUAL(half(0.5f * (val2 + val3)).x, 0x3c02);
+ float val1 = float(Eigen::half(half_impl::__half{0x3c00}));
+ float val2 = float(Eigen::half(half_impl::__half{0x3c01}));
+ float val3 = float(Eigen::half(half_impl::__half{0x3c02}));
+ VERIFY_IS_EQUAL(Eigen::half(0.5f * (val1 + val2)).x, 0x3c00);
+ VERIFY_IS_EQUAL(Eigen::half(0.5f * (val2 + val3)).x, 0x3c02);
// Conversion from int.
- VERIFY_IS_EQUAL(half(-1).x, 0xbc00);
- VERIFY_IS_EQUAL(half(0).x, 0x0000);
- VERIFY_IS_EQUAL(half(1).x, 0x3c00);
- VERIFY_IS_EQUAL(half(2).x, 0x4000);
- VERIFY_IS_EQUAL(half(3).x, 0x4200);
+ VERIFY_IS_EQUAL(Eigen::half(-1).x, 0xbc00);
+ VERIFY_IS_EQUAL(Eigen::half(0).x, 0x0000);
+ VERIFY_IS_EQUAL(Eigen::half(1).x, 0x3c00);
+ VERIFY_IS_EQUAL(Eigen::half(2).x, 0x4000);
+ VERIFY_IS_EQUAL(Eigen::half(3).x, 0x4200);
// Conversion from bool.
- VERIFY_IS_EQUAL(half(false).x, 0x0000);
- VERIFY_IS_EQUAL(half(true).x, 0x3c00);
+ VERIFY_IS_EQUAL(Eigen::half(false).x, 0x0000);
+ VERIFY_IS_EQUAL(Eigen::half(true).x, 0x3c00);
// Conversion to float.
- VERIFY_IS_EQUAL(float(half(__half(0x0000))), 0.0f);
- VERIFY_IS_EQUAL(float(half(__half(0x3c00))), 1.0f);
+ VERIFY_IS_EQUAL(float(Eigen::half(half_impl::__half{0x0000})), 0.0f);
+ VERIFY_IS_EQUAL(float(Eigen::half(half_impl::__half{0x3c00})), 1.0f);
// Denormals.
- VERIFY_IS_APPROX(float(half(__half(0x8001))), -5.96046e-08f);
- VERIFY_IS_APPROX(float(half(__half(0x0001))), 5.96046e-08f);
- VERIFY_IS_APPROX(float(half(__half(0x0002))), 1.19209e-07f);
+ VERIFY_IS_APPROX(float(Eigen::half(half_impl::__half{0x8001})), -5.96046e-08f);
+ VERIFY_IS_APPROX(float(Eigen::half(half_impl::__half{0x0001})), 5.96046e-08f);
+ VERIFY_IS_APPROX(float(Eigen::half(half_impl::__half{0x0002})), 1.19209e-07f);
// NaNs and infinities.
- VERIFY(!(numext::isinf)(float(half(65504.0f)))); // Largest finite number.
- VERIFY(!(numext::isnan)(float(half(0.0f))));
- VERIFY((numext::isinf)(float(half(__half(0xfc00)))));
- VERIFY((numext::isnan)(float(half(__half(0xfc01)))));
- VERIFY((numext::isinf)(float(half(__half(0x7c00)))));
- VERIFY((numext::isnan)(float(half(__half(0x7c01)))));
-
-#if !EIGEN_COMP_MSVC
- // Visual Studio errors out on divisions by 0
- VERIFY((numext::isnan)(float(half(0.0 / 0.0))));
- VERIFY((numext::isinf)(float(half(1.0 / 0.0))));
- VERIFY((numext::isinf)(float(half(-1.0 / 0.0))));
-#endif
+ VERIFY(!(isinf)(float(Eigen::half(65504.0f)))); // Largest finite number.
+ VERIFY(!(isnan)(float(Eigen::half(0.0f))));
+ VERIFY((isinf)(float(Eigen::half(half_impl::__half{0xfc00}))));
+ VERIFY((isnan)(float(Eigen::half(half_impl::__half{0xfc01}))));
+ VERIFY((isinf)(float(Eigen::half(half_impl::__half{0x7c00}))));
+ VERIFY((isnan)(float(Eigen::half(half_impl::__half{0x7c01}))));
+ VERIFY((isnan)(float(Eigen::half(0.0 / 0.0))));
+ VERIFY((isinf)(float(Eigen::half(1.0 / 0.0))));
+ VERIFY((isinf)(float(Eigen::half(-1.0 / 0.0))));
// Exactly same checks as above, just directly on the half representation.
- VERIFY(!(numext::isinf)(half(__half(0x7bff))));
- VERIFY(!(numext::isnan)(half(__half(0x0000))));
- VERIFY((numext::isinf)(half(__half(0xfc00))));
- VERIFY((numext::isnan)(half(__half(0xfc01))));
- VERIFY((numext::isinf)(half(__half(0x7c00))));
- VERIFY((numext::isnan)(half(__half(0x7c01))));
-
-#if !EIGEN_COMP_MSVC
- // Visual Studio errors out on divisions by 0
- VERIFY((numext::isnan)(half(0.0 / 0.0)));
- VERIFY((numext::isinf)(half(1.0 / 0.0)));
- VERIFY((numext::isinf)(half(-1.0 / 0.0)));
-#endif
-}
-
-void test_numtraits()
-{
- std::cout << "expsilin = " << NumTraits<half>::epsilon() << std::endl;
- std::cout << "highest = " << NumTraits<half>::highest() << std::endl;
- std::cout << "lowest = " << NumTraits<half>::lowest() << std::endl;
- std::cout << "inifinty = " << NumTraits<half>::infinity() << std::endl;
- std::cout << "nan = " << NumTraits<half>::quiet_NaN() << std::endl;
-
+ VERIFY(!(numext::isinf)(Eigen::half(half_impl::__half{0x7bff})));
+ VERIFY(!(numext::isnan)(Eigen::half(half_impl::__half{0x0000})));
+ VERIFY((numext::isinf)(Eigen::half(half_impl::__half{0xfc00})));
+ VERIFY((numext::isnan)(Eigen::half(half_impl::__half{0xfc01})));
+ VERIFY((numext::isinf)(Eigen::half(half_impl::__half{0x7c00})));
+ VERIFY((numext::isnan)(Eigen::half(half_impl::__half{0x7c01})));
+ VERIFY((numext::isnan)(Eigen::half(0.0 / 0.0)));
+ VERIFY((numext::isinf)(Eigen::half(1.0 / 0.0)));
+ VERIFY((numext::isinf)(Eigen::half(-1.0 / 0.0)));
}
void test_arithmetic()
{
- VERIFY_IS_EQUAL(float(half(2) + half(2)), 4);
- VERIFY_IS_EQUAL(float(half(2) + half(-2)), 0);
- VERIFY_IS_APPROX(float(half(0.33333f) + half(0.66667f)), 1.0f);
- VERIFY_IS_EQUAL(float(half(2.0f) * half(-5.5f)), -11.0f);
- VERIFY_IS_APPROX(float(half(1.0f) / half(3.0f)), 0.33333f);
- VERIFY_IS_EQUAL(float(-half(4096.0f)), -4096.0f);
- VERIFY_IS_EQUAL(float(-half(-4096.0f)), 4096.0f);
+ VERIFY_IS_EQUAL(float(Eigen::half(2) + Eigen::half(2)), 4);
+ VERIFY_IS_EQUAL(float(Eigen::half(2) + Eigen::half(-2)), 0);
+ VERIFY_IS_APPROX(float(Eigen::half(0.33333f) + Eigen::half(0.66667f)), 1.0f);
+ VERIFY_IS_EQUAL(float(Eigen::half(2.0f) * Eigen::half(-5.5f)), -11.0f);
+ VERIFY_IS_APPROX(float(Eigen::half(1.0f) / Eigen::half(3.0f)), 0.33333f);
+ VERIFY_IS_EQUAL(float(-Eigen::half(4096.0f)), -4096.0f);
+ VERIFY_IS_EQUAL(float(-Eigen::half(-4096.0f)), 4096.0f);
}
void test_comparison()
{
- VERIFY(half(1.0f) > half(0.5f));
- VERIFY(half(0.5f) < half(1.0f));
- VERIFY(!(half(1.0f) < half(0.5f)));
- VERIFY(!(half(0.5f) > half(1.0f)));
+ VERIFY(Eigen::half(1.0f) > Eigen::half(0.5f));
+ VERIFY(Eigen::half(0.5f) < Eigen::half(1.0f));
+ VERIFY(!(Eigen::half(1.0f) < Eigen::half(0.5f)));
+ VERIFY(!(Eigen::half(0.5f) > Eigen::half(1.0f)));
- VERIFY(!(half(4.0f) > half(4.0f)));
- VERIFY(!(half(4.0f) < half(4.0f)));
+ VERIFY(!(Eigen::half(4.0f) > Eigen::half(4.0f)));
+ VERIFY(!(Eigen::half(4.0f) < Eigen::half(4.0f)));
- VERIFY(!(half(0.0f) < half(-0.0f)));
- VERIFY(!(half(-0.0f) < half(0.0f)));
- VERIFY(!(half(0.0f) > half(-0.0f)));
- VERIFY(!(half(-0.0f) > half(0.0f)));
+ VERIFY(!(Eigen::half(0.0f) < Eigen::half(-0.0f)));
+ VERIFY(!(Eigen::half(-0.0f) < Eigen::half(0.0f)));
+ VERIFY(!(Eigen::half(0.0f) > Eigen::half(-0.0f)));
+ VERIFY(!(Eigen::half(-0.0f) > Eigen::half(0.0f)));
- VERIFY(half(0.2f) > half(-1.0f));
- VERIFY(half(-1.0f) < half(0.2f));
- VERIFY(half(-16.0f) < half(-15.0f));
+ VERIFY(Eigen::half(0.2f) > Eigen::half(-1.0f));
+ VERIFY(Eigen::half(-1.0f) < Eigen::half(0.2f));
+ VERIFY(Eigen::half(-16.0f) < Eigen::half(-15.0f));
- VERIFY(half(1.0f) == half(1.0f));
- VERIFY(half(1.0f) != half(2.0f));
+ VERIFY(Eigen::half(1.0f) == Eigen::half(1.0f));
+ VERIFY(Eigen::half(1.0f) != Eigen::half(2.0f));
// Comparisons with NaNs and infinities.
-#if !EIGEN_COMP_MSVC
- // Visual Studio errors out on divisions by 0
- VERIFY(!(half(0.0 / 0.0) == half(0.0 / 0.0)));
- VERIFY(half(0.0 / 0.0) != half(0.0 / 0.0));
-
- VERIFY(!(half(1.0) == half(0.0 / 0.0)));
- VERIFY(!(half(1.0) < half(0.0 / 0.0)));
- VERIFY(!(half(1.0) > half(0.0 / 0.0)));
- VERIFY(half(1.0) != half(0.0 / 0.0));
-
- VERIFY(half(1.0) < half(1.0 / 0.0));
- VERIFY(half(1.0) > half(-1.0 / 0.0));
-#endif
+ VERIFY(!(Eigen::half(0.0 / 0.0) == Eigen::half(0.0 / 0.0)));
+ VERIFY(!(Eigen::half(0.0 / 0.0) != Eigen::half(0.0 / 0.0)));
+
+ VERIFY(!(Eigen::half(1.0) == Eigen::half(0.0 / 0.0)));
+ VERIFY(!(Eigen::half(1.0) < Eigen::half(0.0 / 0.0)));
+ VERIFY(!(Eigen::half(1.0) > Eigen::half(0.0 / 0.0)));
+ VERIFY(!(Eigen::half(1.0) != Eigen::half(0.0 / 0.0)));
+
+ VERIFY(Eigen::half(1.0) < Eigen::half(1.0 / 0.0));
+ VERIFY(Eigen::half(1.0) > Eigen::half(-1.0 / 0.0));
}
+
void test_basic_functions()
{
- VERIFY_IS_EQUAL(float(numext::abs(half(3.5f))), 3.5f);
- VERIFY_IS_EQUAL(float(numext::abs(half(-3.5f))), 3.5f);
+ VERIFY_IS_EQUAL(float(numext::abs(Eigen::half(3.5f))), 3.5f);
+ VERIFY_IS_EQUAL(float(numext::abs(Eigen::half(-3.5f))), 3.5f);
- VERIFY_IS_EQUAL(float(numext::floor(half(3.5f))), 3.0f);
- VERIFY_IS_EQUAL(float(numext::floor(half(-3.5f))), -4.0f);
+ VERIFY_IS_EQUAL(float(numext::floor(Eigen::half(3.5f))), 3.0f);
+ VERIFY_IS_EQUAL(float(numext::floor(Eigen::half(-3.5f))), -4.0f);
- VERIFY_IS_EQUAL(float(numext::ceil(half(3.5f))), 4.0f);
- VERIFY_IS_EQUAL(float(numext::ceil(half(-3.5f))), -3.0f);
+ VERIFY_IS_EQUAL(float(numext::ceil(Eigen::half(3.5f))), 4.0f);
+ VERIFY_IS_EQUAL(float(numext::ceil(Eigen::half(-3.5f))), -3.0f);
- VERIFY_IS_APPROX(float(numext::sqrt(half(0.0f))), 0.0f);
- VERIFY_IS_APPROX(float(numext::sqrt(half(4.0f))), 2.0f);
+ VERIFY_IS_APPROX(float(numext::sqrt(Eigen::half(0.0f))), 0.0f);
+ VERIFY_IS_APPROX(float(numext::sqrt(Eigen::half(4.0f))), 2.0f);
- VERIFY_IS_APPROX(float(numext::pow(half(0.0f), half(1.0f))), 0.0f);
- VERIFY_IS_APPROX(float(numext::pow(half(2.0f), half(2.0f))), 4.0f);
+ VERIFY_IS_APPROX(float(numext::pow(Eigen::half(0.0f), Eigen::half(1.0f))), 0.0f);
+ VERIFY_IS_APPROX(float(numext::pow(Eigen::half(2.0f), Eigen::half(2.0f))), 4.0f);
- VERIFY_IS_EQUAL(float(numext::exp(half(0.0f))), 1.0f);
- VERIFY_IS_APPROX(float(numext::exp(half(EIGEN_PI))), float(20.0 + EIGEN_PI));
+ VERIFY_IS_EQUAL(float(numext::exp(Eigen::half(0.0f))), 1.0f);
+ VERIFY_IS_APPROX(float(numext::exp(Eigen::half(EIGEN_PI))), float(20.0 + EIGEN_PI));
- VERIFY_IS_EQUAL(float(numext::log(half(1.0f))), 0.0f);
- VERIFY_IS_APPROX(float(numext::log(half(10.0f))), 2.30273f);
+ VERIFY_IS_EQUAL(float(numext::log(Eigen::half(1.0f))), 0.0f);
+ VERIFY_IS_APPROX(float(numext::log(Eigen::half(10.0f))), 2.30273f);
}
void test_trigonometric_functions()
{
- VERIFY_IS_APPROX(numext::cos(half(0.0f)), half(cosf(0.0f)));
- VERIFY_IS_APPROX(numext::cos(half(EIGEN_PI)), half(cosf(EIGEN_PI)));
- //VERIFY_IS_APPROX(numext::cos(half(EIGEN_PI/2)), half(cosf(EIGEN_PI/2)));
- //VERIFY_IS_APPROX(numext::cos(half(3*EIGEN_PI/2)), half(cosf(3*EIGEN_PI/2)));
- VERIFY_IS_APPROX(numext::cos(half(3.5f)), half(cosf(3.5f)));
-
- VERIFY_IS_APPROX(numext::sin(half(0.0f)), half(sinf(0.0f)));
- // VERIFY_IS_APPROX(numext::sin(half(EIGEN_PI)), half(sinf(EIGEN_PI)));
- VERIFY_IS_APPROX(numext::sin(half(EIGEN_PI/2)), half(sinf(EIGEN_PI/2)));
- VERIFY_IS_APPROX(numext::sin(half(3*EIGEN_PI/2)), half(sinf(3*EIGEN_PI/2)));
- VERIFY_IS_APPROX(numext::sin(half(3.5f)), half(sinf(3.5f)));
-
- VERIFY_IS_APPROX(numext::tan(half(0.0f)), half(tanf(0.0f)));
- // VERIFY_IS_APPROX(numext::tan(half(EIGEN_PI)), half(tanf(EIGEN_PI)));
- // VERIFY_IS_APPROX(numext::tan(half(EIGEN_PI/2)), half(tanf(EIGEN_PI/2)));
- //VERIFY_IS_APPROX(numext::tan(half(3*EIGEN_PI/2)), half(tanf(3*EIGEN_PI/2)));
- VERIFY_IS_APPROX(numext::tan(half(3.5f)), half(tanf(3.5f)));
+ VERIFY_IS_APPROX(numext::cos(Eigen::half(0.0f)), Eigen::half(cosf(0.0f)));
+ VERIFY_IS_APPROX(numext::cos(Eigen::half(EIGEN_PI)), Eigen::half(cosf(EIGEN_PI)));
+ VERIFY_IS_APPROX_OR_LESS_THAN(numext::cos(Eigen::half(EIGEN_PI/2)), NumTraits<Eigen::half>::epsilon() * Eigen::half(5));
+ VERIFY_IS_APPROX_OR_LESS_THAN(numext::cos(Eigen::half(3*EIGEN_PI/2)), NumTraits<Eigen::half>::epsilon() * Eigen::half(5));
+ VERIFY_IS_APPROX(numext::cos(Eigen::half(3.5f)), Eigen::half(cosf(3.5f)));
+
+ VERIFY_IS_APPROX(numext::sin(Eigen::half(0.0f)), Eigen::half(sinf(0.0f)));
+ VERIFY_IS_APPROX_OR_LESS_THAN(numext::sin(Eigen::half(EIGEN_PI)), NumTraits<Eigen::half>::epsilon() * Eigen::half(10));
+
+ VERIFY_IS_APPROX(numext::sin(Eigen::half(EIGEN_PI/2)), Eigen::half(sinf(EIGEN_PI/2)));
+ VERIFY_IS_APPROX(numext::sin(Eigen::half(3*EIGEN_PI/2)), Eigen::half(sinf(3*EIGEN_PI/2)));
+ VERIFY_IS_APPROX(numext::sin(Eigen::half(3.5f)), Eigen::half(sinf(3.5f)));
+
+ VERIFY_IS_APPROX(numext::tan(Eigen::half(0.0f)), Eigen::half(tanf(0.0f)));
+ VERIFY_IS_APPROX_OR_LESS_THAN(numext::tan(Eigen::half(EIGEN_PI)), NumTraits<Eigen::half>::epsilon() * Eigen::half(10));
+ VERIFY_IS_APPROX(numext::tan(Eigen::half(3.5f)), Eigen::half(tanf(3.5f)));
}
void test_cxx11_float16()
{
CALL_SUBTEST(test_conversion());
- CALL_SUBTEST(test_numtraits());
CALL_SUBTEST(test_arithmetic());
CALL_SUBTEST(test_comparison());
CALL_SUBTEST(test_basic_functions());
diff --git a/unsupported/test/cxx11_tensor_dimension.cpp b/unsupported/test/cxx11_tensor_dimension.cpp
index 0bccc3396..16f168ed4 100644
--- a/unsupported/test/cxx11_tensor_dimension.cpp
+++ b/unsupported/test/cxx11_tensor_dimension.cpp
@@ -21,7 +21,7 @@ static void test_dynamic_size()
VERIFY_IS_EQUAL((int)Eigen::internal::array_get<0>(dimensions), 2);
VERIFY_IS_EQUAL((int)Eigen::internal::array_get<1>(dimensions), 3);
VERIFY_IS_EQUAL((int)Eigen::internal::array_get<2>(dimensions), 7);
- VERIFY_IS_EQUAL(dimensions.TotalSize(), 2*3*7);
+ VERIFY_IS_EQUAL((int)dimensions.TotalSize(), 2*3*7);
VERIFY_IS_EQUAL((int)dimensions[0], 2);
VERIFY_IS_EQUAL((int)dimensions[1], 3);
VERIFY_IS_EQUAL((int)dimensions[2], 7);
@@ -34,12 +34,12 @@ static void test_fixed_size()
VERIFY_IS_EQUAL((int)Eigen::internal::array_get<0>(dimensions), 2);
VERIFY_IS_EQUAL((int)Eigen::internal::array_get<1>(dimensions), 3);
VERIFY_IS_EQUAL((int)Eigen::internal::array_get<2>(dimensions), 7);
- VERIFY_IS_EQUAL(dimensions.TotalSize(), 2*3*7);
+ VERIFY_IS_EQUAL((int)dimensions.TotalSize(), 2*3*7);
}
static void test_match()
{
- Eigen::DSizes<int, 3> dyn(2,3,7);
+ Eigen::DSizes<unsigned int, 3> dyn((unsigned int)2,(unsigned int)3,(unsigned int)7);
Eigen::Sizes<2,3,7> stat;
VERIFY_IS_EQUAL(Eigen::dimensions_match(dyn, stat), true);
@@ -51,13 +51,13 @@ static void test_match()
static void test_rank_zero()
{
Eigen::Sizes<> scalar;
- VERIFY_IS_EQUAL(scalar.TotalSize(), 1);
- VERIFY_IS_EQUAL(scalar.rank(), 0);
- VERIFY_IS_EQUAL(internal::array_prod(scalar), 1);
+ VERIFY_IS_EQUAL((int)scalar.TotalSize(), 1);
+ VERIFY_IS_EQUAL((int)scalar.rank(), 0);
+ VERIFY_IS_EQUAL((int)internal::array_prod(scalar), 1);
Eigen::DSizes<ptrdiff_t, 0> dscalar;
- VERIFY_IS_EQUAL(dscalar.TotalSize(), 1);
- VERIFY_IS_EQUAL(dscalar.rank(), 0u);
+ VERIFY_IS_EQUAL((int)dscalar.TotalSize(), 1);
+ VERIFY_IS_EQUAL((int)dscalar.rank(), 0);
}
void test_cxx11_tensor_dimension()
diff --git a/unsupported/test/cxx11_tensor_morphing.cpp b/unsupported/test/cxx11_tensor_morphing.cpp
index c575d3fdc..f7de43110 100644
--- a/unsupported/test/cxx11_tensor_morphing.cpp
+++ b/unsupported/test/cxx11_tensor_morphing.cpp
@@ -13,6 +13,7 @@
using Eigen::Tensor;
+template<typename>
static void test_simple_reshape()
{
Tensor<float, 5> tensor1(2,3,1,7,1);
@@ -40,7 +41,7 @@ static void test_simple_reshape()
}
}
-
+template<typename>
static void test_reshape_in_expr() {
MatrixXf m1(2,3*5*7*11);
MatrixXf m2(3*5*7*11,13);
@@ -65,7 +66,7 @@ static void test_reshape_in_expr() {
}
}
-
+template<typename>
static void test_reshape_as_lvalue()
{
Tensor<float, 3> tensor(2,3,7);
@@ -114,6 +115,7 @@ static void test_simple_slice()
}
}
+template<typename=void>
static void test_const_slice()
{
const float b[1] = {42};
@@ -459,25 +461,25 @@ static void test_composition()
void test_cxx11_tensor_morphing()
{
- CALL_SUBTEST(test_simple_reshape());
- CALL_SUBTEST(test_reshape_in_expr());
- CALL_SUBTEST(test_reshape_as_lvalue());
-
- CALL_SUBTEST(test_simple_slice<ColMajor>());
- CALL_SUBTEST(test_simple_slice<RowMajor>());
- CALL_SUBTEST(test_const_slice());
- CALL_SUBTEST(test_slice_in_expr<ColMajor>());
- CALL_SUBTEST(test_slice_in_expr<RowMajor>());
- CALL_SUBTEST(test_slice_as_lvalue<ColMajor>());
- CALL_SUBTEST(test_slice_as_lvalue<RowMajor>());
- CALL_SUBTEST(test_slice_raw_data<ColMajor>());
- CALL_SUBTEST(test_slice_raw_data<RowMajor>());
-
- CALL_SUBTEST(test_strided_slice_write<ColMajor>());
- CALL_SUBTEST(test_strided_slice<ColMajor>());
- CALL_SUBTEST(test_strided_slice_write<RowMajor>());
- CALL_SUBTEST(test_strided_slice<RowMajor>());
-
- CALL_SUBTEST(test_composition<ColMajor>());
- CALL_SUBTEST(test_composition<RowMajor>());
+ CALL_SUBTEST_1(test_simple_reshape<void>());
+ CALL_SUBTEST_1(test_reshape_in_expr<void>());
+ CALL_SUBTEST_1(test_reshape_as_lvalue<void>());
+
+ CALL_SUBTEST_1(test_simple_slice<ColMajor>());
+ CALL_SUBTEST_1(test_simple_slice<RowMajor>());
+ CALL_SUBTEST_1(test_const_slice());
+ CALL_SUBTEST_2(test_slice_in_expr<ColMajor>());
+ CALL_SUBTEST_3(test_slice_in_expr<RowMajor>());
+ CALL_SUBTEST_4(test_slice_as_lvalue<ColMajor>());
+ CALL_SUBTEST_4(test_slice_as_lvalue<RowMajor>());
+ CALL_SUBTEST_5(test_slice_raw_data<ColMajor>());
+ CALL_SUBTEST_5(test_slice_raw_data<RowMajor>());
+
+ CALL_SUBTEST_6(test_strided_slice_write<ColMajor>());
+ CALL_SUBTEST_6(test_strided_slice<ColMajor>());
+ CALL_SUBTEST_6(test_strided_slice_write<RowMajor>());
+ CALL_SUBTEST_6(test_strided_slice<RowMajor>());
+
+ CALL_SUBTEST_7(test_composition<ColMajor>());
+ CALL_SUBTEST_7(test_composition<RowMajor>());
}
diff --git a/unsupported/test/cxx11_tensor_of_float16_cuda.cu b/unsupported/test/cxx11_tensor_of_float16_cuda.cu
index 34e9f54a0..b6df5a4d2 100644
--- a/unsupported/test/cxx11_tensor_of_float16_cuda.cu
+++ b/unsupported/test/cxx11_tensor_of_float16_cuda.cu
@@ -21,6 +21,7 @@ using Eigen::Tensor;
#ifdef EIGEN_HAS_CUDA_FP16
+template<typename>
void test_cuda_conversion() {
Eigen::CudaStreamDevice stream;
Eigen::GpuDevice gpu_device(&stream);
@@ -55,7 +56,7 @@ void test_cuda_conversion() {
gpu_device.deallocate(d_conv);
}
-
+template<typename>
void test_cuda_unary() {
Eigen::CudaStreamDevice stream;
Eigen::GpuDevice gpu_device(&stream);
@@ -92,7 +93,7 @@ void test_cuda_unary() {
gpu_device.deallocate(d_res_float);
}
-
+template<typename>
void test_cuda_elementwise() {
Eigen::CudaStreamDevice stream;
Eigen::GpuDevice gpu_device(&stream);
@@ -134,6 +135,7 @@ void test_cuda_elementwise() {
gpu_device.deallocate(d_res_float);
}
+template<typename>
void test_cuda_trancendental() {
Eigen::CudaStreamDevice stream;
Eigen::GpuDevice gpu_device(&stream);
@@ -186,7 +188,10 @@ void test_cuda_trancendental() {
}
for (int i = 0; i < num_elem; ++i) {
std::cout << "Checking elemwise log " << i << " input = " << input2(i) << " full = " << full_prec2(i) << " half = " << half_prec2(i) << std::endl;
- VERIFY_IS_APPROX(full_prec2(i), half_prec2(i));
+ if(std::abs(input2(i)-1.f)<0.05f) // log lacks accurary nearby 1
+ VERIFY_IS_APPROX(full_prec2(i)+Eigen::half(0.1f), half_prec2(i)+Eigen::half(0.1f));
+ else
+ VERIFY_IS_APPROX(full_prec2(i), half_prec2(i));
}
gpu_device.deallocate(d_float1);
gpu_device.deallocate(d_float2);
@@ -196,7 +201,7 @@ void test_cuda_trancendental() {
gpu_device.deallocate(d_res2_float);
}
-
+template<typename>
void test_cuda_contractions() {
Eigen::CudaStreamDevice stream;
Eigen::GpuDevice gpu_device(&stream);
@@ -247,7 +252,7 @@ void test_cuda_contractions() {
gpu_device.deallocate(d_res_float);
}
-
+template<typename>
void test_cuda_reductions(int size1, int size2, int redux) {
std::cout << "Reducing " << size1 << " by " << size2
@@ -296,17 +301,19 @@ void test_cuda_reductions(int size1, int size2, int redux) {
gpu_device.deallocate(d_res_float);
}
+template<typename>
void test_cuda_reductions() {
- test_cuda_reductions(13, 13, 0);
- test_cuda_reductions(13, 13, 1);
+ test_cuda_reductions<void>(13, 13, 0);
+ test_cuda_reductions<void>(13, 13, 1);
- test_cuda_reductions(35, 36, 0);
- test_cuda_reductions(35, 36, 1);
+ test_cuda_reductions<void>(35, 36, 0);
+ test_cuda_reductions<void>(35, 36, 1);
- test_cuda_reductions(36, 35, 0);
- test_cuda_reductions(36, 35, 1);
+ test_cuda_reductions<void>(36, 35, 0);
+ test_cuda_reductions<void>(36, 35, 1);
}
+template<typename>
void test_cuda_full_reductions() {
Eigen::CudaStreamDevice stream;
Eigen::GpuDevice gpu_device(&stream);
@@ -355,7 +362,7 @@ void test_cuda_full_reductions() {
gpu_device.deallocate(d_res_float);
}
-
+template<typename>
void test_cuda_forced_evals() {
Eigen::CudaStreamDevice stream;
@@ -409,14 +416,14 @@ void test_cuda_forced_evals() {
void test_cxx11_tensor_of_float16_cuda()
{
#ifdef EIGEN_HAS_CUDA_FP16
- CALL_SUBTEST_1(test_cuda_conversion());
- CALL_SUBTEST_1(test_cuda_unary());
- CALL_SUBTEST_1(test_cuda_elementwise());
- CALL_SUBTEST_1(test_cuda_trancendental());
- CALL_SUBTEST_2(test_cuda_contractions());
- CALL_SUBTEST_3(test_cuda_reductions());
- CALL_SUBTEST_4(test_cuda_full_reductions());
- CALL_SUBTEST_5(test_cuda_forced_evals());
+ CALL_SUBTEST_1(test_cuda_conversion<void>());
+ CALL_SUBTEST_1(test_cuda_unary<void>());
+ CALL_SUBTEST_1(test_cuda_elementwise<void>());
+ CALL_SUBTEST_1(test_cuda_trancendental<void>());
+ CALL_SUBTEST_2(test_cuda_contractions<void>());
+ CALL_SUBTEST_3(test_cuda_reductions<void>());
+ CALL_SUBTEST_4(test_cuda_full_reductions<void>());
+ CALL_SUBTEST_5(test_cuda_forced_evals<void>());
#else
std::cout << "Half floats are not supported by this version of cuda: skipping the test" << std::endl;
#endif
diff --git a/unsupported/test/cxx11_tensor_reduction.cpp b/unsupported/test/cxx11_tensor_reduction.cpp
index ca483257b..1490ec3da 100644
--- a/unsupported/test/cxx11_tensor_reduction.cpp
+++ b/unsupported/test/cxx11_tensor_reduction.cpp
@@ -239,6 +239,33 @@ static void test_simple_reductions() {
}
}
+
+template <int DataLayout>
+static void test_reductions_in_expr() {
+ Tensor<float, 4, DataLayout> tensor(2, 3, 5, 7);
+ tensor.setRandom();
+ array<ptrdiff_t, 2> reduction_axis2;
+ reduction_axis2[0] = 1;
+ reduction_axis2[1] = 3;
+
+ Tensor<float, 2, DataLayout> result(2, 5);
+ result = result.constant(1.0f) - tensor.sum(reduction_axis2);
+ VERIFY_IS_EQUAL(result.dimension(0), 2);
+ VERIFY_IS_EQUAL(result.dimension(1), 5);
+ for (int i = 0; i < 2; ++i) {
+ for (int j = 0; j < 5; ++j) {
+ float sum = 0.0f;
+ for (int k = 0; k < 3; ++k) {
+ for (int l = 0; l < 7; ++l) {
+ sum += tensor(i, k, j, l);
+ }
+ }
+ VERIFY_IS_APPROX(result(i, j), 1.0f - sum);
+ }
+ }
+}
+
+
template <int DataLayout>
static void test_full_reductions() {
Tensor<float, 2, DataLayout> tensor(2, 3);
@@ -462,6 +489,8 @@ void test_cxx11_tensor_reduction() {
CALL_SUBTEST(test_trivial_reductions<RowMajor>());
CALL_SUBTEST(test_simple_reductions<ColMajor>());
CALL_SUBTEST(test_simple_reductions<RowMajor>());
+ CALL_SUBTEST(test_reductions_in_expr<ColMajor>());
+ CALL_SUBTEST(test_reductions_in_expr<RowMajor>());
CALL_SUBTEST(test_full_reductions<ColMajor>());
CALL_SUBTEST(test_full_reductions<RowMajor>());
CALL_SUBTEST(test_user_defined_reductions<ColMajor>());
diff --git a/unsupported/test/mpreal_support.cpp b/unsupported/test/mpreal_support.cpp
index 1aa9e786a..ffa5691eb 100644
--- a/unsupported/test/mpreal_support.cpp
+++ b/unsupported/test/mpreal_support.cpp
@@ -17,6 +17,7 @@ void test_mpreal_support()
std::cerr << "dummy_precision = " << NumTraits<mpreal>::dummy_precision() << "\n";
std::cerr << "highest = " << NumTraits<mpreal>::highest() << "\n";
std::cerr << "lowest = " << NumTraits<mpreal>::lowest() << "\n";
+ std::cerr << "digits10 = " << NumTraits<mpreal>::digits10() << "\n";
for(int i = 0; i < g_repeat; i++) {
int s = Eigen::internal::random<int>(1,100);
diff --git a/unsupported/test/special_functions.cpp b/unsupported/test/special_functions.cpp
new file mode 100644
index 000000000..057fb3e92
--- /dev/null
+++ b/unsupported/test/special_functions.cpp
@@ -0,0 +1,345 @@
+// This file is part of Eigen, a lightweight C++ template library
+// for linear algebra.
+//
+// Copyright (C) 2016 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"
+#include "../Eigen/SpecialFunctions"
+
+template<typename X, typename Y>
+void verify_component_wise(const X& x, const Y& y)
+{
+ for(Index i=0; i<x.size(); ++i)
+ {
+ if((numext::isfinite)(y(i)))
+ VERIFY_IS_APPROX( x(i), y(i) );
+ else if((numext::isnan)(y(i)))
+ VERIFY((numext::isnan)(x(i)));
+ else
+ VERIFY_IS_EQUAL( x(i), y(i) );
+ }
+}
+
+template<typename ArrayType> void array_special_functions()
+{
+ using std::abs;
+ using std::sqrt;
+ typedef typename ArrayType::Scalar Scalar;
+ typedef typename NumTraits<Scalar>::Real RealScalar;
+
+ Scalar plusinf = std::numeric_limits<Scalar>::infinity();
+ Scalar nan = std::numeric_limits<Scalar>::quiet_NaN();
+
+ Index rows = internal::random<Index>(1,30);
+ Index cols = 1;
+
+ // API
+ {
+ ArrayType m1 = ArrayType::Random(rows,cols);
+#if EIGEN_HAS_C99_MATH
+ VERIFY_IS_APPROX(m1.lgamma(), lgamma(m1));
+ VERIFY_IS_APPROX(m1.digamma(), digamma(m1));
+ VERIFY_IS_APPROX(m1.erf(), erf(m1));
+ VERIFY_IS_APPROX(m1.erfc(), erfc(m1));
+#endif // EIGEN_HAS_C99_MATH
+ }
+
+
+#if EIGEN_HAS_C99_MATH
+ // check special functions (comparing against numpy implementation)
+ if (!NumTraits<Scalar>::IsComplex)
+ {
+
+ {
+ ArrayType m1 = ArrayType::Random(rows,cols);
+ ArrayType m2 = ArrayType::Random(rows,cols);
+
+ // Test various propreties of igamma & igammac. These are normalized
+ // gamma integrals where
+ // igammac(a, x) = Gamma(a, x) / Gamma(a)
+ // igamma(a, x) = gamma(a, x) / Gamma(a)
+ // where Gamma and gamma are considered the standard unnormalized
+ // upper and lower incomplete gamma functions, respectively.
+ ArrayType a = m1.abs() + 2;
+ ArrayType x = m2.abs() + 2;
+ ArrayType zero = ArrayType::Zero(rows, cols);
+ ArrayType one = ArrayType::Constant(rows, cols, Scalar(1.0));
+ ArrayType a_m1 = a - one;
+ ArrayType Gamma_a_x = Eigen::igammac(a, x) * a.lgamma().exp();
+ ArrayType Gamma_a_m1_x = Eigen::igammac(a_m1, x) * a_m1.lgamma().exp();
+ ArrayType gamma_a_x = Eigen::igamma(a, x) * a.lgamma().exp();
+ ArrayType gamma_a_m1_x = Eigen::igamma(a_m1, x) * a_m1.lgamma().exp();
+
+ // Gamma(a, 0) == Gamma(a)
+ VERIFY_IS_APPROX(Eigen::igammac(a, zero), one);
+
+ // Gamma(a, x) + gamma(a, x) == Gamma(a)
+ VERIFY_IS_APPROX(Gamma_a_x + gamma_a_x, a.lgamma().exp());
+
+ // Gamma(a, x) == (a - 1) * Gamma(a-1, x) + x^(a-1) * exp(-x)
+ VERIFY_IS_APPROX(Gamma_a_x, (a - 1) * Gamma_a_m1_x + x.pow(a-1) * (-x).exp());
+
+ // gamma(a, x) == (a - 1) * gamma(a-1, x) - x^(a-1) * exp(-x)
+ VERIFY_IS_APPROX(gamma_a_x, (a - 1) * gamma_a_m1_x - x.pow(a-1) * (-x).exp());
+ }
+
+ {
+ // Check exact values of igamma and igammac against a third party calculation.
+ Scalar a_s[] = {Scalar(0), Scalar(1), Scalar(1.5), Scalar(4), Scalar(0.0001), Scalar(1000.5)};
+ Scalar x_s[] = {Scalar(0), Scalar(1), Scalar(1.5), Scalar(4), Scalar(0.0001), Scalar(1000.5)};
+
+ // location i*6+j corresponds to a_s[i], x_s[j].
+ Scalar igamma_s[][6] = {{0.0, nan, nan, nan, nan, nan},
+ {0.0, 0.6321205588285578, 0.7768698398515702,
+ 0.9816843611112658, 9.999500016666262e-05, 1.0},
+ {0.0, 0.4275932955291202, 0.608374823728911,
+ 0.9539882943107686, 7.522076445089201e-07, 1.0},
+ {0.0, 0.01898815687615381, 0.06564245437845008,
+ 0.5665298796332909, 4.166333347221828e-18, 1.0},
+ {0.0, 0.9999780593618628, 0.9999899967080838,
+ 0.9999996219837988, 0.9991370418689945, 1.0},
+ {0.0, 0.0, 0.0, 0.0, 0.0, 0.5042041932513908}};
+ Scalar igammac_s[][6] = {{nan, nan, nan, nan, nan, nan},
+ {1.0, 0.36787944117144233, 0.22313016014842982,
+ 0.018315638888734182, 0.9999000049998333, 0.0},
+ {1.0, 0.5724067044708798, 0.3916251762710878,
+ 0.04601170568923136, 0.9999992477923555, 0.0},
+ {1.0, 0.9810118431238462, 0.9343575456215499,
+ 0.4334701203667089, 1.0, 0.0},
+ {1.0, 2.1940638138146658e-05, 1.0003291916285e-05,
+ 3.7801620118431334e-07, 0.0008629581310054535,
+ 0.0},
+ {1.0, 1.0, 1.0, 1.0, 1.0, 0.49579580674813944}};
+ for (int i = 0; i < 6; ++i) {
+ for (int j = 0; j < 6; ++j) {
+ if ((std::isnan)(igamma_s[i][j])) {
+ VERIFY((std::isnan)(numext::igamma(a_s[i], x_s[j])));
+ } else {
+ VERIFY_IS_APPROX(numext::igamma(a_s[i], x_s[j]), igamma_s[i][j]);
+ }
+
+ if ((std::isnan)(igammac_s[i][j])) {
+ VERIFY((std::isnan)(numext::igammac(a_s[i], x_s[j])));
+ } else {
+ VERIFY_IS_APPROX(numext::igammac(a_s[i], x_s[j]), igammac_s[i][j]);
+ }
+ }
+ }
+ }
+ }
+#endif // EIGEN_HAS_C99_MATH
+
+ // Check the zeta function against scipy.special.zeta
+ {
+ ArrayType x(7), q(7), res(7), ref(7);
+ x << 1.5, 4, 10.5, 10000.5, 3, 1, 0.9;
+ q << 2, 1.5, 3, 1.0001, -2.5, 1.2345, 1.2345;
+ ref << 1.61237534869, 0.234848505667, 1.03086757337e-5, 0.367879440865, 0.054102025820864097, plusinf, nan;
+ CALL_SUBTEST( verify_component_wise(ref, ref); );
+ CALL_SUBTEST( res = x.zeta(q); verify_component_wise(res, ref); );
+ CALL_SUBTEST( res = zeta(x,q); verify_component_wise(res, ref); );
+ }
+
+ // digamma
+ {
+ ArrayType x(7), res(7), ref(7);
+ x << 1, 1.5, 4, -10.5, 10000.5, 0, -1;
+ ref << -0.5772156649015329, 0.03648997397857645, 1.2561176684318, 2.398239129535781, 9.210340372392849, plusinf, plusinf;
+ CALL_SUBTEST( verify_component_wise(ref, ref); );
+
+ CALL_SUBTEST( res = x.digamma(); verify_component_wise(res, ref); );
+ CALL_SUBTEST( res = digamma(x); verify_component_wise(res, ref); );
+ }
+
+
+#if EIGEN_HAS_C99_MATH
+ {
+ ArrayType n(11), x(11), res(11), ref(11);
+ n << 1, 1, 1, 1.5, 17, 31, 28, 8, 42, 147, 170;
+ x << 2, 3, 25.5, 1.5, 4.7, 11.8, 17.7, 30.2, 15.8, 54.1, 64;
+ ref << 0.644934066848, 0.394934066848, 0.0399946696496, nan, 293.334565435, 0.445487887616, -2.47810300902e-07, -8.29668781082e-09, -0.434562276666, 0.567742190178, -0.0108615497927;
+ CALL_SUBTEST( verify_component_wise(ref, ref); );
+
+ if(sizeof(RealScalar)>=8) { // double
+ // Reason for commented line: http://eigen.tuxfamily.org/bz/show_bug.cgi?id=1232
+ // CALL_SUBTEST( res = x.polygamma(n); verify_component_wise(res, ref); );
+ CALL_SUBTEST( res = polygamma(n,x); verify_component_wise(res, ref); );
+ }
+ else {
+ // CALL_SUBTEST( res = x.polygamma(n); verify_component_wise(res.head(8), ref.head(8)); );
+ CALL_SUBTEST( res = polygamma(n,x); verify_component_wise(res.head(8), ref.head(8)); );
+ }
+ }
+#endif
+
+#if EIGEN_HAS_C99_MATH
+ {
+ // Inputs and ground truth generated with scipy via:
+ // a = np.logspace(-3, 3, 5) - 1e-3
+ // b = np.logspace(-3, 3, 5) - 1e-3
+ // x = np.linspace(-0.1, 1.1, 5)
+ // (full_a, full_b, full_x) = np.vectorize(lambda a, b, x: (a, b, x))(*np.ix_(a, b, x))
+ // full_a = full_a.flatten().tolist() # same for full_b, full_x
+ // v = scipy.special.betainc(full_a, full_b, full_x).flatten().tolist()
+ //
+ // Note in Eigen, we call betainc with arguments in the order (x, a, b).
+ ArrayType a(125);
+ ArrayType b(125);
+ ArrayType x(125);
+ ArrayType v(125);
+ ArrayType res(125);
+
+ a << 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
+ 0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+ 0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+ 0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+ 0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+ 0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+ 0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+ 0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+ 0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+ 0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999,
+ 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999,
+ 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999, 0.999,
+ 31.62177660168379, 31.62177660168379, 31.62177660168379,
+ 31.62177660168379, 31.62177660168379, 31.62177660168379,
+ 31.62177660168379, 31.62177660168379, 31.62177660168379,
+ 31.62177660168379, 31.62177660168379, 31.62177660168379,
+ 31.62177660168379, 31.62177660168379, 31.62177660168379,
+ 31.62177660168379, 31.62177660168379, 31.62177660168379,
+ 31.62177660168379, 31.62177660168379, 31.62177660168379,
+ 31.62177660168379, 31.62177660168379, 31.62177660168379,
+ 31.62177660168379, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999,
+ 999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999,
+ 999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999, 999.999,
+ 999.999, 999.999, 999.999;
+
+ b << 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379, 0.03062277660168379,
+ 0.03062277660168379, 0.03062277660168379, 0.03062277660168379, 0.999,
+ 0.999, 0.999, 0.999, 0.999, 31.62177660168379, 31.62177660168379,
+ 31.62177660168379, 31.62177660168379, 31.62177660168379, 999.999,
+ 999.999, 999.999, 999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0,
+ 0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+ 0.03062277660168379, 0.03062277660168379, 0.999, 0.999, 0.999, 0.999,
+ 0.999, 31.62177660168379, 31.62177660168379, 31.62177660168379,
+ 31.62177660168379, 31.62177660168379, 999.999, 999.999, 999.999,
+ 999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379,
+ 0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+ 0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999,
+ 31.62177660168379, 31.62177660168379, 31.62177660168379,
+ 31.62177660168379, 31.62177660168379, 999.999, 999.999, 999.999,
+ 999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379,
+ 0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+ 0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999,
+ 31.62177660168379, 31.62177660168379, 31.62177660168379,
+ 31.62177660168379, 31.62177660168379, 999.999, 999.999, 999.999,
+ 999.999, 999.999, 0.0, 0.0, 0.0, 0.0, 0.0, 0.03062277660168379,
+ 0.03062277660168379, 0.03062277660168379, 0.03062277660168379,
+ 0.03062277660168379, 0.999, 0.999, 0.999, 0.999, 0.999,
+ 31.62177660168379, 31.62177660168379, 31.62177660168379,
+ 31.62177660168379, 31.62177660168379, 999.999, 999.999, 999.999,
+ 999.999, 999.999;
+
+ x << -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5,
+ 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2,
+ 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1,
+ 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1,
+ -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8,
+ 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5,
+ 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2,
+ 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1,
+ 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5, 0.8, 1.1, -0.1, 0.2, 0.5,
+ 0.8, 1.1;
+
+ v << nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
+ nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,
+ nan, nan, nan, 0.47972119876364683, 0.5, 0.5202788012363533, nan, nan,
+ 0.9518683957740043, 0.9789663010413743, 0.9931729188073435, nan, nan,
+ 0.999995949033062, 0.9999999999993698, 0.9999999999999999, nan, nan,
+ 0.9999999999999999, 0.9999999999999999, 0.9999999999999999, nan, nan,
+ nan, nan, nan, nan, nan, 0.006827081192655869, 0.0210336989586256,
+ 0.04813160422599567, nan, nan, 0.20014344256217678, 0.5000000000000001,
+ 0.7998565574378232, nan, nan, 0.9991401428435834, 0.999999999698403,
+ 0.9999999999999999, nan, nan, 0.9999999999999999, 0.9999999999999999,
+ 0.9999999999999999, nan, nan, nan, nan, nan, nan, nan,
+ 1.0646600232370887e-25, 6.301722877826246e-13, 4.050966937974938e-06,
+ nan, nan, 7.864342668429763e-23, 3.015969667594166e-10,
+ 0.0008598571564165444, nan, nan, 6.031987710123844e-08,
+ 0.5000000000000007, 0.9999999396801229, nan, nan, 0.9999999999999999,
+ 0.9999999999999999, 0.9999999999999999, nan, nan, nan, nan, nan, nan,
+ nan, 0.0, 7.029920380986636e-306, 2.2450728208591345e-101, nan, nan,
+ 0.0, 9.275871147869727e-302, 1.2232913026152827e-97, nan, nan, 0.0,
+ 3.0891393081932924e-252, 2.9303043666183996e-60, nan, nan,
+ 2.248913486879199e-196, 0.5000000000004947, 0.9999999999999999, nan;
+
+ CALL_SUBTEST(res = betainc(a, b, x);
+ verify_component_wise(res, v););
+ }
+
+ // Test various properties of betainc
+ {
+ ArrayType m1 = ArrayType::Random(32);
+ ArrayType m2 = ArrayType::Random(32);
+ ArrayType m3 = ArrayType::Random(32);
+ ArrayType one = ArrayType::Constant(32, Scalar(1.0));
+ const Scalar eps = std::numeric_limits<Scalar>::epsilon();
+ ArrayType a = (m1 * 4.0).exp();
+ ArrayType b = (m2 * 4.0).exp();
+ ArrayType x = m3.abs();
+
+ // betainc(a, 1, x) == x**a
+ CALL_SUBTEST(
+ ArrayType test = betainc(a, one, x);
+ ArrayType expected = x.pow(a);
+ verify_component_wise(test, expected););
+
+ // betainc(1, b, x) == 1 - (1 - x)**b
+ CALL_SUBTEST(
+ ArrayType test = betainc(one, b, x);
+ ArrayType expected = one - (one - x).pow(b);
+ verify_component_wise(test, expected););
+
+ // betainc(a, b, x) == 1 - betainc(b, a, 1-x)
+ CALL_SUBTEST(
+ ArrayType test = betainc(a, b, x) + betainc(b, a, one - x);
+ ArrayType expected = one;
+ verify_component_wise(test, expected););
+
+ // betainc(a+1, b, x) = betainc(a, b, x) - x**a * (1 - x)**b / (a * beta(a, b))
+ CALL_SUBTEST(
+ ArrayType num = x.pow(a) * (one - x).pow(b);
+ ArrayType denom = a * (a.lgamma() + b.lgamma() - (a + b).lgamma()).exp();
+ // Add eps to rhs and lhs so that component-wise test doesn't result in
+ // nans when both outputs are zeros.
+ ArrayType expected = betainc(a, b, x) - num / denom + eps;
+ ArrayType test = betainc(a + one, b, x) + eps;
+ if (sizeof(Scalar) >= 8) { // double
+ verify_component_wise(test, expected);
+ } else {
+ // Reason for limited test: http://eigen.tuxfamily.org/bz/show_bug.cgi?id=1232
+ verify_component_wise(test.head(8), expected.head(8));
+ });
+
+ // betainc(a, b+1, x) = betainc(a, b, x) + x**a * (1 - x)**b / (b * beta(a, b))
+ CALL_SUBTEST(
+ // Add eps to rhs and lhs so that component-wise test doesn't result in
+ // nans when both outputs are zeros.
+ ArrayType num = x.pow(a) * (one - x).pow(b);
+ ArrayType denom = b * (a.lgamma() + b.lgamma() - (a + b).lgamma()).exp();
+ ArrayType expected = betainc(a, b, x) + num / denom + eps;
+ ArrayType test = betainc(a, b + one, x) + eps;
+ verify_component_wise(test, expected););
+ }
+#endif
+}
+
+void test_special_functions()
+{
+ CALL_SUBTEST_1(array_special_functions<ArrayXf>());
+ CALL_SUBTEST_2(array_special_functions<ArrayXd>());
+}
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