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Feb 4, 2021
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Test pyarray assign traits #252

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54ca763
test pyarray assign traits
adriendelsalle Feb 1, 2021
63d083a
test both static and dynamic simd linear assign
adriendelsalle Feb 1, 2021
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1 change: 1 addition & 0 deletions test/CMakeLists.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -86,6 +86,7 @@ include_directories(${GTEST_INCLUDE_DIRS})
set(XTENSOR_PYTHON_TESTS
main.cpp
test_pyarray.cpp
test_pyarray_traits.cpp
test_pytensor.cpp
test_pyvectorize.cpp
)
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166 changes: 166 additions & 0 deletions test/test_pyarray_traits.cpp
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@@ -0,0 +1,166 @@
/***************************************************************************
* Copyright (c) Wolf Vollprecht, Johan Mabille and Sylvain Corlay *
* Copyright (c) QuantStack *
* *
* Distributed under the terms of the BSD 3-Clause License. *
* *
* The full license is in the file LICENSE, distributed with this software. *
****************************************************************************/

#include "gtest/gtest.h"

#include "xtensor-python/pyarray.hpp"



namespace xt
{
namespace testing
{
class pyarray_traits: public ::testing::Test
{
protected:

using dynamic_type = xt::pyarray<double>;
using row_major_type = xt::pyarray<double, xt::layout_type::row_major>;
using column_major_type = xt::pyarray<double, xt::layout_type::column_major>;

dynamic_type d1 = {{0., 1.}, {0., 10.}, {0., 100.}};
dynamic_type d2 = {{0., 2.}, {0., 20.}, {0., 200.}};

row_major_type r1 = {{0., 1.}, {0., 10.}, {0., 100.}};
row_major_type r2 = {{0., 2.}, {0., 20.}, {0., 200.}};

column_major_type c1 = {{0., 1.}, {0., 10.}, {0., 100.}};
column_major_type c2 = {{0., 2.}, {0., 20.}, {0., 200.}};

template <class T>
bool test_has_strides(T const&)
{
return xt::has_strides<T>::value;
}

template <class T>
xt::layout_type test_result_layout(T const& a1, T const& a2)
{
auto tmp1 = pow(sin((a2 - a1) / 2.), 2.);
auto tmp2 = cos(a1);
return (tmp1 + tmp2).layout();
}

template <class T>
bool test_linear_assign(T const& a1, T const& a2)
{
auto tmp1 = pow(sin((a2 - a1) / 2.), 2.);
auto tmp2 = cos(a1);
T res = tmp1 + tmp2;
return xt::xassign_traits<T, decltype(tmp1 + tmp2)>::linear_assign(res, tmp1 + tmp2, true);
}

template <class T>
bool test_static_simd_linear_assign(T const& a1, T const& a2)
{
auto tmp1 = pow(sin((a2 - a1) / 2.), 2.);
auto tmp2 = cos(a1);
return xt::xassign_traits<T, decltype(tmp2)>::simd_linear_assign();
}

template <class T>
bool test_dynamic_simd_linear_assign(T const& a1, T const& a2)
{
auto tmp1 = pow(sin((a2 - a1) / 2.), 2.);
auto tmp2 = cos(a1);
return xt::xassign_traits<T, decltype(tmp2)>::simd_linear_assign(a1, tmp2);
}

template <class T>
bool test_linear_static_layout(T const& a1, T const& a2)
{
auto tmp1 = pow(sin((a2 - a1) / 2.), 2.);
auto tmp2 = cos(a1);
return xt::detail::linear_static_layout<decltype(tmp1), decltype(tmp2)>();
}

template <class T>
bool test_contiguous_layout(T const& a1, T const& a2)
{
auto tmp1 = pow(sin((a2 - a1) / 2.), 2.);
auto tmp2 = cos(a1);
return decltype(tmp1)::contiguous_layout && decltype(tmp2)::contiguous_layout;
}
};

TEST_F(pyarray_traits, result_layout)
{
EXPECT_TRUE(d1.layout() == layout_type::row_major);
EXPECT_TRUE(test_result_layout(d1, d2) == layout_type::row_major);

EXPECT_TRUE(r1.layout() == layout_type::row_major);
EXPECT_TRUE(test_result_layout(r1, r2) == layout_type::row_major);

EXPECT_TRUE(c1.layout() == layout_type::column_major);
EXPECT_TRUE(test_result_layout(c1, c2) == layout_type::column_major);
}

TEST_F(pyarray_traits, has_strides)
{
EXPECT_TRUE(test_has_strides(d1));
EXPECT_TRUE(test_has_strides(r1));
EXPECT_TRUE(test_has_strides(c1));
}

TEST_F(pyarray_traits, has_linear_assign)
{
EXPECT_TRUE(d2.has_linear_assign(d1.strides()));
EXPECT_TRUE(r2.has_linear_assign(r1.strides()));
EXPECT_TRUE(c2.has_linear_assign(c1.strides()));
}

TEST_F(pyarray_traits, linear_assign)
{
EXPECT_TRUE(test_linear_assign(d1, d2));
EXPECT_TRUE(test_linear_assign(r1, r2));
EXPECT_TRUE(test_linear_assign(c1, c2));
}

TEST_F(pyarray_traits, static_simd_linear_assign)
{
#ifdef XTENSOR_USE_XSIMD
EXPECT_FALSE(test_static_simd_linear_assign(d1, d2));
EXPECT_TRUE(test_static_simd_linear_assign(r1, r2));
EXPECT_TRUE(test_static_simd_linear_assign(c1, c2));
#else
EXPECT_FALSE(test_static_simd_linear_assign(d1, d2));
EXPECT_FALSE(test_static_simd_linear_assign(r1, r2));
EXPECT_FALSE(test_static_simd_linear_assign(c1, c2));
#endif
}

TEST_F(pyarray_traits, dynamic_simd_linear_assign)
{
#ifdef XTENSOR_USE_XSIMD
EXPECT_TRUE(test_dynamic_simd_linear_assign(d1, d2));
EXPECT_TRUE(test_dynamic_simd_linear_assign(r1, r2));
EXPECT_TRUE(test_dynamic_simd_linear_assign(c1, c2));
#else
EXPECT_FALSE(test_dynamic_simd_linear_assign(d1, d2));
EXPECT_FALSE(test_dynamic_simd_linear_assign(r1, r2));
EXPECT_FALSE(test_dynamic_simd_linear_assign(c1, c2));
#endif
}

TEST_F(pyarray_traits, linear_static_layout)
{
EXPECT_FALSE(test_linear_static_layout(d1, d2));
EXPECT_TRUE(test_linear_static_layout(r1, r2));
EXPECT_TRUE(test_linear_static_layout(c1, c2));
}

TEST_F(pyarray_traits, contiguous_layout)
{
EXPECT_FALSE(test_contiguous_layout(d1, d2));
EXPECT_TRUE(test_contiguous_layout(r1, r2));
EXPECT_TRUE(test_contiguous_layout(c1, c2));
}
}
}