xtensor-python/test/test_pyarray.cpp at master · robertodr/xtensor-python · GitHub

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/***************************************************************************

* *

* 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"

#include "xtensor/xarray.hpp"

#include "xtensor/xview.hpp"

#include "test_common.hpp"

namespace xt

{

using container_type = std::vector<npy_intp>;

template <class T>

using ndarray = pyarray<T, xt::layout_type::row_major>;

void test1 (ndarray<int>const& x)

{

ndarray<int> y = x;

ndarray<int> z = xt::zeros<int>({10});

}

double compute(ndarray<double> const& xs)

{

auto v = xt::view (xs, 0, xt::all());

return v(0);

}

TEST(pyarray, initializer_constructor)

{

pyarray<int> t

{{{ 0, 1, 2},

{ 3, 4, 5},

{ 6, 7, 8}},

{{ 9, 10, 11},

{12, 13, 14},

{15, 16, 17}}};

EXPECT_EQ(t.dimension(), 3);

EXPECT_EQ(t(0, 0, 1), 1);

EXPECT_EQ(t.shape()[0], 2);

}

TEST(pyarray, shaped_constructor)

{

SCOPED_TRACE("row_major constructor");

row_major_result<> rm;

pyarray<int> ra(rm.m_shape);

compare_shape(ra, rm);

EXPECT_EQ(layout_type::row_major, ra.layout());

}

{

SCOPED_TRACE("column_major constructor");

column_major_result<> cm;

pyarray<int> ca(cm.m_shape, layout_type::column_major);

compare_shape(ca, cm);

EXPECT_EQ(layout_type::column_major, ca.layout());

}

TEST(pyarray, from_shape)

{

auto arr = pyarray<double>::from_shape({5, 2, 6});

auto exp_shape = std::vector<std::size_t>{5, 2, 6};

EXPECT_TRUE(std::equal(arr.shape().begin(), arr.shape().end(), exp_shape.begin()));

EXPECT_EQ(arr.shape().size(), 3);

EXPECT_EQ(arr.size(), 5 * 2 * 6);

}

TEST(pyarray, strided_constructor)

{

central_major_result<> cmr;

pyarray<int> cma(cmr.m_shape, cmr.m_strides);

compare_shape(cma, cmr);

}

TEST(pyarray, valued_constructor)

{

SCOPED_TRACE("row_major valued constructor");

row_major_result<> rm;

int value = 2;

pyarray<int> ra(rm.m_shape, value);

compare_shape(ra, rm);

std::vector<int> vec(ra.size(), value);

EXPECT_TRUE(std::equal(vec.cbegin(), vec.cend(), ra.storage().cbegin()));

}

{

SCOPED_TRACE("column_major valued constructor");

column_major_result<> cm;

int value = 2;

pyarray<int> ca(cm.m_shape, value, layout_type::column_major);

compare_shape(ca, cm);

std::vector<int> vec(ca.size(), value);

EXPECT_TRUE(std::equal(vec.cbegin(), vec.cend(), ca.storage().cbegin()));

}

TEST(pyarray, strided_valued_constructor)

{

central_major_result<> cmr;

int value = 2;

pyarray<int> cma(cmr.m_shape, cmr.m_strides, value);

compare_shape(cma, cmr);

std::vector<int> vec(cma.size(), value);

EXPECT_TRUE(std::equal(vec.cbegin(), vec.cend(), cma.storage().cbegin()));

}

TEST(pyarray, copy_semantic)

{

central_major_result<> res;

int value = 2;

pyarray<int> a(res.m_shape, res.m_strides, value);

{

SCOPED_TRACE("copy constructor");

pyarray<int> b(a);

compare_shape(a, b);

EXPECT_EQ(a.storage(), b.storage());

a.data()[0] += 1;

EXPECT_NE(a.storage()[0], b.storage()[0]);

}

{

SCOPED_TRACE("assignment operator");

row_major_result<> r;

pyarray<int> c(r.m_shape, 0);

EXPECT_NE(a.storage(), c.storage());

c = a;

compare_shape(a, c);

EXPECT_EQ(a.storage(), c.storage());

a.data()[0] += 1;

EXPECT_NE(a.storage()[0], c.storage()[0]);

}

TEST(pyarray, move_semantic)

{

central_major_result<> res;

int value = 2;

pyarray<int> a(res.m_shape, res.m_strides, value);

{

SCOPED_TRACE("move constructor");

pyarray<int> tmp(a);

pyarray<int> b(std::move(tmp));

compare_shape(a, b);

EXPECT_EQ(a.storage(), b.storage());

}

{

SCOPED_TRACE("move assignment");

row_major_result<> r;

pyarray<int> c(r.m_shape, 0);

EXPECT_NE(a.storage(), c.storage());

pyarray<int> tmp(a);

c = std::move(tmp);

compare_shape(a, c);

EXPECT_EQ(a.storage(), c.storage());

}

TEST(pyarray, extended_constructor)

{

xt::xarray<int> a1 = { { 1, 2 },{ 3, 4 } };

xt::xarray<int> a2 = { { 1, 2 },{ 3, 4 } };

pyarray<int> c = a1 + a2;

EXPECT_EQ(c(0, 0), a1(0, 0) + a2(0, 0));

EXPECT_EQ(c(0, 1), a1(0, 1) + a2(0, 1));

EXPECT_EQ(c(1, 0), a1(1, 0) + a2(1, 0));

EXPECT_EQ(c(1, 1), a1(1, 1) + a2(1, 1));

}

TEST(pyarray, resize)

{

pyarray<int> a;

test_resize(a);

pyarray<int> b = { {1, 2}, {3, 4} };

a.resize(b.shape());

EXPECT_EQ(a.shape(), b.shape());

}

TEST(pyarray, transpose)

{

pyarray<int> a;

test_transpose(a);

}

TEST(pyarray, access)

{

pyarray<int> a;

test_access(a);

}

TEST(pyarray, indexed_access)

{

pyarray<int> a;

test_indexed_access(a);

}

TEST(pyarray, broadcast_shape)

{

pyarray<int> a;

test_broadcast(a);

test_broadcast2(a);

}

TEST(pyarray, iterator)

{

pyarray<int> a;

pyarray<int> b;

test_iterator(a, b);

pyarray<int, layout_type::row_major> c;

bool truthy = std::is_same<decltype(c.begin()), int*>::value;

EXPECT_TRUE(truthy);

}

TEST(pyarray, initializer_list)

{

pyarray<int> a0(1);

pyarray<int> a1({1, 2});

pyarray<int> a2({{1, 2}, {2, 4}, {5, 6}});

EXPECT_EQ(1, a0());

EXPECT_EQ(2, a1(1));

EXPECT_EQ(4, a2(1, 1));

}

TEST(pyarray, zerod)

{

pyarray<int> a;

EXPECT_EQ(0, a());

}

TEST(pyarray, reshape)

{

pyarray<int> a = {{1,2,3}, {4,5,6}};

auto ptr = a.data();

a.reshape({1, 6});

std::vector<std::size_t> sc1({1, 6});

EXPECT_TRUE(std::equal(sc1.begin(), sc1.end(), a.shape().begin()) && a.shape().size() == 2);

EXPECT_EQ(ptr, a.data());

a.reshape({6});

std::vector<std::size_t> sc2 = {6};

EXPECT_TRUE(std::equal(sc2.begin(), sc2.end(), a.shape().begin()) && a.shape().size() == 1);

EXPECT_EQ(ptr, a.data());

}

TEST(pyarray, view)

{

xt::pyarray<int> arr = xt::zeros<int>({ 10 });

auto v = xt::view(arr, xt::all());

EXPECT_EQ(v(0), 0.);

}

TEST(pyarray, zerod_copy)

{

xt::pyarray<int> arr = 2;

xt::pyarray<int> arr2(arr);

EXPECT_EQ(arr(), arr2());

}

xtensor-python/test/test_pyarray.cpp at master · robertodr/xtensor-python · GitHub

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