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// Copyright (c) 2018-2019 Cem Bassoy
//
// Distributed under the Boost Software License, Version 1.0. (See
// accompanying file LICENSE_1_0.txt or copy at
// http://www.boost.org/LICENSE_1_0.txt)
//
// The authors gratefully acknowledge the support of
// Fraunhofer and Google in producing this work
// which started as a Google Summer of Code project.
//
#include <boost/numeric/ublas/tensor/expression.hpp>
#include <boost/numeric/ublas/tensor/tensor.hpp>
#include <boost/test/unit_test.hpp>
#include "utility.hpp"
#include <functional>
#include <complex>
using test_types = zip<int,long,float,double,std::complex<float>>::with_t<boost::numeric::ublas::first_order, boost::numeric::ublas::last_order>;
struct fixture
{
using extents_type = boost::numeric::ublas::shape;
fixture()
: extents {
extents_type{}, // 0
extents_type{1,1}, // 1
extents_type{1,2}, // 2
extents_type{2,1}, // 3
extents_type{2,3}, // 4
extents_type{2,3,1}, // 5
extents_type{1,2,3}, // 6
extents_type{1,1,2,3}, // 7
extents_type{1,2,3,1,1}, // 8
extents_type{4,2,3}, // 9
extents_type{4,2,1,3}, // 10
extents_type{4,2,1,3,1}, // 11
extents_type{1,4,2,1,3,1} } // 12
{
}
std::vector<extents_type> extents;
};
BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_expression_access, value, test_types, fixture)
{
using namespace boost::numeric;
using value_type = typename value::first_type;
using layout_type = typename value::second_type;
using tensor_type = ublas::tensor<value_type, layout_type>;
using tensor_expression_type = typename tensor_type::super_type;
for(auto const& e : extents) {
auto v = value_type{};
auto t = tensor_type(e);
for(auto& tt: t){ tt = v; v+=value_type{1}; }
const auto& tensor_expression_const = static_cast<tensor_expression_type const&>( t );
for(auto i = 0ul; i < t.size(); ++i)
BOOST_CHECK_EQUAL( tensor_expression_const()(i), t(i) );
}
}
BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_unary_expression, value, test_types, fixture)
{
using namespace boost::numeric;
using value_type = typename value::first_type;
using layout_type = typename value::second_type;
using tensor_type = ublas::tensor<value_type, layout_type>;
auto uplus1 = std::bind( std::plus<value_type>{}, std::placeholders::_1, value_type(1) );
for(auto const& e : extents) {
auto t = tensor_type(e);
auto v = value_type{};
for(auto& tt: t) { tt = v; v+=value_type{1}; }
const auto uexpr = ublas::detail::make_unary_tensor_expression<tensor_type>( t, uplus1 );
for(auto i = 0ul; i < t.size(); ++i)
BOOST_CHECK_EQUAL( uexpr(i), uplus1(t(i)) );
auto uexpr_uexpr = ublas::detail::make_unary_tensor_expression<tensor_type>( uexpr, uplus1 );
for(auto i = 0ul; i < t.size(); ++i)
BOOST_CHECK_EQUAL( uexpr_uexpr(i), uplus1(uplus1(t(i))) );
const auto & uexpr_e = uexpr.e;
BOOST_CHECK( ( std::is_same_v< std::decay_t< decltype(uexpr_e) >, tensor_type > ) );
const auto & uexpr_uexpr_e_e = uexpr_uexpr.e.e;
BOOST_CHECK( ( std::is_same_v< std::decay_t< decltype(uexpr_uexpr_e_e) >, tensor_type > ) );
}
}
BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_binary_expression, value, test_types, fixture)
{
using namespace boost::numeric;
using value_type = typename value::first_type;
using layout_type = typename value::second_type;
using tensor_type = ublas::tensor<value_type, layout_type>;
auto uplus1 = std::bind( std::plus<value_type>{}, std::placeholders::_1, value_type(1) );
auto uplus2 = std::bind( std::plus<value_type>{}, std::placeholders::_1, value_type(2) );
auto bplus = std::plus <value_type>{};
auto bminus = std::minus<value_type>{};
for(auto const& e : extents) {
auto t = tensor_type(e);
auto v = value_type{};
for(auto& tt: t){ tt = v; v+=value_type{1}; }
auto uexpr1 = ublas::detail::make_unary_tensor_expression<tensor_type>( t, uplus1 );
auto uexpr2 = ublas::detail::make_unary_tensor_expression<tensor_type>( t, uplus2 );
BOOST_CHECK( ( std::is_same_v< std::decay_t< decltype(uexpr1.e) >, tensor_type > ) );
BOOST_CHECK( ( std::is_same_v< std::decay_t< decltype(uexpr2.e) >, tensor_type > ) );
for(auto i = 0ul; i < t.size(); ++i)
BOOST_CHECK_EQUAL( uexpr1(i), uplus1(t(i)) );
for(auto i = 0ul; i < t.size(); ++i)
BOOST_CHECK_EQUAL( uexpr2(i), uplus2(t(i)) );
auto bexpr_uexpr = ublas::detail::make_binary_tensor_expression<tensor_type>( uexpr1, uexpr2, bplus );
BOOST_CHECK( ( std::is_same_v< std::decay_t< decltype(bexpr_uexpr.el.e) >, tensor_type > ) );
BOOST_CHECK( ( std::is_same_v< std::decay_t< decltype(bexpr_uexpr.er.e) >, tensor_type > ) );
for(auto i = 0ul; i < t.size(); ++i)
BOOST_CHECK_EQUAL( bexpr_uexpr(i), bplus(uexpr1(i),uexpr2(i)) );
auto bexpr_bexpr_uexpr = ublas::detail::make_binary_tensor_expression<tensor_type>( bexpr_uexpr, t, bminus );
BOOST_CHECK( ( std::is_same_v< std::decay_t< decltype(bexpr_bexpr_uexpr.el.el.e) >, tensor_type > ) );
BOOST_CHECK( ( std::is_same_v< std::decay_t< decltype(bexpr_bexpr_uexpr.el.er.e) >, tensor_type > ) );
BOOST_CHECK( ( std::is_same_v< std::decay_t< decltype(bexpr_bexpr_uexpr.er) >, tensor_type > ) );
BOOST_CHECK( ( std::is_same_v< std::decay_t< decltype(bexpr_bexpr_uexpr.er) >, tensor_type > ) );
for(auto i = 0ul; i < t.size(); ++i)
BOOST_CHECK_EQUAL( bexpr_bexpr_uexpr(i), bminus(bexpr_uexpr(i),t(i)) );
}
}
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