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