// 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 #include #include #include #include #include "utility.hpp" // BOOST_AUTO_TEST_SUITE ( test_tensor_matrix_interoperability, * boost::unit_test::depends_on("test_tensor") ) ; BOOST_AUTO_TEST_SUITE ( test_tensor_matrix_interoperability ) using test_types = zip::with_t; BOOST_AUTO_TEST_CASE_TEMPLATE( test_tensor_matrix_copy_ctor, value, test_types) { using namespace boost::numeric; using value_type = typename value::first_type; using layout_type = typename value::second_type; using tensor_type = ublas::tensor; using matrix_type = typename tensor_type::matrix_type; tensor_type a1 = matrix_type(); BOOST_CHECK_EQUAL( a1.size() , 0ul ); BOOST_CHECK( a1.empty() ); BOOST_CHECK_EQUAL( a1.data() , nullptr); tensor_type a2 = matrix_type(1,1); BOOST_CHECK_EQUAL( a2.size() , 1 ); BOOST_CHECK( !a2.empty() ); BOOST_CHECK_NE( a2.data() , nullptr); tensor_type a3 = matrix_type(2,1); BOOST_CHECK_EQUAL( a3.size() , 2 ); BOOST_CHECK( !a3.empty() ); BOOST_CHECK_NE( a3.data() , nullptr); tensor_type a4 = matrix_type(1,2); BOOST_CHECK_EQUAL( a4.size() , 2 ); BOOST_CHECK( !a4.empty() ); BOOST_CHECK_NE( a4.data() , nullptr); tensor_type a5 = matrix_type(2,3); BOOST_CHECK_EQUAL( a5.size() , 6 ); BOOST_CHECK( !a5.empty() ); BOOST_CHECK_NE( a5.data() , nullptr); } BOOST_AUTO_TEST_CASE_TEMPLATE( test_tensor_vector_copy_ctor, value, test_types) { using namespace boost::numeric; using value_type = typename value::first_type; using layout_type = typename value::second_type; using tensor_type = ublas::tensor; using vector_type = typename tensor_type::vector_type; tensor_type a1 = vector_type(); BOOST_CHECK_EQUAL( a1.size() , 0ul ); BOOST_CHECK( a1.empty() ); BOOST_CHECK_EQUAL( a1.data() , nullptr); tensor_type a2 = vector_type(1); BOOST_CHECK_EQUAL( a2.size() , 1 ); BOOST_CHECK( !a2.empty() ); BOOST_CHECK_NE( a2.data() , nullptr); tensor_type a3 = vector_type(2); BOOST_CHECK_EQUAL( a3.size() , 2 ); BOOST_CHECK( !a3.empty() ); BOOST_CHECK_NE( a3.data() , nullptr); tensor_type a4 = vector_type(2); BOOST_CHECK_EQUAL( a4.size() , 2 ); BOOST_CHECK( !a4.empty() ); BOOST_CHECK_NE( a4.data() , nullptr); tensor_type a5 = vector_type(3); BOOST_CHECK_EQUAL( a5.size() , 3 ); BOOST_CHECK( !a5.empty() ); BOOST_CHECK_NE( a5.data() , nullptr); } struct fixture { using extents_type = boost::numeric::ublas::basic_extents; fixture() : extents{ extents_type{1,1}, // 1 extents_type{1,2}, // 2 extents_type{2,1}, // 3 extents_type{2,3}, // 4 extents_type{9,7}, // 5 extents_type{9,11}, // 6 extents_type{12,12}, // 7 extents_type{15,17}} // 8 { } std::vector extents; }; BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_matrix_copy_ctor_extents, 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; using matrix_type = typename tensor_type::matrix_type; auto check = [](auto const& e) { assert(e.size()==2); tensor_type t = matrix_type{e[0],e[1]}; BOOST_CHECK_EQUAL ( t.size() , e.product() ); BOOST_CHECK_EQUAL ( t.rank() , e.size() ); BOOST_CHECK ( !t.empty() ); BOOST_CHECK_NE ( t.data() , nullptr); }; for(auto const& e : extents) check(e); } BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_vector_copy_ctor_extents, 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; using vector_type = typename tensor_type::vector_type; auto check = [](auto const& e) { assert(e.size()==2); if(e.empty()) return; tensor_type t = vector_type(e.product()); BOOST_CHECK_EQUAL ( t.size() , e.product() ); BOOST_CHECK_EQUAL ( t.rank() , e.size() ); BOOST_CHECK ( !t.empty() ); BOOST_CHECK_NE ( t.data() , nullptr); }; for(auto const& e : extents) check(e); } BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_matrix_copy_assignment, 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; using matrix_type = typename tensor_type::matrix_type; auto check = [](auto const& e) { assert(e.size() == 2); auto t = tensor_type{}; auto r = matrix_type(e[0],e[1]); std::iota(r.data().begin(),r.data().end(), 1); t = r; BOOST_CHECK_EQUAL ( t.extents().at(0) , e.at(0) ); BOOST_CHECK_EQUAL ( t.extents().at(1) , e.at(1) ); BOOST_CHECK_EQUAL ( t.size() , e.product() ); BOOST_CHECK_EQUAL ( t.rank() , e.size() ); BOOST_CHECK ( !t.empty() ); BOOST_CHECK_NE ( t.data() , nullptr); for(auto j = 0ul; j < t.size(1); ++j){ for(auto i = 0ul; i < t.size(0); ++i){ BOOST_CHECK_EQUAL( t.at(i,j), r(i,j) ); } } }; for(auto const& e : extents) check(e); } BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_vector_copy_assignment, 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; using vector_type = typename tensor_type::vector_type; auto check = [](auto const& e) { assert(e.size() == 2); auto t = tensor_type{}; auto r = vector_type(e[0]*e[1]); std::iota(r.data().begin(),r.data().end(), 1); t = r; BOOST_CHECK_EQUAL ( t.extents().at(0) , e.at(0)*e.at(1) ); BOOST_CHECK_EQUAL ( t.extents().at(1) , 1); BOOST_CHECK_EQUAL ( t.size() , e.product() ); BOOST_CHECK_EQUAL ( t.rank() , e.size() ); BOOST_CHECK ( !t.empty() ); BOOST_CHECK_NE ( t.data() , nullptr); for(auto i = 0ul; i < t.size(); ++i){ BOOST_CHECK_EQUAL( t[i], r(i) ); } }; for(auto const& e : extents) check(e); } BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_matrix_move_assignment, 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; using matrix_type = typename tensor_type::matrix_type; auto check = [](auto const& e) { assert(e.size() == 2); auto t = tensor_type{}; auto r = matrix_type(e[0],e[1]); std::iota(r.data().begin(),r.data().end(), 1); auto q = r; t = std::move(r); BOOST_CHECK_EQUAL ( t.extents().at(0) , e.at(0) ); BOOST_CHECK_EQUAL ( t.extents().at(1) , e.at(1) ); BOOST_CHECK_EQUAL ( t.size() , e.product() ); BOOST_CHECK_EQUAL ( t.rank() , e.size() ); BOOST_CHECK ( !t.empty() ); BOOST_CHECK_NE ( t.data() , nullptr); for(auto j = 0ul; j < t.size(1); ++j){ for(auto i = 0ul; i < t.size(0); ++i){ BOOST_CHECK_EQUAL( t.at(i,j), q(i,j) ); } } }; for(auto const& e : extents) check(e); } BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_vector_move_assignment, 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; using vector_type = typename tensor_type::vector_type; auto check = [](auto const& e) { assert(e.size() == 2); auto t = tensor_type{}; auto r = vector_type(e[0]*e[1]); std::iota(r.data().begin(),r.data().end(), 1); auto q = r; t = std::move(r); BOOST_CHECK_EQUAL ( t.extents().at(0) , e.at(0) * e.at(1)); BOOST_CHECK_EQUAL ( t.extents().at(1) , 1); BOOST_CHECK_EQUAL ( t.size() , e.product() ); BOOST_CHECK_EQUAL ( t.rank() , e.size() ); BOOST_CHECK ( !t.empty() ); BOOST_CHECK_NE ( t.data() , nullptr); for(auto i = 0ul; i < t.size(); ++i){ BOOST_CHECK_EQUAL( t[i], q(i) ); } }; for(auto const& e : extents) check(e); } BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_matrix_expressions, 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; using matrix_type = typename tensor_type::matrix_type; auto check = [](auto const& e) { assert(e.size() == 2); auto t = tensor_type{}; auto r = matrix_type(e[0],e[1]); std::iota(r.data().begin(),r.data().end(), 1); t = r + 3*r; tensor_type s = r + 3*r; tensor_type q = s + r + 3*r + s; // + 3*r BOOST_CHECK_EQUAL ( t.extents().at(0) , e.at(0) ); BOOST_CHECK_EQUAL ( t.extents().at(1) , e.at(1) ); BOOST_CHECK_EQUAL ( t.size() , e.product() ); BOOST_CHECK_EQUAL ( t.rank() , e.size() ); BOOST_CHECK ( !t.empty() ); BOOST_CHECK_NE ( t.data() , nullptr); BOOST_CHECK_EQUAL ( s.extents().at(0) , e.at(0) ); BOOST_CHECK_EQUAL ( s.extents().at(1) , e.at(1) ); BOOST_CHECK_EQUAL ( s.size() , e.product() ); BOOST_CHECK_EQUAL ( s.rank() , e.size() ); BOOST_CHECK ( !s.empty() ); BOOST_CHECK_NE ( s.data() , nullptr); BOOST_CHECK_EQUAL ( q.extents().at(0) , e.at(0) ); BOOST_CHECK_EQUAL ( q.extents().at(1) , e.at(1) ); BOOST_CHECK_EQUAL ( q.size() , e.product() ); BOOST_CHECK_EQUAL ( q.rank() , e.size() ); BOOST_CHECK ( !q.empty() ); BOOST_CHECK_NE ( q.data() , nullptr); for(auto j = 0ul; j < t.size(1); ++j){ for(auto i = 0ul; i < t.size(0); ++i){ BOOST_CHECK_EQUAL( t.at(i,j), 4*r(i,j) ); BOOST_CHECK_EQUAL( s.at(i,j), t.at(i,j) ); BOOST_CHECK_EQUAL( q.at(i,j), 3*s.at(i,j) ); } } }; for(auto const& e : extents) check(e); } BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_vector_expressions, 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; using vector_type = typename tensor_type::vector_type; auto check = [](auto const& e) { assert(e.size() == 2); auto t = tensor_type{}; auto r = vector_type(e[0]*e[1]); std::iota(r.data().begin(),r.data().end(), 1); t = r + 3*r; tensor_type s = r + 3*r; tensor_type q = s + r + 3*r + s; // + 3*r BOOST_CHECK_EQUAL ( t.extents().at(0) , e.at(0)*e.at(1) ); BOOST_CHECK_EQUAL ( t.extents().at(1) , 1); BOOST_CHECK_EQUAL ( t.size() , e.product() ); BOOST_CHECK_EQUAL ( t.rank() , e.size() ); BOOST_CHECK ( !t.empty() ); BOOST_CHECK_NE ( t.data() , nullptr); BOOST_CHECK_EQUAL ( s.extents().at(0) , e.at(0)*e.at(1) ); BOOST_CHECK_EQUAL ( s.extents().at(1) , 1); BOOST_CHECK_EQUAL ( s.size() , e.product() ); BOOST_CHECK_EQUAL ( s.rank() , e.size() ); BOOST_CHECK ( !s.empty() ); BOOST_CHECK_NE ( s.data() , nullptr); BOOST_CHECK_EQUAL ( q.extents().at(0) , e.at(0)*e.at(1) ); BOOST_CHECK_EQUAL ( q.extents().at(1) , 1); BOOST_CHECK_EQUAL ( q.size() , e.product() ); BOOST_CHECK_EQUAL ( q.rank() , e.size() ); BOOST_CHECK ( !q.empty() ); BOOST_CHECK_NE ( q.data() , nullptr); for(auto i = 0ul; i < t.size(); ++i){ BOOST_CHECK_EQUAL( t.at(i), 4*r(i) ); BOOST_CHECK_EQUAL( s.at(i), t.at(i) ); BOOST_CHECK_EQUAL( q.at(i), 3*s.at(i) ); } }; for(auto const& e : extents) check(e); } BOOST_FIXTURE_TEST_CASE_TEMPLATE( test_tensor_matrix_vector_expressions, 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; using matrix_type = typename tensor_type::matrix_type; using vector_type = typename tensor_type::vector_type; auto check = [](auto const& e) { if(e.product() <= 2) return; assert(e.size() == 2); auto Q = tensor_type{e[0],1}; auto A = matrix_type(e[0],e[1]); auto b = vector_type(e[1]); auto c = vector_type(e[0]); std::iota(b.data().begin(),b.data().end(), 1); std::fill(A.data().begin(),A.data().end(), 1); std::fill(c.data().begin(),c.data().end(), 2); std::fill(Q.begin(),Q.end(), 2); tensor_type T = Q + (ublas::prod(A , b) + 2*c) + 3*Q; BOOST_CHECK_EQUAL ( T.extents().at(0) , Q.extents().at(0) ); BOOST_CHECK_EQUAL ( T.extents().at(1) , Q.extents().at(1)); BOOST_CHECK_EQUAL ( T.size() , Q.size() ); BOOST_CHECK_EQUAL ( T.size() , c.size() ); BOOST_CHECK_EQUAL ( T.rank() , Q.rank() ); BOOST_CHECK ( !T.empty() ); BOOST_CHECK_NE ( T.data() , nullptr); for(auto i = 0ul; i < T.size(); ++i){ auto n = e[1]; auto ab = n * (n+1) / 2; BOOST_CHECK_EQUAL( T(i), ab+4*Q(0)+2*c(0) ); } }; for(auto const& e : extents) check(e); } BOOST_AUTO_TEST_SUITE_END()