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-rw-r--r--src/boost/libs/numeric/ublas/test/tensor/test_tensor_matrix_vector.cpp472
1 files changed, 472 insertions, 0 deletions
diff --git a/src/boost/libs/numeric/ublas/test/tensor/test_tensor_matrix_vector.cpp b/src/boost/libs/numeric/ublas/test/tensor/test_tensor_matrix_vector.cpp
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index 000000000..3e34047dd
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+++ b/src/boost/libs/numeric/ublas/test/tensor/test_tensor_matrix_vector.cpp
@@ -0,0 +1,472 @@
+// 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 <iostream>
+#include <random>
+#include <boost/numeric/ublas/tensor.hpp>
+#include <boost/numeric/ublas/matrix.hpp>
+#include <boost/test/unit_test.hpp>
+
+#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<int,long,float,double>::with_t<boost::numeric::ublas::first_order, boost::numeric::ublas::last_order>;
+
+
+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<value_type, layout_type>;
+ 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<value_type, layout_type>;
+ 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<std::size_t>;
+ 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_type> 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<value_type, layout_type>;
+ 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<value_type, layout_type>;
+ 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<value_type, layout_type>;
+ 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<value_type, layout_type>;
+ 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<value_type, layout_type>;
+ 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<value_type, layout_type>;
+ 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<value_type, layout_type>;
+ 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<value_type, layout_type>;
+ 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<value_type, layout_type>;
+ 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()
+
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