//
// 	Copyright (c) 2018-2020, Cem Bassoy, cem.bassoy@gmail.com
// 	Copyright (c) 2019-2020, Amit Singh, amitsingh19975@gmail.com
//
//  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
//  Google and Fraunhofer IOSB, Ettlingen, Germany
//
//  And we acknowledge the support from all contributors.


#include <iostream>
#include <algorithm>
#include <boost/numeric/ublas/tensor.hpp>

#include <boost/test/unit_test.hpp>

#include "utility.hpp"

BOOST_AUTO_TEST_SUITE ( test_einstein_notation, * boost::unit_test::depends_on("test_multi_index") )


using test_types = zip<int,float,std::complex<float>>::with_t<boost::numeric::ublas::first_order, boost::numeric::ublas::last_order>;

//using test_types = zip<int>::with_t<boost::numeric::ublas::first_order>;

BOOST_AUTO_TEST_CASE_TEMPLATE( test_einstein_multiplication, value,  test_types )
{
	using namespace boost::numeric::ublas;
	using value_type   = typename value::first_type;
	using layout_type  = typename value::second_type;
	using extents_type  = dynamic_extents<>;
	using tensor_type  = tensor<value_type,extents_type,layout_type>;
	using namespace boost::numeric::ublas::index;
	
	{
		auto A = tensor_type{5,3};
		auto B = tensor_type{3,4};
		//		auto C = tensor_type{4,5,6};

		for(auto j = 0u; j < A.extents().at(1); ++j)
			for(auto i = 0u; i < A.extents().at(0); ++i)
				A.at( i,j ) = value_type( static_cast< inner_type_t<value_type> >(i+1) );

		for(auto j = 0u; j < B.extents().at(1); ++j)
			for(auto i = 0u; i < B.extents().at(0); ++i)
				B.at( i,j ) = value_type( static_cast< inner_type_t<value_type> >(i+1) );



		auto AB = A(_,_e) * B(_e,_);

		//		std::cout << "A = " << A << std::endl;
		//		std::cout << "B = " << B << std::endl;
		//		std::cout << "AB = " << AB << std::endl;

		for(auto j = 0u; j < AB.extents().at(1); ++j)
			for(auto i = 0u; i < AB.extents().at(0); ++i)
				BOOST_CHECK_EQUAL( AB.at( i,j ) , value_type(A.at( i,0 ) * ( B.extents().at(0) * (B.extents().at(0)+1) / 2 )) );


	}


	{
		auto A = tensor_type{4,5,3};
		auto B = tensor_type{3,4,2};

		for(auto k = 0u; k < A.extents().at(2); ++k)
			for(auto j = 0u; j < A.extents().at(1); ++j)
				for(auto i = 0u; i < A.extents().at(0); ++i)
					A.at( i,j,k ) = value_type( static_cast< inner_type_t<value_type> >(i+1) );

		for(auto k = 0u; k < B.extents().at(2); ++k)
			for(auto j = 0u; j < B.extents().at(1); ++j)
				for(auto i = 0u; i < B.extents().at(0); ++i)
					B.at( i,j,k ) = value_type( static_cast< inner_type_t<value_type> >(i+1) );

		auto AB = A(_d,_,_f) * B(_f,_d,_);

		//		std::cout << "A = " << A << std::endl;
		//		std::cout << "B = " << B << std::endl;
		//		std::cout << "AB = " << AB << std::endl;
		// n*(n+1)/2;
		auto const nf = ( B.extents().at(0) * (B.extents().at(0)+1) / 2 );
		auto const nd = ( A.extents().at(0) * (A.extents().at(0)+1) / 2 );

		for(auto j = 0u; j < AB.extents().at(1); ++j)
			for(auto i = 0u; i < AB.extents().at(0); ++i)
				BOOST_CHECK_EQUAL( AB.at( i,j ) ,  value_type( static_cast< inner_type_t<value_type> >(nf * nd) ) );

	}


	{
		auto A = tensor_type{4,3};
		auto B = tensor_type{3,4,2};

		for(auto j = 0u; j < A.extents().at(1); ++j)
			for(auto i = 0u; i < A.extents().at(0); ++i)
				A.at( i,j ) = value_type( static_cast< inner_type_t<value_type> >(i+1) );

		for(auto k = 0u; k < B.extents().at(2); ++k)
			for(auto j = 0u; j < B.extents().at(1); ++j)
				for(auto i = 0u; i < B.extents().at(0); ++i)
					B.at( i,j,k ) = value_type( static_cast< inner_type_t<value_type> >(i+1) );

		auto AB = A(_d,_f) * B(_f,_d,_);

		// n*(n+1)/2;
		auto const nf = ( B.extents().at(0) * (B.extents().at(0)+1) / 2 );
		auto const nd = ( A.extents().at(0) * (A.extents().at(0)+1) / 2 );

		for(auto i = 0u; i < AB.extents().at(0); ++i)
			BOOST_CHECK_EQUAL ( AB.at( i  ) ,  value_type( static_cast< inner_type_t<value_type> >(nf * nd) ) );

	}
}

BOOST_AUTO_TEST_SUITE_END()