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//
// Copyright (c) 2018-2019, Cem Bassoy, cem.bassoy@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
// Fraunhofer IOSB, Ettlingen, Germany
//
#include <boost/numeric/ublas/tensor.hpp>
#include <boost/multiprecision/cpp_bin_float.hpp>
#include <ostream>
int main()
{
using namespace boost::numeric::ublas;
using namespace boost::multiprecision;
// creates a three-dimensional tensor with extents 3,4 and 2
// tensor A stores single-precision floating-point number according
// to the first-order storage format
using ftype = float;
auto A = tensor<ftype>{3,4,2};
// initializes the tensor with increasing values along the first-index
// using a single index.
auto vf = ftype(0);
for(auto i = 0u; i < A.size(); ++i, vf += ftype(1))
A[i] = vf;
// formatted output
std::cout << "% --------------------------- " << std::endl;
std::cout << "% --------------------------- " << std::endl << std::endl;
std::cout << "A=" << A << ";" << std::endl << std::endl;
// creates a four-dimensional tensor with extents 5,4,3 and 2
// tensor A stores complex floating-point extended double precision numbers
// according to the last-order storage format
// and initializes it with the default value.
using ctype = std::complex<cpp_bin_float_double_extended>;
auto B = tensor<ctype,last_order>(shape{5,4,3,2},ctype{});
// initializes the tensor with increasing values along the last-index
// using a single-index
auto vc = ctype(0,0);
for(auto i = 0u; i < B.size(); ++i, vc += ctype(1,1))
B[i] = vc;
// formatted output
std::cout << "% --------------------------- " << std::endl;
std::cout << "% --------------------------- " << std::endl << std::endl;
std::cout << "B=" << B << ";" << std::endl << std::endl;
auto C = tensor<ctype,last_order>(B.extents());
// computes the complex conjugate of elements of B
// using multi-index notation.
for(auto i = 0u; i < B.size(0); ++i)
for(auto j = 0u; j < B.size(1); ++j)
for(auto k = 0u; k < B.size(2); ++k)
for(auto l = 0u; l < B.size(3); ++l)
C.at(i,j,k,l) = std::conj(B.at(i,j,k,l));
std::cout << "% --------------------------- " << std::endl;
std::cout << "% --------------------------- " << std::endl << std::endl;
std::cout << "C=" << C << ";" << std::endl << std::endl;
// computes the complex conjugate of elements of B
// using iterators.
auto D = tensor<ctype,last_order>(B.extents());
std::transform(B.begin(), B.end(), D.begin(), [](auto const& b){ return std::conj(b); });
std::cout << "% --------------------------- " << std::endl;
std::cout << "% --------------------------- " << std::endl << std::endl;
std::cout << "D=" << D << ";" << std::endl << std::endl;
// reshaping tensors.
auto new_extents = B.extents().base();
std::next_permutation( new_extents.begin(), new_extents.end() );
D.reshape( shape(new_extents) );
std::cout << "% --------------------------- " << std::endl;
std::cout << "% --------------------------- " << std::endl << std::endl;
std::cout << "newD=" << D << ";" << std::endl << std::endl;
}
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