140 lines
4.7 KiB
C++
140 lines
4.7 KiB
C++
//
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// Copyright (c) 2018-2019, Cem Bassoy, cem.bassoy@gmail.com
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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 IOSB, Ettlingen, Germany
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//
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#include <boost/numeric/ublas/tensor.hpp>
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#include <boost/numeric/ublas/matrix.hpp>
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#include <boost/numeric/ublas/vector.hpp>
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#include <iostream>
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int main()
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{
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using namespace boost::numeric::ublas;
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using format_t = column_major;
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using value_t = float;
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using tensor_t = tensor<value_t,format_t>;
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using matrix_t = matrix<value_t,format_t>;
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using namespace boost::numeric::ublas::index;
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// Tensor-Vector-Multiplications - Including Transposition
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{
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auto n = shape{3,4,2};
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auto A = tensor_t(n,1);
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auto B1 = matrix_t(n[1],n[2],2);
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auto v1 = tensor_t(shape{n[0],1},2);
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auto v2 = tensor_t(shape{n[1],1},2);
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// auto v3 = tensor_t(shape{n[2],1},2);
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// C1(j,k) = B1(j,k) + A(i,j,k)*v1(i);
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// tensor_t C1 = B1 + prod(A,vector_t(n[0],1),1);
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// tensor_t C1 = B1 + A(_i,_,_) * v1(_i,_);
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// C2(i,k) = A(i,j,k)*v2(j) + 4;
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//tensor_t C2 = prod(A,vector_t(n[1],1),2) + 4;
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// tensor_t C2 = A(_,_i,_) * v2(_i,_) + 4;
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// not yet implemented!
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// C3() = A(i,j,k)*T1(i)*T2(j)*T2(k);
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// tensor_t C3 = prod(prod(prod(A,v1,1),v2,1),v3,1);
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// tensor_t C3 = A(_i,_j,_k) * v1(_i,_) * v2(_j,_) * v3(_k,_);
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// formatted output
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std::cout << "% --------------------------- " << std::endl;
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std::cout << "% --------------------------- " << std::endl << std::endl;
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std::cout << "% C1(j,k) = B1(j,k) + A(i,j,k)*v1(i);" << std::endl << std::endl;
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// std::cout << "C1=" << C1 << ";" << std::endl << std::endl;
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// formatted output
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std::cout << "% --------------------------- " << std::endl;
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std::cout << "% --------------------------- " << std::endl << std::endl;
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std::cout << "% C2(i,k) = A(i,j,k)*v2(j) + 4;" << std::endl << std::endl;
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// std::cout << "C2=" << C2 << ";" << std::endl << std::endl;
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}
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// Tensor-Matrix-Multiplications - Including Transposition
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{
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auto n = shape{3,4,2};
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auto m = 5u;
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auto A = tensor_t(n,2);
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auto B = tensor_t(shape{n[1],n[2],m},2);
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auto B1 = tensor_t(shape{m,n[0]},1);
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auto B2 = tensor_t(shape{m,n[1]},1);
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// C1(l,j,k) = B(j,k,l) + A(i,j,k)*B1(l,i);
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// tensor_t C1 = B + prod(A,B1,1);
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// tensor_t C1 = B + A(_i,_,_) * B1(_,_i);
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// C2(i,l,k) = A(i,j,k)*B2(l,j) + 4;
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// tensor_t C2 = prod(A,B2) + 4;
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// tensor_t C2 = A(_,_j,_) * B2(_,_j) + 4;
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// C3(i,l1,l2) = A(i,j,k)*T1(l1,j)*T2(l2,k);
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// not yet implemented.
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// formatted output
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std::cout << "% --------------------------- " << std::endl;
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std::cout << "% --------------------------- " << std::endl << std::endl;
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std::cout << "% C1(l,j,k) = B(j,k,l) + A(i,j,k)*B1(l,i);" << std::endl << std::endl;
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// std::cout << "C1=" << C1 << ";" << std::endl << std::endl;
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// formatted output
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std::cout << "% --------------------------- " << std::endl;
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std::cout << "% --------------------------- " << std::endl << std::endl;
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std::cout << "% C2(i,l,k) = A(i,j,k)*B2(l,j) + 4;" << std::endl << std::endl;
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// std::cout << "C2=" << C2 << ";" << std::endl << std::endl;
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// // formatted output
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// std::cout << "% --------------------------- " << std::endl;
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// std::cout << "% --------------------------- " << std::endl << std::endl;
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// std::cout << "% C3(i,l1,l2) = A(i,j,k)*T1(l1,j)*T2(l2,k);" << std::endl << std::endl;
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// std::cout << "C3=" << C3 << ";" << std::endl << std::endl;
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}
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// Tensor-Tensor-Multiplications Including Transposition
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{
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auto na = shape{3,4,5};
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auto nb = shape{4,6,3,2};
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auto A = tensor_t(na,2);
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auto B = tensor_t(nb,3);
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auto T1 = tensor_t(shape{na[2],na[2]},2);
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auto T2 = tensor_t(shape{na[2],nb[1],nb[3]},2);
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// C1(j,l) = T1(j,l) + A(i,j,k)*A(i,j,l) + 5;
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// tensor_t C1 = T1 + prod(A,A,perm_t{1,2}) + 5;
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// tensor_t C1 = T1 + A(_i,_j,_m)*A(_i,_j,_l) + 5;
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// formatted output
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std::cout << "% --------------------------- " << std::endl;
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std::cout << "% --------------------------- " << std::endl << std::endl;
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std::cout << "% C1(k,l) = T1(k,l) + A(i,j,k)*A(i,j,l) + 5;" << std::endl << std::endl;
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// std::cout << "C1=" << C1 << ";" << std::endl << std::endl;
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// C2(k,l,m) = T2(k,l,m) + A(i,j,k)*B(j,l,i,m) + 5;
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//tensor_t C2 = T2 + prod(A,B,perm_t{1,2},perm_t{3,1}) + 5;
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// tensor_t C2 = T2 + A(_i,_j,_k)*B(_j,_l,_i,_m) + 5;
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// formatted output
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std::cout << "% --------------------------- " << std::endl;
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std::cout << "% --------------------------- " << std::endl << std::endl;
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std::cout << "% C2(k,l,m) = T2(k,l,m) + A(i,j,k)*B(j,l,i,m) + 5;" << std::endl << std::endl;
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// std::cout << "C2=" << C2 << ";" << std::endl << std::endl;
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}
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}
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