tensor3.h

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/*-------------------------------------------------------------------
Copyright 2011 Ravishankar Sundararaman

This file is part of JDFTx.

JDFTx is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.

JDFTx is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with JDFTx.  If not, see <http://www.gnu.org/licenses/>.
-------------------------------------------------------------------*/

#ifndef JDFTX_CORE_TENSOR3_H
#define JDFTX_CORE_TENSOR3_H


#include <core/scalar.h>
#include <vector>

#define LOOP5(code) { for(int k=0; k<5; k++) { code } }

template<typename scalar=double> class tensor3
{
        scalar v[5];
public:
        //Accessors
        __hostanddev__ scalar& operator[](int k) { return v[k]; }
        __hostanddev__ const scalar& operator[](int k) const { return v[k]; }
        __hostanddev__ scalar& xy() { return v[0]; }
        __hostanddev__ scalar& yz() { return v[1]; }
        __hostanddev__ scalar& zx() { return v[2]; }
        __hostanddev__ scalar& xxr() { return v[3]; } 
        __hostanddev__ scalar& yyr() { return v[4]; } 
        __hostanddev__ const scalar& xy() const { return v[0]; }
        __hostanddev__ const scalar& yz() const { return v[1]; }
        __hostanddev__ const scalar& zx() const { return v[2]; }
        __hostanddev__ const scalar& xxr() const { return v[3]; }
        __hostanddev__ const scalar& yyr() const { return v[4]; }

        explicit __hostanddev__ tensor3(scalar a=0, scalar b=0, scalar c=0, scalar d=0, scalar e=0) { v[0]=a; v[1]=b; v[2]=c; v[3]=d; v[4]=e; }
        tensor3(std::vector<scalar> a) { LOOP5( v[k]=a[k]; ) }
};

template<typename scalar> __hostanddev__ tensor3<scalar> loadTensor(const tensor3<const scalar*>& tArr, int i)
{       return tensor3<scalar>( tArr[0][i], tArr[1][i], tArr[2][i], tArr[3][i], tArr[4][i] );
}
template<typename scalar> __hostanddev__ tensor3<scalar> loadTensor(const tensor3<scalar*>& tArr, int i)
{       return tensor3<scalar>( tArr[0][i], tArr[1][i], tArr[2][i], tArr[3][i], tArr[4][i] );
}
template<typename scalar> __hostanddev__ void storeTensor(const tensor3<scalar>& t, tensor3<scalar*>& tArr, int i)
{       LOOP5( tArr[k][i] = t[k]; )
}
template<typename scalar> __hostanddev__ void accumTensor(const tensor3<scalar>& t, tensor3<scalar*>& tArr, int i)
{       LOOP5( tArr[k][i] += t[k]; )
}

#undef LOOP5
#endif // JDFTX_CORE_TENSOR3_H