NumTns_impl.hpp

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/*
   Copyright (c) 2012 The Regents of the University of California,
   through Lawrence Berkeley National Laboratory.  

Authors: Lexing Ying, Mathias Jacquelin and Lin Lin

This file is part of PEXSI. All rights reserved.

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modification, are permitted provided that the following conditions are met:

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 */
#ifndef _PEXSI_NUMTNS_IMPL_HPP_
#define _PEXSI_NUMTNS_IMPL_HPP_


namespace  PEXSI{

template <class F> NumTns<F>::NumTns(Int m, Int n, Int p): m_(m), n_(n), p_(p), owndata_(true) {
  if(m_>0 && n_>0 && p_>0) { data_ = new F[m_*n_*p_]; if( data_ == NULL ) {
    ErrorHandling("Cannot allocate memory.");}
  } else data_=NULL;
}

template <class F> NumTns<F>::NumTns(Int m, Int n, Int p, bool owndata, F* data): m_(m), n_(n), p_(p), owndata_(owndata) {
  if(owndata_) {
    if(m_>0 && n_>0 && p_>0) { data_ = new F[m_*n_*p_]; if( data_ == NULL ) {
      ErrorHandling("Cannot allocate memory.");}
    } else data_=NULL;
    if(m_>0 && n_>0 && p_>0) { for(Int i=0; i<m_*n_*p_; i++) data_[i] = data[i]; }
  } else {
    data_ = data;
  }
}

template <class F> NumTns<F>::NumTns(const NumTns<F>& C): m_(C.m_), n_(C.n_), p_(C.p_), owndata_(C.owndata_) {
  if(owndata_) {
    if(m_>0 && n_>0 && p_>0) { data_ = new F[m_*n_*p_]; 
      if( data_ == NULL ) {
        ErrorHandling("Cannot allocate memory.");} 
    } else data_=NULL;

    if(m_>0 && n_>0 && p_>0) { for(Int i=0; i<m_*n_*p_; i++) data_[i] = C.data_[i]; }
  } else {
    data_ = C.data_;
  }
}

template <class F> NumTns<F>::~NumTns() { 
  if(owndata_) { 
    if(m_>0 && n_>0 && p_>0) { delete[] data_; data_ = NULL; } 
  }
}

template <class F> NumTns<F>& NumTns<F>::operator=(const NumTns<F>& C) {
  if(owndata_) { 
    if(m_>0 && n_>0 && p_>0) { delete[] data_; data_ = NULL; } 
  }
  m_ = C.m_; n_=C.n_; p_=C.p_; owndata_=C.owndata_;
  if(owndata_) {
    if(m_>0 && n_>0 && p_>0) { data_ = new F[m_*n_*p_]; if( data_ == NULL ) {
      ErrorHandling("Cannot allocate memory.");} } else data_=NULL;
    if(m_>0 && n_>0 && p_>0) { for(Int i=0; i<m_*n_*p_; i++) data_[i] = C.data_[i]; }
  } else {
    data_ = C.data_;
  }
  return *this;
}

template <class F> void NumTns<F>::Resize(Int m, Int n, Int p)  {
  if( owndata_ == false ){
    ErrorHandling("Tensor being resized must own data.");
  }
  if(m_!=m || n_!=n || p_!=p) {
    if(m_>0 && n_>0 && p_>0) { delete[] data_; data_ = NULL; } 
    m_ = m; n_ = n; p_=p;
    if(m_>0 && n_>0 && p_>0) { data_ = new F[m_*n_*p_]; if( data_ == NULL ) {
      ErrorHandling("Cannot allocate memory.");}
    } else data_=NULL;
  }
}

template <class F> const F& NumTns<F>::operator()(Int i, Int j, Int k) const  {
  if( i < 0 || i >= m_ ||
      j < 0 || j >= n_ ||
      k < 0 || k >= p_ ) {
    ErrorHandling( "Index is out of bound." );
  }
  return data_[i+j*m_+k*m_*n_];
}

template <class F> F& NumTns<F>::operator()(Int i, Int j, Int k)  {
  if( i < 0 || i >= m_ ||
      j < 0 || j >= n_ ||
      k < 0 || k >= p_ ) {
    ErrorHandling( "Index is out of bound." );
  }
  return data_[i+j*m_+k*m_*n_];
}


template <class F> F* NumTns<F>::MatData (Int j) const {
  if( j < 0 || j >= p_ ) {
    ErrorHandling( "Index is out of bound." );
  }
  return &(data_[j*m_*n_]);
};

template <class F> F* NumTns<F>::VecData (Int j, Int k) const {
  if( j < 0 || j >= n_ ||
      k < 0 || k >= p_ ) {
    ErrorHandling( "Index is out of bound." );
  }

  return &(data_[k*m_*n_+j*m_]);
};

template <class F> inline void SetValue(NumTns<F>& T, F val)
{
  F *ptr = T.data_;
  for(Int i=0; i < T.m() * T.n() * T.p(); i++) *(ptr++) = val; 

  return;
}



template <class F> inline Real Energy(const NumTns<F>& T)
{
  Real sum = 0;

  F *ptr = T.Data();
  for(Int i=0; i < T.m() * T.n() * T.p(); i++) 
    sum += abs(ptr[i]) * abs(ptr[i]);

  return sum;
}

} // namespace PEXSI

#endif // _PEXSI_NUMTNS_IMPL_HPP_