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.

         Redistribution and use in source and binary forms, with or without
         modification, are permitted provided that the following conditions are met:

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         list of conditions and the following disclaimer.
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         National Laboratory, U.S. Dept. of Energy nor the names of its contributors may
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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 ) throw std::runtime_error("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 ) throw std::runtime_error("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 ) throw std::runtime_error("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 ) throw std::runtime_error("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 ){
      throw std::logic_error("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 ) throw std::runtime_error("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_ ) {
      throw std::logic_error( "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_ ) {
      throw std::logic_error( "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_ ) {
      throw std::logic_error( "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_ ) {
      throw std::logic_error( "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_