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:

(1) Redistributions of source code must retain the above copyright notice, this
list of conditions and the following disclaimer.
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and/or other materials provided with the distribution.
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National Laboratory, U.S. Dept. of Energy nor the names of its contributors may
be used to endorse or promote products derived from this software without
specific prior written permission.

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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 ) {
#ifdef USE_ABORT
      abort();
#endif
      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 ) {
#ifdef USE_ABORT
        abort();
#endif
        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 ) {
#ifdef USE_ABORT
          abort();
#endif
          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 ) {
#ifdef USE_ABORT
        abort();
#endif
        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 ){
#ifdef USE_ABORT
      abort();
#endif
      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 ) {
#ifdef USE_ABORT
        abort();
#endif
        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_ ) {
#ifdef USE_ABORT
      abort();
#endif
      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_ ) {
#ifdef USE_ABORT
      abort();
#endif
      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_ ) {
#ifdef USE_ABORT
      abort();
#endif
      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_ ) {
#ifdef USE_ABORT
      abort();
#endif
      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_