NumMat_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_NUMMAT_IMPL_HPP_
#define _PEXSI_NUMMAT_IMPL_HPP_


namespace  PEXSI{

  template <class F> inline void NumMat<F>::allocate(F* data) {
    if(owndata_) {
      if(m_>0 && n_>0) { data_ = new F[m_*n_]; if( data_ == NULL ) {
#ifdef USE_ABORT
        abort();
#endif
        throw std::runtime_error("Cannot allocate memory.");}
      } else data_=NULL;
      if(data!=NULL){std::copy(data,data+m_*n_,data_);}
    } else {
      data_ = data;
    }
    bufsize_=m_*n_;
  }
  template <class F> inline void NumMat<F>::deallocate(){
    if(owndata_) {
      if(bufsize_>0) { delete[] data_; data_ = NULL; bufsize_ = 0; m_=0; n_=0; }
    }
  }

  template <class F> NumMat<F>::NumMat(Int m, Int n): m_(m), n_(n), owndata_(true) {
    this->allocate();
  }

  template <class F> NumMat<F>::NumMat(Int m, Int n, bool owndata, F* data): m_(m), n_(n), owndata_(owndata) {
    this->allocate(data);
  }

  template <class F> NumMat<F>::NumMat(const NumMat& C): m_(C.m_), n_(C.n_), owndata_(C.owndata_) {
    this->allocate(C.data_);
  }

  template <class F> NumMat<F>::~NumMat() {
    this->deallocate();
  }

  template <class F> NumMat<F>& NumMat<F>::Copy(const NumMat<F>& C) {
    this->deallocate();
    m_ = C.m_; n_=C.n_; owndata_=C.owndata_;
    this->allocate(C.data_);
    return *this;
  }

  template <class F> NumMat<F>& NumMat<F>::operator=(const NumMat<F>& C) {
    this->deallocate();
    m_ = C.m_; n_=C.n_; owndata_=C.owndata_;
    this->allocate(C.data_);
    return *this;
  }

  template <class F> void NumMat<F>::Resize(Int m, Int n)  {
    if( owndata_ == false ){
#ifdef USE_ABORT
      abort();
#endif
      throw std::logic_error("Matrix being resized must own data.");
    }

    if(m*n > bufsize_) {
      this->deallocate();
      m_ = m; n_ = n;
      this->allocate();
    }
    else{
      m_ = m; n_ = n;
    }
  }

  template <class F> void NumMat<F>::Clear()  {
    if( owndata_ == false ){
#ifdef USE_ABORT
      abort();
#endif
      throw std::logic_error("Matrix being cleared must own data.");
    }

      this->deallocate();
      m_ = 0; n_ = 0;
      bufsize_=0;
  }





  template <class F> const F& NumMat<F>::operator()(Int i, Int j) const  { 
    if( i < 0 || i >= m_ ||
        j < 0 || j >= n_ ) {
#ifdef USE_ABORT
      abort();
#endif
      throw std::logic_error( "Index is out of bound." );
    }
    return data_[i+j*m_];
  }

  template <class F> F& NumMat<F>::operator()(Int i, Int j)  { 
    if( i < 0 || i >= m_ ||
        j < 0 || j >= n_ ) {
#ifdef USE_ABORT
      abort();
#endif
      throw std::logic_error( "Index is out of bound." );
    }
    return data_[i+j*m_];
  }

  template <class F> F* NumMat<F>::VecData(Int j)  const 
  { 
    if( j < 0 || j >= n_ ) {
#ifdef USE_ABORT
      abort();
#endif
      throw std::logic_error( "Index is out of bound." );
    }
    return &(data_[j*m_]); 
  }


  template <class F> inline void SetValue(NumMat<F>& M, F val)
  {
    std::fill(M.Data(),M.Data()+M.m()*M.n(),val);
  }

  template <class F> inline Real Energy(const NumMat<F>& M)
  {
    Real sum = 0;
    F *ptr = M.Data();
    for (Int i=0; i < M.m()*M.n(); i++) 
      sum += abs(ptr[i]) * abs(ptr[i]);
    return sum;
  }


  template <class F> inline void
    Transpose ( const NumMat<F>& A, NumMat<F>& B )
    {
#ifndef _RELEASE_
      PushCallStack("Transpose");
#endif
      if( A.m() != B.n() || A.n() != B.m() ){
        B.Resize( A.n(), A.m() );
      }

      F* Adata = A.Data();
      F* Bdata = B.Data();
      Int m = A.m(), n = A.n();

      for( Int i = 0; i < m; i++ ){
        for( Int j = 0; j < n; j++ ){
          Bdata[ j + n*i ] = Adata[ i + j*m ];
        }
      }

#ifndef _RELEASE_
      PopCallStack();
#endif

      return ;
    }           // -----  end of function Transpose  ----- 

  template <class F> inline void
    Symmetrize( NumMat<F>& A )
    {
#ifndef _RELEASE_
      PushCallStack("Symmetrize");
#endif
      if( A.m() != A.n() ){
#ifdef USE_ABORT
        abort();
#endif
        throw std::logic_error( "The matrix to be symmetrized should be a square matrix." );
      }

      NumMat<F> B;
      Transpose( A, B );

      F* Adata = A.Data();
      F* Bdata = B.Data();

      F  half = (F) 0.5;

      for( Int i = 0; i < A.m() * A.n(); i++ ){
        *Adata = half * (*Adata + *Bdata);
        Adata++; Bdata++;
      }

#ifndef _RELEASE_
      PopCallStack();
#endif

      return ;
    }           // -----  end of function Symmetrize ----- 


} // namespace PEXSI

#endif // _PEXSI_NUMMAT_IMPL_HPP_