include/colmap/lib/PoissonRecon/SparseMatrix.inl

/*
Copyright (c) 2006, Michael Kazhdan and Matthew Bolitho
All rights reserved.

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are permitted provided that the following conditions are met:

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may be used to endorse or promote products derived from this software without specific
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*/

#include <float.h>
#include <string.h>


///////////////////
//  SparseMatrix //
///////////////////
///////////////////////////////////////
// SparseMatrix Methods and Memebers //
///////////////////////////////////////

template< class T >
void SparseMatrix< T >::_init( void )
{
	_contiguous = false;
	_maxEntriesPerRow = 0;
	rows = 0;
	rowSizes = NullPointer( int );
	m_ppElements = NullPointer( Pointer( MatrixEntry< T > ) );
}

template< class T > SparseMatrix< T >::SparseMatrix( void ){  _init(); }

template< class T > SparseMatrix< T >::SparseMatrix( int rows                        ){ _init() , Resize( rows ); }
template< class T > SparseMatrix< T >::SparseMatrix( int rows , int maxEntriesPerRow ){ _init() , Resize( rows , maxEntriesPerRow ); }

template< class T >
SparseMatrix< T >::SparseMatrix( const SparseMatrix& M )
{
	_init();
	if( M._contiguous ) Resize( M.rows , M._maxEntriesPerRow );
	else                Resize( M.rows );
	for( int i=0 ; i<rows ; i++ )
	{
		SetRowSize( i , M.rowSizes[i] );
		memcpy( (*this)[i] , M[i] , sizeof( MatrixEntry< T > ) * rowSizes[i] );
	}
}
template<class T>
int SparseMatrix<T>::Entries( void ) const
{
	int e = 0;
	for( int i=0 ; i<rows ; i++ ) e += int( rowSizes[i] );
	return e;
}
template<class T>
SparseMatrix<T>& SparseMatrix<T>::operator = (const SparseMatrix<T>& M)
{
	if( M._contiguous ) Resize( M.rows , M._maxEntriesPerRow );
	else                Resize( M.rows );
	for( int i=0 ; i<rows ; i++ )
	{
		SetRowSize( i , M.rowSizes[i] );
		memcpy( (*this)[i] , M[i] , sizeof( MatrixEntry< T > ) * rowSizes[i] );
	}
	return *this;
}

template<class T>
SparseMatrix<T>::~SparseMatrix( void ){ Resize( 0 ); }

template< class T >
bool SparseMatrix< T >::write( const char* fileName ) const
{
	FILE* fp = fopen( fileName , "wb" );
	if( !fp ) return false;
	bool ret = write( fp );
	fclose( fp );
	return ret;
}
template< class T >
bool SparseMatrix< T >::read( const char* fileName )
{
	FILE* fp = fopen( fileName , "rb" );
	if( !fp ) return false;
	bool ret = read( fp );
	fclose( fp );
	return ret;
}
template< class T >
bool SparseMatrix< T >::write( FILE* fp ) const
{
	if( fwrite( &rows , sizeof( int ) , 1 , fp )!=1 ) return false;
	if( fwrite( rowSizes , sizeof( int ) , rows , fp )!=rows ) return false;
	for( int i=0 ; i<rows ; i++ ) if( fwrite( (*this)[i] , sizeof( MatrixEntry< T > ) , rowSizes[i] , fp )!=rowSizes[i] ) return false;
	return true;
}
template< class T >
bool SparseMatrix< T >::read( FILE* fp )
{
	int r;
	if( fread( &r , sizeof( int ) , 1 , fp )!=1 ) return false;
	Resize( r );
	if( fread( rowSizes , sizeof( int ) , rows , fp )!=rows ) return false;
	for( int i=0 ; i<rows ; i++ )
	{
		r = rowSizes[i];
		rowSizes[i] = 0;
		SetRowSize( i , r );
		if( fread( (*this)[i] , sizeof( MatrixEntry< T > ) , rowSizes[i] , fp )!=rowSizes[i] ) return false;
	}
	return true;
}


template< class T >
void SparseMatrix< T >::Resize( int r )
{
	if( rows>0 )
	{
		if( _contiguous ){ if( _maxEntriesPerRow ) FreePointer( m_ppElements[0] ); }
		else for( int i=0 ; i<rows ; i++ ){ if( rowSizes[i] ) FreePointer( m_ppElements[i] ); }
		FreePointer( m_ppElements );
		FreePointer( rowSizes );
	}
	rows = r;
	if( r )
	{
		rowSizes = AllocPointer< int >( r );
		m_ppElements = AllocPointer< Pointer( MatrixEntry< T > ) >( r );
		memset( rowSizes , 0 , sizeof( int ) * r );
	}
	_contiguous = false;
	_maxEntriesPerRow = 0;
}
template< class T >
void SparseMatrix< T >::Resize( int r , int e )
{
	if( rows>0 )
	{
		if( _contiguous ){ if( _maxEntriesPerRow ) FreePointer( m_ppElements[0] ); }
		else for( int i=0 ; i<rows ; i++ ){ if( rowSizes[i] ) FreePointer( m_ppElements[i] ); }
		FreePointer( m_ppElements );
		FreePointer( rowSizes );
	}
	rows = r;
	if( r )
	{
		rowSizes = AllocPointer< int >( r );
		m_ppElements = AllocPointer< Pointer( MatrixEntry< T > ) >( r );
		m_ppElements[0] = AllocPointer< MatrixEntry< T > >( r * e );
		memset( rowSizes , 0 , sizeof( int ) * r );
		for( int i=1 ; i<r ; i++ ) m_ppElements[i] = m_ppElements[i-1] + e;
	}
	_contiguous = true;
	_maxEntriesPerRow = e;
}

template<class T>
void SparseMatrix< T >::SetRowSize( int row , int count )
{
	if( _contiguous )
	{
		if( count>_maxEntriesPerRow ) fprintf( stderr , "[ERROR] Cannot set row size on contiguous matrix: %d<=%d\n" , count , _maxEntriesPerRow ) , exit( 0 );
		rowSizes[row] = count;
	}
	else if( row>=0 && row<rows )
	{
		if( rowSizes[row] ) FreePointer( m_ppElements[row] );
		if( count>0 ) m_ppElements[row] = AllocPointer< MatrixEntry< T > >( count );
		// [WARNING] Why wasn't this line here before???
		rowSizes[row] = count;
	}
}


template<class T>
void SparseMatrix<T>::SetZero()
{
	Resize(this->m_N, this->m_M);
}

template<class T>
SparseMatrix<T> SparseMatrix<T>::operator * (const T& V) const
{
	SparseMatrix<T> M(*this);
	M *= V;
	return M;
}

template<class T>
SparseMatrix<T>& SparseMatrix<T>::operator *= (const T& V)
{
	for( int i=0 ; i<rows ; i++ ) for( int ii=0 ; ii<rowSizes[i] ; i++ ) m_ppElements[i][ii].Value *= V;
	return *this;
}

template< class T >
template< class T2 >
void SparseMatrix< T >::Multiply( ConstPointer( T2 ) in , Pointer( T2 ) out , int threads ) const
{
#pragma omp parallel for num_threads( threads )
	for( int i=0 ; i<rows ; i++ )
	{
		T2 _out(0);
		ConstPointer( MatrixEntry< T > ) start = m_ppElements[i];
		ConstPointer( MatrixEntry< T > ) end = start + rowSizes[i];
		ConstPointer( MatrixEntry< T > ) e;
		for( e=start ; e!=end ; e++ ) _out += in[ e->N ] * e->Value;
		out[i] = _out;
	}
}
template< class T >
template< class T2 >
void SparseMatrix< T >::MultiplyAndAddAverage( ConstPointer( T2 ) in , Pointer( T2 ) out , int threads ) const
{
	T2 average = 0;
	for( int i=0 ; i<rows ; i++ ) average += in[i];
	average /= rows;
	Multiply( in , out , threads );
#pragma omp parallel for num_threads( threads )
	for( int i=0 ; i<rows ; i++ ) out[i] += average;
}


template< class T >
template< class T2 >
int SparseMatrix<T>::SolveJacobi( const SparseMatrix<T>& M , ConstPointer( T2 ) diagonal , ConstPointer( T2 ) b , Pointer( T2 ) x , Pointer( T2 ) Mx , T2 sor , int threads )
{
	M.Multiply( x , Mx , threads );
#if ZERO_TESTING_JACOBI
	for( int j=0 ; j<int(M.rows) ; j++ ) if( diagonal[j] ) x[j] += ( b[j]-Mx[j] ) * sor / diagonal[j];
#else // !ZERO_TESTING_JACOBI
	for( int j=0 ; j<int(M.rows) ; j++ ) x[j] += ( b[j]-Mx[j] ) * sor / diagonal[j];
#endif // ZERO_TESTING_JACOBI
	return M.rows;
}
template< class T >
template< class T2 >
int SparseMatrix<T>::SolveJacobi( const SparseMatrix<T>& M , ConstPointer( T2 ) b , Pointer( T2 ) x , Pointer( T2 ) Mx , T2 sor , int threads )
{
	M.Multiply( x , Mx , threads );
#if ZERO_TESTING_JACOBI
	for( int j=0 ; j<int(M.rows) ; j++ )
	{
		T diagonal = M[j][0].Value;
		if( diagonal ) x[j] += ( b[j]-Mx[j] ) * sor / diagonal;
	}
#else // !ZERO_TESTING_JACOBI
	for( int j=0 ; j<int(M.rows) ; j++ ) x[j] += ( b[j]-Mx[j] ) * sor / M[j][0].Value;
#endif // ZERO_TESTING_JACOBI
	return M.rows;
}
template<class T>
template<class T2>
int SparseMatrix<T>::SolveGS( const SparseMatrix<T>& M , ConstPointer( T2 ) diagonal , ConstPointer( T2 ) b , Pointer( T2 ) x , bool forward )
{
#define ITERATE                                                         \
	{                                                                   \
		ConstPointer( MatrixEntry< T > ) start = M[j];                  \
		ConstPointer( MatrixEntry< T > ) end = start + M.rowSizes[j];   \
		ConstPointer( MatrixEntry< T > ) e;                             \
		T2 _b = b[j];                                                   \
		for( e=start ; e!=end ; e++ ) _b -= x[ e->N ] * e->Value;       \
		x[j] += _b / diagonal[j];                                       \
	}

#if ZERO_TESTING_JACOBI
	if( forward ) for( int j=0 ; j<int(M.rows)    ; j++ ){ if( diagonal[j] ){ ITERATE; } }
	else          for( int j=int(M.rows)-1 ; j>=0 ; j-- ){ if( diagonal[j] ){ ITERATE; } }
#else // !ZERO_TESTING_JACOBI
	if( forward ) for( int j=0 ; j<int(M.rows) ; j++ ){ ITERATE; }
	else          for( int j=int(M.rows)-1 ; j>=0 ; j-- ){ ITERATE; }
#endif // ZERO_TESTING_JACOBI
#undef ITERATE
	return M.rows;
}
template<class T>
template<class T2>
int SparseMatrix<T>::SolveGS( const std::vector< std::vector< int > >& mcIndices , const SparseMatrix<T>& M , ConstPointer( T2 ) diagonal , ConstPointer( T2 ) b , Pointer( T2 ) x , bool forward , int threads )
{
	int sum=0;
#ifdef _WIN32
#define SetOMPParallel __pragma( omp parallel for num_threads( threads ) )
#else // !_WIN32
#define SetOMPParallel _Pragma( "omp parallel for num_threads( threads )" )
#endif // _WIN32
#if ZERO_TESTING_JACOBI
#define ITERATE( indices )                                                        \
	{                                                                             \
SetOMPParallel                                                                    \
		for( int k=0 ; k<int( indices.size() ) ; k++ ) if( diagonal[indices[k]] ) \
		{                                                                         \
			int jj = indices[k];                                                  \
			ConstPointer( MatrixEntry< T > ) start = M[jj];                       \
			ConstPointer( MatrixEntry< T > ) end = start + M.rowSizes[jj];        \
			ConstPointer( MatrixEntry< T > ) e;                                   \
			T2 _b = b[jj];                                                        \
			for( e=start ; e!=end ; e++ ) _b -= x[ e->N ] * e->Value;             \
			x[jj] += _b / diagonal[jj];                                           \
		}                                                                         \
	}
#else // !ZERO_TESTING_JACOBI
#define ITERATE( indices )                                                  \
	{                                                                       \
SetOMPParallel                                                              \
		for( int k=0 ; k<int( indices.size() ) ; k++ )                      \
		{                                                                   \
			int jj = indices[k];                                            \
			ConstPointer( MatrixEntry< T > ) start = M[jj];                 \
			ConstPointer( MatrixEntry< T > ) end = start + M.rowSizes[jj];  \
			ConstPointer( MatrixEntry< T > ) e;                             \
			T2 _b = b[jj];                                                  \
			for( e=start ; e!=end ; e++ ) _b -= x[ e->N ] * e->Value;       \
			x[jj] += _b / diagonal[jj];                                     \
		}                                                                   \
	}
#endif // ZERO_TESTING_JACOBI
	if( forward ) for( int j=0 ; j<mcIndices.size()  ; j++ ){ sum += int( mcIndices[j].size() ) ; ITERATE( mcIndices[j] ); }
	else for( int j=int( mcIndices.size() )-1 ; j>=0 ; j-- ){ sum += int( mcIndices[j].size() ) ; ITERATE( mcIndices[j] ); }
#undef ITERATE
#undef SetOMPParallel
	return sum;
}
template<class T>
template<class T2>
int SparseMatrix<T>::SolveGS( const SparseMatrix<T>& M , ConstPointer( T2 ) b , Pointer( T2 ) x , bool forward )
{
	int start = forward ? 0 : M.rows-1 , end = forward ? M.rows : -1 , dir = forward ? 1 : -1;
	for( int j=start ; j!=end ; j+=dir )
	{
		T diagonal = M[j][0].Value;
#if ZERO_TESTING_JACOBI
		if( diagonal )
#endif // ZERO_TESTING_JACOBI
		{
			ConstPointer( MatrixEntry< T > ) start = M[j];
			ConstPointer( MatrixEntry< T > ) end = start + M.rowSizes[j];
			ConstPointer( MatrixEntry< T > ) e;
			start++;
			T2 _b = b[j];
			for( e=start ; e!=end ; e++ ) _b -= x[ e->N ] * e->Value;
			x[j] = _b / diagonal;
		}
	}
	return M.rows;
}
template<class T>
template<class T2>
int SparseMatrix<T>::SolveGS( const std::vector< std::vector< int > >& mcIndices , const SparseMatrix<T>& M , ConstPointer( T2 ) b , Pointer( T2 ) x , bool forward , int threads )
{
	int sum=0 , start = forward ? 0 : int( mcIndices.size() )-1 , end = forward ? int( mcIndices.size() ) : -1 , dir = forward ? 1 : -1;
	for( int j=start ; j!=end ; j+=dir )
	{
		const std::vector< int >& _mcIndices = mcIndices[j];
		sum += int( _mcIndices.size() );
		{
#pragma omp parallel for num_threads( threads )
			for( int k=0 ; k<int( _mcIndices.size() ) ; k++ )
			{
				int jj = _mcIndices[k];
				T diagonal = M[jj][0].Value;
#if ZERO_TESTING_JACOBI
				if( diagonal )
#endif // ZERO_TESTING_JACOBI
				{
					ConstPointer( MatrixEntry< T > ) start = M[jj];
					ConstPointer( MatrixEntry< T > ) end = start + M.rowSizes[jj];
					ConstPointer( MatrixEntry< T > ) e;
					start++;
					T2 _b = b[jj];
					for( e=start ; e!=end ; e++ ) _b -= x[ e->N ] * e->Value;
					x[jj] = _b / diagonal;
				}                                   
			}
		}
	}
	return sum;
}

template< class T >
template< class T2 >
void SparseMatrix< T >::getDiagonal( Pointer( T2 ) diagonal , int threads ) const
{
#pragma omp parallel for num_threads( threads )
	for( int i=0 ; i<rows ; i++ )
	{
		T2 d = 0.;
		ConstPointer( MatrixEntry< T > ) start = m_ppElements[i];
		ConstPointer( MatrixEntry< T > ) end = start + rowSizes[i];
		ConstPointer( MatrixEntry< T > ) e;
		for( e=start ; e!=end ; e++ ) if( e->N==i ) d += e->Value;
		diagonal[i] = d;
	}
}
template< class T >
template< class T2 >
int SparseMatrix< T >::SolveCG( const SparseMatrix<T>& A , ConstPointer( T2 ) b , int iters , Pointer( T2 ) x , T2 eps , int reset , bool addDCTerm , bool solveNormal , int threads )
{
	eps *= eps;
	int dim = A.rows;
	Pointer( T2 ) r = AllocPointer< T2 >( dim );
	Pointer( T2 ) d = AllocPointer< T2 >( dim );
	Pointer( T2 ) q = AllocPointer< T2 >( dim );
	Pointer( T2 ) temp = NullPointer( T2 );
	if( reset ) memset( x , 0 , sizeof(T2)* dim );
	if( solveNormal ) temp = AllocPointer< T2 >( dim );

	double delta_new = 0 , delta_0;
	if( solveNormal )
	{
		if( addDCTerm ) A.MultiplyAndAddAverage( ( ConstPointer( T2 ) )x , temp , threads ) , A.MultiplyAndAddAverage( ( ConstPointer( T2 ) )temp , r , threads ) , A.MultiplyAndAddAverage( ( ConstPointer( T2 ) )b , temp , threads );
		else            A.Multiply( ( ConstPointer( T2 ) )x , temp , threads ) , A.Multiply( ( ConstPointer( T2 ) )temp , r , threads ) , A.Multiply( ( ConstPointer( T2 ) )b , temp , threads );
#pragma omp parallel for num_threads( threads ) reduction( + : delta_new )
		for( int i=0 ; i<dim ; i++ ) d[i] = r[i] = temp[i] - r[i] , delta_new += r[i] * r[i];
	}
	else
	{
		if( addDCTerm ) A.MultiplyAndAddAverage( ( ConstPointer( T2 ) )x , r , threads );
		else            A.Multiply( ( ConstPointer( T2 ) )x , r , threads );
#pragma omp parallel for num_threads( threads )  reduction ( + : delta_new )
		for( int i=0 ; i<dim ; i++ ) d[i] = r[i] = b[i] - r[i] , delta_new += r[i] * r[i];
	}
	delta_0 = delta_new;
	if( delta_new<eps )
	{
//		fprintf( stderr , "[WARNING] Initial residual too low: %g < %f\n" , delta_new , eps );
		FreePointer( r );
		FreePointer( d );
		FreePointer( q );
		FreePointer( temp );
		return 0;
	}
	int ii;
	for( ii=0 ; ii<iters && delta_new>eps*delta_0 ; ii++ )
	{
		if( solveNormal )
			if( addDCTerm ) A.MultiplyAndAddAverage( ( ConstPointer( T2 ) )d , temp , threads ) , A.MultiplyAndAddAverage( ( ConstPointer( T2 ) )temp , q , threads );
			else            A.Multiply( ( ConstPointer( T2 ) )d , temp , threads ) , A.Multiply( ( ConstPointer( T2 ) )temp , q , threads );
		else
			if( addDCTerm ) A.MultiplyAndAddAverage( ( ConstPointer( T2 ) )d , q , threads );
			else            A.Multiply( ( ConstPointer( T2 ) )d , q , threads );
        double dDotQ = 0;
#pragma omp parallel for num_threads( threads ) reduction( + : dDotQ )
		for( int i=0 ; i<dim ; i++ ) dDotQ += d[i] * q[i];
		T2 alpha = T2( delta_new / dDotQ );
		double delta_old = delta_new;
		delta_new = 0;
		if( (ii%50)==(50-1) )
		{
#pragma omp parallel for num_threads( threads )
			for( int i=0 ; i<dim ; i++ ) x[i] += d[i] * alpha;
			if( solveNormal )
				if( addDCTerm ) A.MultiplyAndAddAverage( ( ConstPointer( T2 ) )x , temp , threads ) , A.MultiplyAndAddAverage( ( ConstPointer( T2 ) )temp , r , threads );
				else            A.Multiply( ( ConstPointer( T2 ) )x , temp , threads ) , A.Multiply( ( ConstPointer( T2 ) )temp , r , threads );
			else
				if( addDCTerm ) A.MultiplyAndAddAverage( ( ConstPointer( T2 ) )x , r , threads );
				else            A.Multiply( ( ConstPointer( T2 ) )x , r , threads );
#pragma omp parallel for num_threads( threads ) reduction( + : delta_new )
			for( int i=0 ; i<dim ; i++ ) r[i] = b[i] - r[i] , delta_new += r[i] * r[i] , x[i] += d[i] * alpha;
		}
		else
#pragma omp parallel for num_threads( threads ) reduction( + : delta_new )
			for( int i=0 ; i<dim ; i++ ) r[i] -= q[i] * alpha , delta_new += r[i] * r[i] ,  x[i] += d[i] * alpha;

		T2 beta = T2( delta_new / delta_old );
#pragma omp parallel for num_threads( threads )
		for( int i=0 ; i<dim ; i++ ) d[i] = r[i] + d[i] * beta;
	}
	FreePointer( r );
	FreePointer( d );
	FreePointer( q );
	FreePointer( temp );
	return ii;
}