243 lines
7 KiB
C++
243 lines
7 KiB
C++
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#ifndef __VECTORSET_H__
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#define __VECTORSET_H__
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/*
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===============================================================================
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Vector Set
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Creates a set of vectors without duplicates.
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===============================================================================
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*/
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template< class type, int dimension >
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class idVectorSet : public idList<type> {
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public:
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idVectorSet( void );
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idVectorSet( const type &mins, const type &maxs, const int boxHashSize, const int initialSize );
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// returns total size of allocated memory
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size_t Allocated( void ) const { return idList<type>::Allocated() + hash.Allocated(); }
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// returns total size of allocated memory including size of type
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size_t Size( void ) const { return sizeof( *this ) + Allocated(); }
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void Init( const type &mins, const type &maxs, const int boxHashSize, const int initialSize );
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void ResizeIndex( const int newSize );
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void Clear( void );
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int FindVector( const type &v, const float epsilon );
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private:
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idHashIndex hash;
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type mins;
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type maxs;
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int boxHashSize;
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float boxInvSize[dimension];
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float boxHalfSize[dimension];
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};
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template< class type, int dimension >
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ID_INLINE idVectorSet<type,dimension>::idVectorSet( void ) {
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hash.Clear( idMath::IPow( boxHashSize, dimension ), 128 );
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boxHashSize = 16;
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memset( boxInvSize, 0, dimension * sizeof( boxInvSize[0] ) );
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memset( boxHalfSize, 0, dimension * sizeof( boxHalfSize[0] ) );
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}
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template< class type, int dimension >
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ID_INLINE idVectorSet<type,dimension>::idVectorSet( const type &mins, const type &maxs, const int boxHashSize, const int initialSize ) {
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Init( mins, maxs, boxHashSize, initialSize );
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}
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template< class type, int dimension >
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ID_INLINE void idVectorSet<type,dimension>::Init( const type &mins, const type &maxs, const int boxHashSize, const int initialSize ) {
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int i;
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float boxSize;
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idList<type>::AssureSize( initialSize );
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idList<type>::SetNum( 0, false );
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hash.Clear( idMath::IPow( boxHashSize, dimension ), initialSize );
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this->mins = mins;
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this->maxs = maxs;
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this->boxHashSize = boxHashSize;
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for ( i = 0; i < dimension; i++ ) {
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boxSize = ( maxs[i] - mins[i] ) / (float) boxHashSize;
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boxInvSize[i] = 1.0f / boxSize;
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boxHalfSize[i] = boxSize * 0.5f;
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}
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}
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template< class type, int dimension >
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ID_INLINE void idVectorSet<type,dimension>::ResizeIndex( const int newSize ) {
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idList<type>::Resize( newSize );
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hash.ResizeIndex( newSize );
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}
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template< class type, int dimension >
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ID_INLINE void idVectorSet<type,dimension>::Clear( void ) {
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idList<type>::Clear();
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hash.Clear();
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}
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template< class type, int dimension >
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ID_INLINE int idVectorSet<type,dimension>::FindVector( const type &v, const float epsilon ) {
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int i, j, k, hashKey, partialHashKey[dimension];
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for ( i = 0; i < dimension; i++ ) {
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assert( epsilon <= boxHalfSize[i] );
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partialHashKey[i] = (int) ( ( v[i] - mins[i] - boxHalfSize[i] ) * boxInvSize[i] );
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}
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for ( i = 0; i < ( 1 << dimension ); i++ ) {
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hashKey = 0;
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for ( j = 0; j < dimension; j++ ) {
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hashKey *= boxHashSize;
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hashKey += partialHashKey[j] + ( ( i >> j ) & 1 );
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}
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for ( j = hash.First( hashKey ); j >= 0; j = hash.Next( j ) ) {
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const type &lv = (*this)[j];
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for ( k = 0; k < dimension; k++ ) {
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if ( idMath::Fabs( lv[k] - v[k] ) > epsilon ) {
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break;
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}
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}
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if ( k >= dimension ) {
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return j;
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}
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}
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}
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hashKey = 0;
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for ( i = 0; i < dimension; i++ ) {
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hashKey *= boxHashSize;
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hashKey += (int) ( ( v[i] - mins[i] ) * boxInvSize[i] );
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}
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hash.Add( hashKey, idList<type>::Num() );
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Append( v );
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return idList<type>::Num()-1;
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}
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/*
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===============================================================================
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Vector Subset
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Creates a subset without duplicates from an existing list with vectors.
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===============================================================================
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*/
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template< class type, int dimension >
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class idVectorSubset {
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public:
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idVectorSubset( void );
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idVectorSubset( const type &mins, const type &maxs, const int boxHashSize, const int initialSize );
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// returns total size of allocated memory
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size_t Allocated( void ) const { return idList<type>::Allocated() + hash.Allocated(); }
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// returns total size of allocated memory including size of type
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size_t Size( void ) const { return sizeof( *this ) + Allocated(); }
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void Init( const type &mins, const type &maxs, const int boxHashSize, const int initialSize );
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void Clear( void );
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// returns either vectorNum or an index to a previously found vector
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int FindVector( const type *vectorList, const int vectorNum, const float epsilon );
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private:
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idHashIndex hash;
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type mins;
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type maxs;
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int boxHashSize;
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float boxInvSize[dimension];
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float boxHalfSize[dimension];
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};
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template< class type, int dimension >
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ID_INLINE idVectorSubset<type,dimension>::idVectorSubset( void ) {
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hash.Clear( idMath::IPow( boxHashSize, dimension ), 128 );
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boxHashSize = 16;
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memset( boxInvSize, 0, dimension * sizeof( boxInvSize[0] ) );
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memset( boxHalfSize, 0, dimension * sizeof( boxHalfSize[0] ) );
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}
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template< class type, int dimension >
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ID_INLINE idVectorSubset<type,dimension>::idVectorSubset( const type &mins, const type &maxs, const int boxHashSize, const int initialSize ) {
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Init( mins, maxs, boxHashSize, initialSize );
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}
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template< class type, int dimension >
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ID_INLINE void idVectorSubset<type,dimension>::Init( const type &mins, const type &maxs, const int boxHashSize, const int initialSize ) {
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int i;
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float boxSize;
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hash.Clear( idMath::IPow( boxHashSize, dimension ), initialSize );
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this->mins = mins;
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this->maxs = maxs;
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this->boxHashSize = boxHashSize;
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for ( i = 0; i < dimension; i++ ) {
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boxSize = ( maxs[i] - mins[i] ) / (float) boxHashSize;
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boxInvSize[i] = 1.0f / boxSize;
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boxHalfSize[i] = boxSize * 0.5f;
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}
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}
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template< class type, int dimension >
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ID_INLINE void idVectorSubset<type,dimension>::Clear( void ) {
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idList<type>::Clear();
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hash.Clear();
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}
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template< class type, int dimension >
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ID_INLINE int idVectorSubset<type,dimension>::FindVector( const type *vectorList, const int vectorNum, const float epsilon ) {
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int i, j, k, hashKey, partialHashKey[dimension];
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const type &v = vectorList[vectorNum];
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for ( i = 0; i < dimension; i++ ) {
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assert( epsilon <= boxHalfSize[i] );
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partialHashKey[i] = (int) ( ( v[i] - mins[i] - boxHalfSize[i] ) * boxInvSize[i] );
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}
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for ( i = 0; i < ( 1 << dimension ); i++ ) {
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hashKey = 0;
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for ( j = 0; j < dimension; j++ ) {
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hashKey *= boxHashSize;
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hashKey += partialHashKey[j] + ( ( i >> j ) & 1 );
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}
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for ( j = hash.First( hashKey ); j >= 0; j = hash.Next( j ) ) {
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const type &lv = vectorList[j];
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for ( k = 0; k < dimension; k++ ) {
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if ( idMath::Fabs( lv[k] - v[k] ) > epsilon ) {
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break;
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}
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}
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if ( k >= dimension ) {
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return j;
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}
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}
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}
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hashKey = 0;
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for ( i = 0; i < dimension; i++ ) {
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hashKey *= boxHashSize;
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hashKey += (int) ( ( v[i] - mins[i] ) * boxInvSize[i] );
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}
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hash.Add( hashKey, vectorNum );
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return vectorNum;
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}
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#endif /* !__VECTORSET_H__ */
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