xgboost/booster/xgboost_data.h
2014-02-20 22:08:31 -08:00

180 lines
7.2 KiB
C++

#ifndef _XGBOOST_DATA_H_
#define _XGBOOST_DATA_H_
/*!
* \file xgboost_data.h
* \brief the input data structure for gradient boosting
* \author Tianqi Chen: tianqi.tchen@gmail.com
*/
#include <vector>
#include <climits>
#include "../utils/xgboost_utils.h"
#include "../utils/xgboost_stream.h"
namespace xgboost{
namespace booster{
/*! \brief interger type used in boost */
typedef int bst_int;
/*! \brief unsigned interger type used in boost */
typedef unsigned bst_uint;
/*! \brief float type used in boost */
typedef float bst_float;
/*! \brief debug option for booster */
const bool bst_debug = false;
};
};
namespace xgboost{
namespace booster{
/*!
* \brief feature matrix to store training instance, in sparse CSR format
*/
class FMatrixS{
public:
/*! \brief one row of sparse feature matrix */
struct Line{
/*! \brief array of feature index */
const bst_uint *findex;
/*! \brief array of feature value */
const bst_float *fvalue;
/*! \brief size of the data */
bst_uint len;
};
/*!
* \brief remapped image of sparse matrix,
* allows use a subset of sparse matrix, by specifying a rowmap
*/
struct Image{
public:
Image( const FMatrixS &smat ):smat(smat), row_map( tmp_rowmap ){
}
Image( const FMatrixS &smat, const std::vector<unsigned> &row_map )
:smat(smat), row_map(row_map){
}
/*! \brief get sparse part of current row */
inline Line operator[]( size_t sidx ) const{
if( row_map.size() == 0 ) return smat[ sidx ];
else return smat[ row_map[ sidx ] ];
}
private:
// used to set the simple case
std::vector<unsigned> tmp_rowmap;
const FMatrixS &smat;
const std::vector<unsigned> &row_map;
};
public:
// -----Note: unless needed for hacking, these fields should not be accessed directly -----
/*! \brief row pointer of CSR sparse storage */
std::vector<size_t> row_ptr;
/*! \brief index of CSR format */
std::vector<bst_uint> findex;
/*! \brief value of CSR format */
std::vector<bst_float> fvalue;
public:
/*! \brief constructor */
FMatrixS( void ){ this->Clear(); }
/*!
* \brief get number of rows
* \return number of rows
*/
inline size_t NumRow( void ) const{
return row_ptr.size() - 1;
}
/*!
* \brief get number of nonzero entries
* \return number of nonzero entries
*/
inline size_t NumEntry( void ) const{
return findex.size();
}
/*! \brief clear the storage */
inline void Clear( void ){
row_ptr.resize( 0 );
findex.resize( 0 );
fvalue.resize( 0 );
row_ptr.push_back( 0 );
}
/*!
* \brief add a row to the matrix, but only accept features from fstart to fend
* \param feat sparse feature
* \param fstart start bound of feature
* \param fend end bound range of feature
* \return the row id of added line
*/
inline size_t AddRow( const Line &feat, unsigned fstart = 0, unsigned fend = UINT_MAX ){
utils::Assert( feat.len >= 0, "sparse feature length can not be negative" );
unsigned cnt = 0;
for( unsigned i = 0; i < feat.len; i ++ ){
if( feat.findex[i] < fstart || feat.findex[i] >= fend ) continue;
findex.push_back( feat.findex[i] );
fvalue.push_back( feat.fvalue[i] );
cnt ++;
}
row_ptr.push_back( row_ptr.back() + cnt );
return row_ptr.size() - 2;
}
/*!
* \brief add a row to the matrix, with data stored in STL container
* \param findex feature index
* \param fvalue feature value
* \return the row id added line
*/
inline size_t AddRow( const std::vector<bst_uint> &findex,
const std::vector<bst_float> &fvalue ){
FMatrixS::Line l;
utils::Assert( findex.size() == fvalue.size() );
l.findex = &findex[0];
l.fvalue = &fvalue[0];
l.len = static_cast<bst_uint>( findex.size() );
return this->AddRow( l );
}
/*! \brief get sparse part of current row */
inline Line operator[]( size_t sidx ) const{
Line sp;
utils::Assert( !bst_debug || sidx < this->NumRow(), "row id exceed bound" );
sp.len = static_cast<bst_uint>( row_ptr[ sidx + 1 ] - row_ptr[ sidx ] );
sp.findex = &findex[ row_ptr[ sidx ] ];
sp.fvalue = &fvalue[ row_ptr[ sidx ] ];
return sp;
}
public:
/*!
* \brief save data to binary stream
* note: since we have size_t in row_ptr,
* the function is not consistent between 64bit and 32bit machine
* \param fo output stream
*/
inline void SaveBinary(utils::IStream &fo ) const{
size_t nrow = this->NumRow();
fo.Write( &nrow, sizeof(size_t) );
fo.Write( &row_ptr[0], row_ptr.size() * sizeof(size_t) );
if( findex.size() != 0 ){
fo.Write( &findex[0] , findex.size() * sizeof(bst_uint) );
fo.Write( &fvalue[0] , fvalue.size() * sizeof(bst_float) );
}
}
/*!
* \brief load data from binary stream
* note: since we have size_t in row_ptr,
* the function is not consistent between 64bit and 32bit machine
* \param fi output stream
*/
inline void LoadBinary( utils::IStream &fi ){
size_t nrow;
utils::Assert( fi.Read( &nrow, sizeof(size_t) ) != 0, "Load FMatrixS" );
row_ptr.resize( nrow + 1 );
utils::Assert( fi.Read( &row_ptr[0], row_ptr.size() * sizeof(size_t) ), "Load FMatrixS" );
findex.resize( row_ptr.back() ); fvalue.resize( row_ptr.back() );
if( findex.size() != 0 ){
utils::Assert( fi.Read( &findex[0] , findex.size() * sizeof(bst_uint) ) , "Load FMatrixS" );
utils::Assert( fi.Read( &fvalue[0] , fvalue.size() * sizeof(bst_float) ), "Load FMatrixS" );
}
}
};
};
};
#endif