nojhan/eodev
Archived
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity

use rank mu selector ; bugfix estimator's linear algebra : mu is useless in estimator ; arx = pop^T ; store D as a diagonal ; cwise prod for covar recomposition ; more asserts

Browse source
This commit is contained in:
Johann Dreo 2012-07-13 14:58:27 +02:00
commit 1735660ffe
4 changed files with 63 additions and 45 deletions
Download patch file Download diff file Expand all files Collapse all files

30
edo/src/edoNormalAdaptive.h
View file

@ -41,10 +41,11 @@ class edoNormalAdaptive : public edoDistrib< EOT >
public:
//typedef EOT EOType;
typedef typename EOT::AtomType AtomType;
typedef Eigen::Matrix< AtomType, Eigen::Dynamic, 1> Vector;
typedef Eigen::Matrix< AtomType, Eigen::Dynamic, 1> Vector; // column vectors ( n lines, 1 column)
typedef Eigen::Matrix< AtomType, Eigen::Dynamic, Eigen::Dynamic> Matrix;
edoNormalAdaptive( unsigned int dim ) :
_dim(dim),
_mean( Vector::Zero(dim) ),
_C( Matrix::Identity(dim,dim) ),
_B( Matrix::Identity(dim,dim) ),
@ -53,7 +54,7 @@ public:
_p_c( Vector::Zero(dim) ),
_p_s( Vector::Zero(dim) )
{
assert( dim > 0);
assert( _dim > 0);
}
edoNormalAdaptive( unsigned int dim,
@ -88,23 +89,24 @@ public:
return _mean.innerSize();
}
Vector mean() const {return _mean;}
Matrix covar() const {return _C;}
Matrix coord_sys() const {return _B;}
Vector scaling() const {return _D;}
double sigma() const {return _sigma;}
Vector mean() const {return _mean;}
Matrix covar() const {return _C;}
Matrix coord_sys() const {return _B;}
Vector scaling() const {return _D;}
double sigma() const {return _sigma;}
Vector path_covar() const {return _p_c;}
Vector path_sigma() const {return _p_s;}
void mean( Vector m ) { _mean = m; }
void covar( Matrix c ) { _C = c; }
void coord_sys( Matrix b ) { _B = b; }
void scaling( Vector d ) { _D = d; }
void sigma( double s ) { _sigma = s; }
void path_covar( Vector p ) { _p_c = p; }
void path_sigma( Vector p ) { _p_s = p; }
void mean( Vector m ) { _mean = m; assert( m.size() == _dim ); }
void covar( Matrix c ) { _C = c; assert( c.innerSize() == _dim && c.outerSize() == _dim ); }
void coord_sys( Matrix b ) { _B = b; assert( b.innerSize() == _dim && b.outerSize() == _dim ); }
void scaling( Vector d ) { _D = d; assert( d.size() == _dim ); }
void sigma( double s ) { _sigma = s; assert( s != 0.0 );}
void path_covar( Vector p ) { _p_c = p; assert( p.size() == _dim ); }
void path_sigma( Vector p ) { _p_s = p; assert( p.size() == _dim ); }
private:
unsigned int _dim;
Vector _mean; //
Matrix _C; // covariance matrix
Matrix _B; // eigen vectors / coordinates system