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first attempt at implementing a robust cholesky

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nojhan 2011-11-10 15:56:59 +01:00
commit b9b3c486f9
1 changed files with 26 additions and 6 deletions
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32
edo/src/edoSamplerNormalMulti.h
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@ -66,7 +66,7 @@ public:
//! use the algorithm using absolute value within the square root @see factorize_abs
absolute,
//! use the robust algorithm, without square root
//robust
robust
};
Method _use;
@ -150,6 +150,8 @@ public:
factorize_std( V );
} else if( _use == absolute ) {
factorize_abs( V );
} else if( _use == robust ) {
factorize_robust( V );
}
}
@ -183,7 +185,6 @@ public:
// round-off errors may appear here
assert( V(i,i) - sum >= 0 );
_L(i,i) = sqrt( V(i,i) - sum );
//_L(i,i) = sqrt( fabs( V(i,i) - sum) );
for ( j = i + 1; j < N; ++j ) { // rows
// one element
@ -247,18 +248,37 @@ public:
*
* Computes L and D such as V = L D Lt
*/
/*
void factorize_robust( const MatrixType& V)
{
unsigned int N = assert_properties( V );
unsigned int i, j, k;
ublas::symmetric_matrix< AtomType, ublas::lower > D = ublas::zero_matrix<AtomType>(N);
//MatrixType D = ublas::zero_matrix<AtomType>(N);
std::vector<AtomType> _D(N,0);
_L(0, 0) = sqrt( V(0, 0) );
_D[0] = V(0,0);
_L(0, 0) = 1;
//_L(1,0) = 1/D[0] * V(1,0);
for( j=0; j<N; ++j ) { // each columns
_D[j] = V(j,j);
for( k=0; k<j-1; ++k) { // sum
_D[j] -= _L(j,k) * _L(j,k) * _D[k];
}
for( i=j+1; i<N; ++i ) { // remaining rows
_L(i,j) = V(i,j);
for( k=0; k<j-1; ++k) { // sum
_L(i,j) -= _L(i,k)*_L(j,k) * _D[k];
}
_L(i,j) /= _D[j];
} // for i in rows
} // for j in columns
}
*/
}; // class Cholesky