**** Includes some functions that only work with FLTs Generalizing these functions is possible, but would require definitions of machine epsilon in the numeric classes

Flattened version is here

Ancestors
 \$MAT{_,_,_} NUMERIC_MAT{_,_} MAT{_,_} AREF{_}

Public

Features
 **** Fill vin `self' to be the best least squares affine map relating `in' to `out' by: `out[i]=self.affine_act_on(vin[i])'.
 **** Fill vin `self' to be the least squares best linear approximation relating `vin' to `vout' by: `out[i]=self.act_on(in[i])'. Return `self'.
 **** Become self's entries uniform in `[0.,1.)'
inplace_weighted_affine_fit_of(vin,vout:ARRAY{VEC}, wt:ARRAY{FLT})
 **** Fill in `self' to be the least squares best linear approximation relating `vin' to `vout' by: `vout[i]=self.act_on(vin[i])'. `wt[i]' gives the weight which should be given to the ith example. (typically in `[0.,1.]' (`0.' means ignore, `1.' means full weight).
 **** Solves `a.x=b' for `x' when `a=u.d.v^T' is the svd of `a'.
 **** Computes the singular value decomposition of `self = a w v^T'. `a' must be `max(nr,nc)' by `nc', `w' length `nc', `v' is `nc' by `nc'. `Self' is unchanged, `a', `w', `v' are altered.

Iters

Private