__call__(self,
curve,
param_vals,
xx,
yy,
vvv=[ ] ,
ww=None,
on_iter=<__builtin__.function object>,
on_status=<__builtin__.function object>)
(Call operator)
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Returns improved param_vals, which minimize the sum-squared-residual
between yy and curve.eval(param_vals, xx, vvv).
- Parameters:
curve - BaseCurve
param_vals - list of float corresponding to curve.params
xx - numpy.array(dtype='float32') of x coords
yy - numpy.array(dtype='float32') of y coords
vvv - list of numpy.array(dtype='float32') of additional named data
series, available to curve expr
ww - numpy.array(dtype='float32') of weighting factors, per sample, or
None
on_iter - each improvement in param_vals, calls on_iter(param_vals, iter)
-> True to continue iterating
on_status - text output callback: on_status(msg)
- Returns:
- (fitted param_vals, sum_sqr_residual, iterations, fit curve
array)
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