Fixed minimizer behaviour on exceeded iterations

[rozyczko]

This adds improvements to the fitting result reporting and evaluation tracking across all minimizer engines, ensuring that the number of function evaluations and relevant messages are consistently captured and propagated.

• All minimizer engines (Bumps, DFO, LMFit) now populate n_evaluations (number of function evaluations) and message (status or error message) fields in FitResults, and these fields are propagated in multi-dataset fitting.

• The Bumps minimizer uses a new _EvalCounter wrapper to count function evaluations and detect when the maximum evaluation budget is reached, updating the success flag and message accordingly.

• The DFO minimizer now raises FitError only for real failures, and considers both success and max function evaluation warnings as successful fits, improving error reporting and testability.

[henrikjacobsenfys]

Looks good to me apart from a tiny nitpick.

This may also be a good opportunity to make a __repr__ method for the FitResults class?

[rozyczko]

This may also be a good opportunity to make a __repr__ method for the FitResults class?

Good idea!
Added these

   lines = [
        f"FitResults(success={self.success}",
        f"  n_pars={self.n_pars}, n_points={len(self.x)}",
        f"  chi2={self.chi2:.4g}, reduced_chi={self.reduced_chi:.4g}",
        f"  n_evaluations={self.n_evaluations}",
        f"  minimizer={self.minimizer_engine.__name__ if self.minimizer_engine else None}",
    ]