(self, X, fit, func, ask=None, args=())
return self.treat()
proceed with noise measurement, set anew attributes ``evaluations``
        (proposed number of evaluations to "treat" noise) and ``evaluations_just_done``
        and return a factor for increasing sigma.

        Parameters
        ----------
            `X`
                a list/sequence/vector of solutions
            `fit`
                the respective list of function values
            `func`
                the objective function, ``fit[i]`` corresponds to ``func(X[i], *args)``
            `ask`
                a method to generate a new, slightly disturbed solution. The argument
                is mandatory if ``epsilon`` is not zero, see `__init__()`.
            `args`
                optional additional arguments to `func`

        Details
        -------
        Calls the methods ``reeval()``, ``update_measure()`` and ``treat()`` in this order.
        ``self.evaluations`` is adapted within the method `treat()`.
proceed with noise measurement, set anew attributes ``evaluations``
        (proposed number of evaluations to "treat" noise) and ``evaluations_just_done``
        and return a factor for increasing sigma.
proceed with noise measurement set anew attributes evaluations ( proposed number of evaluations to treat noise ) and evaluations_just_done and return a factor for increasing sigma .
def __call__(self, X, fit, func, ask=None, args=()):
        """proceed with noise measurement, set anew attributes ``evaluations``
        (proposed number of evaluations to "treat" noise) and ``evaluations_just_done``
        and return a factor for increasing sigma.

        Parameters
        ----------
            `X`
                a list/sequence/vector of solutions
            `fit`
                the respective list of function values
            `func`
                the objective function, ``fit[i]`` corresponds to ``func(X[i], *args)``
            `ask`
                a method to generate a new, slightly disturbed solution. The argument
                is mandatory if ``epsilon`` is not zero, see `__init__()`.
            `args`
                optional additional arguments to `func`

        Details
        -------
        Calls the methods ``reeval()``, ``update_measure()`` and ``treat()`` in this order.
        ``self.evaluations`` is adapted within the method `treat()`.

        """
        self.evaluations_just_done = 0
        if not self.maxevals or self.lam_reeval == 0:
            return 1.0
        res = self.reeval(X, fit, func, ask, args)
        if not len(res):
            return 1.0
        self.update_measure()
        return self.treat()
def __call__ ( self , X , fit , func , ask = None , args = ( ) ) : self . evaluations_just_done = 0 if not self . maxevals or self . lam_reeval == 0 : return 1.0 res = self . reeval ( X , fit , func , ask , args ) if not len ( res ) : return 1.0 self . update_measure ( ) return self . treat ( )