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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def sample_conf(self, f, *args, **kwargs):
 r"""Sample confidence interval of numerical method f over all samples Calls f(\*args, \*\*kwargs) on all samples and computes the confidence interval. Size of confidence interval is given in the construction of the SampledModel. f must return a numerical value or an ndarray. Parameters f : method reference or name (str) Model method to be evaluated for each model sample args : arguments Non-keyword arguments to be passed to the method in each call kwargs : keyword-argments Keyword arguments to be passed to the method in each call Returns ------- L : float or ndarray lower value or array of confidence interval R : float or ndarray upper value or array of confidence interval """

        vals = self.sample_f(f, *args, **kwargs)
        return confidence_interval(vals, conf=self.conf)