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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 _solve_scipy(self, intern_x0, tol=1e-8, method=None, **kwargs):
 """ Uses ``scipy.optimize.root`` See: http://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.root.html Parameters intern_x0: array_like initial guess tol: float Tolerance method: str What method to use. Defaults to ``'lm'`` if ``self.nf > self.nx`` otherwise ``'hybr'``. """

        from scipy.optimize import root
        if method is None:
            if self.nf > self.nx:
                method = 'lm'
            elif self.nf == self.nx:
                method = 'hybr'
            else:
                raise ValueError('Underdetermined problem')
        if 'band' in kwargs:
            raise ValueError("Set 'band' at initialization instead.")
        if 'args' in kwargs:
            raise ValueError("Set 'args' as params in initialization instead.")

        new_kwargs = kwargs.copy()
        if self.band is not None:
            warnings.warn("Band argument ignored (see SciPy docs)")
            new_kwargs['band'] = self.band
        new_kwargs['args'] = self.internal_params

        return root(self.f_cb, intern_x0, jac=self.j_cb, method=method, tol=tol, **new_kwargs)