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)
def _solve_scipy ( self , intern_x0 , tol = 1e-8 , method = None , ** kwargs ) : 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 )
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'``.