How to use the photutils.isophote.sample.EllipseSample function in photutils

def _iterative(self, sma, step, linear, geometry, sclip, nclip,
                   integrmode, conver, minit, maxit, fflag, maxgerr,
                   going_inwards=False):
        if sma > 0.:
            # iterative fitter
            sample = EllipseSample(self.image, sma, astep=step, sclip=sclip,
                                   nclip=nclip, linear_growth=linear,
                                   geometry=geometry, integrmode=integrmode)
            fitter = EllipseFitter(sample)
        else:
            # sma == 0 requires special handling
            sample = CentralEllipseSample(self.image, 0.0, geometry=geometry)
            fitter = CentralEllipseFitter(sample)

        isophote = fitter.fit(conver, minit, maxit, fflag, maxgerr,
                              going_inwards)

        return isophote

def _non_iterative(self, sma, step, linear, geometry, sclip, nclip,
                       integrmode):
        sample = EllipseSample(self.image, sma, astep=step, sclip=sclip,
                               nclip=nclip, linear_growth=linear,
                               geometry=geometry, integrmode=integrmode)
        sample.update()

        # build isophote without iterating with an EllipseFitter
        isophote = Isophote(sample, 0, True, stop_code=4)

        return isophote

def _get_gradient(self, step):
        gradient_sma = (1. + step) * self.geometry.sma

        gradient_sample = EllipseSample(
            self.image, gradient_sma, x0=self.geometry.x0,
            y0=self.geometry.y0, astep=self.geometry.astep, sclip=self.sclip,
            nclip=self.nclip, eps=self.geometry.eps,
            position_angle=self.geometry.pa,
            linear_growth=self.geometry.linear_growth,
            integrmode=self.integrmode)

        sg = gradient_sample.extract()
        mean_g = np.mean(sg[2])
        gradient = (mean_g - self.mean) / self.geometry.sma / step

        s = self.extract()
        sigma = np.std(s[2])
        sigma_g = np.std(sg[2])

        gradient_error = (np.sqrt(sigma**2 / len(s[2]) +

def finalize_correction(self, dx, dy, sample):
        new_x0 = sample.geometry.x0 + dx
        new_y0 = sample.geometry.y0 + dy

        return EllipseSample(sample.image, sample.geometry.sma, x0=new_x0,
                             y0=new_y0, astep=sample.geometry.astep,
                             sclip=sample.sclip, nclip=sample.nclip,
                             eps=sample.geometry.eps,
                             position_angle=sample.geometry.pa,
                             linear_growth=sample.geometry.linear_growth,
                             integrmode=sample.integrmode)