musecube_old.py 文件源码

def determinate_seeing_from_white(self, xc, yc, halfsize):
        """
        Function used to estimate the observation seeing of an exposure, fitting a gaussian to  a brigth source of the  image
        :param xc: x coordinate in pixels of a bright source
        :param yc: y coordinate  in pixels of a bright source
        :param halfsize: the radius of the area to fit the gaussian
        :return: seeing: float
                         the observational seeing of the image defined as the FWHM of the gaussian
        """
        hdulist = self.hdulist_white
        data = hdulist[1].data
        matrix_data = np.array(self.get_mini_image([xc, yc], halfsize=halfsize))
        x = np.arange(0, matrix_data.shape[0], 1)
        y = np.arange(0, matrix_data.shape[1], 1)
        matrix_x, matrix_y = np.meshgrid(x, y)
        amp_init = np.matrix(matrix_data).max()
        stdev_init = 0.33 * halfsize

        def tie_stddev(model):  # we need this for tying x_std and y_std
            xstddev = model.x_stddev
            return xstddev

        g_init = models.Gaussian2D(x_mean=halfsize + 0.5, y_mean=halfsize + 0.5, x_stddev=stdev_init,
                                   y_stddev=stdev_init, amplitude=amp_init, tied={'y_stddev': tie_stddev})

        fit_g = fitting.LevMarLSQFitter()
        g = fit_g(g_init, matrix_x, matrix_y, matrix_data)
        if (g.y_stddev < 0) or (g.y_stddev > halfsize):
            raise ValueError('Cannot trust the model, please try other imput parameters.')

        seeing = 2.355 * g.y_stddev * self.pixelsize.to('arcsec')  # in arcsecs
        print('FWHM={:.2f}'.format(seeing))
        print('stddev from the 2D gaussian = {:.3f}'.format(g.y_stddev * self.pixelsize.to('arcsec')))
        return seeing