code: def circular_annular(cls, shape, pixel_scale, inner_radius_arcsec, outer_radius_arcsec, centre=(0., 0.),
                           invert=False):
          
          mask = mask_util.mask_circular_annular_from_shape_pixel_scale_and_radii(shape, pixel_scale, inner_radius_arcsec,
                                                                                  outer_radius_arcsec, centre)
          if invert: mask = np.invert(mask)
          return cls(array=mask.astype('bool'), pixel_scale=pixel_scale)
docs: Setup a mask where unmasked pixels are within an annulus of input inner and outer arc second radii and \
           centre.
  
          Parameters
          ----------
          shape : (int, int)
              The (y,x) shape of the mask in units of pixels.
          pixel_scale: float
              The arc-second to pixel conversion factor of each pixel.
          inner_radius_arcsec : float
              The radius (in arc seconds) of the inner circle outside of which pixels are unmasked.
          outer_radius_arcsec : float
              The radius (in arc seconds) of the outer circle within which pixels are unmasked.
          centre: (float, float)
              The centre of the annulus used to mask pixels.