output, _ = reproject_interp(aia_map, out_wcs, out_shape) outmap_default = sunpy.map.Map((output, out_header)) outmap_default.plot_settings = aia_map.plot_settings plt.figure() plt.subplot(projection=outmap_default) outmap_default.plot() ###################################################################### # You can use the different assumption that the image lies on the # surface of a spherical screen centered at AIA, with a radius equal # to the Sun-AIA distance. The curvature of the spherical screen is # not obvious in this plot due to the relatively small field of view # of AIA (compared to, say, a coronagraph). with Helioprojective.assume_spherical_screen(aia_map.observer_coordinate): output, _ = reproject_interp(aia_map, out_wcs, out_shape) outmap_screen_all = sunpy.map.Map((output, out_header)) outmap_screen_all.plot_settings = aia_map.plot_settings plt.figure() plt.subplot(projection=outmap_screen_all) outmap_screen_all.plot() ###################################################################### # Finally, you can specify that the spherical-screen assumption should # be used for only off-disk parts of the image, and continue to map # on-disk parts of the image to the surface of the Sun. with Helioprojective.assume_spherical_screen(aia_map.observer_coordinate, only_off_disk=True):