Overlay an AIA image on a LASCO C2 coronagraph#

This example shows the steps needed to overlay the disc and off-limb components of an AIA image within the masked occulter of a LASCO C2 image.

from datetime import datetime

import hvpy
import matplotlib.pyplot as plt
from hvpy.datasource import DataSource

import astropy.units as u
from astropy.coordinates import SkyCoord

import sunpy.data.sample
from sunpy.coordinates import Helioprojective
from sunpy.map import Map
from sunpy.util.config import get_and_create_download_dir

First, we will acquire a calibrated LASCO C2 image from Helioviewer and create a map. hvpy uses the standard datetime instead of astropy.time.

lasco_jp2_file = hvpy.save_file(hvpy.getJP2Image(datetime(2011, 6, 7, 6, 34),
                                filename=get_and_create_download_dir() + "/LASCO_C2.jp2", overwrite=True)
lasco_map = Map(lasco_jp2_file)
aia_map = Map(sunpy.data.sample.AIA_171_IMAGE)

In order to plot off-limb features of the AIA image.

Note that off-disk AIA data are not retained by default because an additional assumption is required to define the location of the AIA emission in 3D space. We can use assume_spherical_screen() to retain the off-disk AIA data. See Reprojecting Using a Spherical Screen for more reference.

projected_coord = SkyCoord(0*u.arcsec, 0*u.arcsec,
projected_header = sunpy.map.make_fitswcs_header(aia_map.data.shape,
# We use `assume_spherical_screen` to ensure that the off limb AIA pixels are reprojected
# otherwise it will only be the on disk pixels that are reprojected.
with Helioprojective.assume_spherical_screen(aia_map.observer_coordinate):
    aia_reprojected = aia_map.reproject_to(projected_header)
/home/docs/checkouts/readthedocs.org/user_builds/sunpy/checkouts/latest/examples/plotting/lasco_overlay.py:45: SunpyMetadataWarning: Missing metadata for observer: assuming Earth-based observer.
For frame 'heliographic_stonyhurst' the following metadata is missing: hglt_obs,dsun_obs,hgln_obs
For frame 'heliographic_carrington' the following metadata is missing: dsun_obs,crln_obs,crlt_obs


Finally, we plot the images by layering the AIA image on top of the LASCO C2 image.

fig = plt.figure()
ax = fig.add_subplot(projection=lasco_map)
aia_reprojected.plot(axes=ax, clip_interval=(1, 99.9)*u.percent, autoalign=True)
ax.set_title("AIA and LASCO C2 Overlay")

AIA and LASCO C2 Overlay
INFO: Missing metadata for solar radius: assuming the standard radius of the photosphere. [sunpy.map.mapbase]

Total running time of the script: (0 minutes 4.332 seconds)

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