Requesting cutouts of AIA images from the JSOC

This example shows how to request a cutout of a series of AIA images from the JSOC.

import os

import matplotlib.pyplot as plt

import astropy.units as u
from astropy.coordinates import SkyCoord
from astropy.time import Time
from astropy.visualization import ImageNormalize, SqrtStretch

import sunpy.coordinates  # NOQA
import sunpy.map
from sunpy.net import Fido
from sunpy.net import attrs as a

As this is an example, we have already worked out where we need to crop for the active region we want to showcase.

start_time = Time('2012-09-24T14:56:03', scale='utc', format='isot')
bottom_left = SkyCoord(-500*u.arcsec, -275*u.arcsec, obstime=start_time, observer="earth", frame="helioprojective")
top_right = SkyCoord(150*u.arcsec, 375*u.arcsec, obstime=start_time, observer="earth", frame="helioprojective")

Now construct the cutout from the coordinates above above using the Cutout attribute.

cutout = a.jsoc.Cutout(bottom_left, top_right=top_right, tracking=True)

Exporting data from the JSOC requires registering your email first. Please replace this with your email address once you have registered like so: jsoc_email = “your_email@example.com” See this page for more details.

jsoc_email = os.environ["JSOC_EMAIL"]

Now we are ready to construct the query. Note that all of this is the same for a full-frame image except for the cutout component. We will download images from a 12 hour interval centered on the time of the above cutout. We request one image every 2 hours.

query = Fido.search(
    a.Time(start_time - 6*u.h, start_time + 6*u.h),
    a.Wavelength(171*u.angstrom),
    a.Sample(2*u.h),
    a.jsoc.Series.aia_lev1_euv_12s,
    a.jsoc.Notify(jsoc_email),
    a.jsoc.Segment.image,
    cutout,
)
print(query)

Submit the export request and download the data.

files = Fido.fetch(query)
files.sort()

Now that we’ve downloaded the files, we can create a MapSequence from them and animate them.

sequence = sunpy.map.Map(files, sequence=True)

fig = plt.figure()
ax = fig.add_subplot(projection=sequence.maps[0])
ani = sequence.plot(axes=ax, norm=ImageNormalize(vmin=0, vmax=5e3, stretch=SqrtStretch()))

plt.show()