Note
Go to the end to download the full example code
Requesting specific AIA images from the JSOC#
This example shows how to request a specific series of AIA images from the JSOC.
We will be filtering the data we require by keywords and requesting short exposure images from a recent (at time of writing) flare.
import os
import astropy.units as u
import matplotlib.pyplot as plt
import sunpy.map
from astropy.coordinates import SkyCoord
from astropy.visualization import AsinhStretch, ImageNormalize
from sunpy.net import Fido, attrs
from aiapy.calibrate import correct_degradation, register, update_pointing
from aiapy.calibrate.util import get_correction_table, get_pointing_table
Exporting data from the JSOC requires registering your
email first. Please replace the text after the =
with your email address once you have registered.
See this page for more details.
jsoc_email = os.environ.get("JSOC_EMAIL")
Our goal is to request data of a recent X-class flare. The X-class flare occurred on the 2021/07/03 at 14:30:00 UTC. We will focus on the 5 minutes before and after this time. What we want to do is only get the shorter exposures, which are going to be the flare related.
query = Fido.search(
attrs.Time("2021-07-03 14:25:00", "2021-07-03 14:35:00"),
attrs.jsoc.Series("aia.lev1_euv_12s"),
attrs.Wavelength(211 * u.AA),
attrs.jsoc.Notify(jsoc_email),
attrs.jsoc.Keyword("EXPTIME") <= 2,
attrs.jsoc.Segment("image"),
)
print(query)
Results from 1 Provider:
20 Results from the JSOCClient:
Source: http://jsoc.stanford.edu
T_REC TELESCOP INSTRUME WAVELNTH CAR_ROT
-------------------- -------- -------- -------- -------
2021-07-03T14:27:23Z SDO/AIA AIA_2 211 2245
2021-07-03T14:27:47Z SDO/AIA AIA_2 211 2245
2021-07-03T14:28:11Z SDO/AIA AIA_2 211 2245
2021-07-03T14:28:35Z SDO/AIA AIA_2 211 2245
2021-07-03T14:28:59Z SDO/AIA AIA_2 211 2245
2021-07-03T14:29:23Z SDO/AIA AIA_2 211 2245
2021-07-03T14:29:47Z SDO/AIA AIA_2 211 2245
2021-07-03T14:30:11Z SDO/AIA AIA_2 211 2245
2021-07-03T14:30:35Z SDO/AIA AIA_2 211 2245
2021-07-03T14:30:59Z SDO/AIA AIA_2 211 2245
2021-07-03T14:31:23Z SDO/AIA AIA_2 211 2245
2021-07-03T14:31:47Z SDO/AIA AIA_2 211 2245
2021-07-03T14:32:11Z SDO/AIA AIA_2 211 2245
2021-07-03T14:32:35Z SDO/AIA AIA_2 211 2245
2021-07-03T14:32:59Z SDO/AIA AIA_2 211 2245
2021-07-03T14:33:23Z SDO/AIA AIA_2 211 2245
2021-07-03T14:33:47Z SDO/AIA AIA_2 211 2245
2021-07-03T14:34:11Z SDO/AIA AIA_2 211 2245
2021-07-03T14:34:35Z SDO/AIA AIA_2 211 2245
2021-07-03T14:34:59Z SDO/AIA AIA_2 211 2245
Now we will download the data and “aia prep” the
data with every feature of aiapy and plot the
data sequence using sunpy.
files = Fido.fetch(query)
level_1_maps = sunpy.map.Map(files)
# We get the pointing table outside of the loop for the relevant time range.
# Otherwise you're making a call to the JSOC every single time.
pointing_table = get_pointing_table(level_1_maps[0].date - 3 * u.h, level_1_maps[-1].date + 3 * u.h)
# The same applies for the correction table.
correction_table = get_correction_table()
level_15_maps = []
for a_map in level_1_maps:
map_updated_pointing = update_pointing(a_map, pointing_table=pointing_table)
map_registered = register(map_updated_pointing)
map_degradation = correct_degradation(map_registered, correction_table=correction_table)
map_normalized = map_degradation / map_degradation.exposure_time
bottom_left = SkyCoord(500 * u.arcsec, 100 * u.arcsec, frame=map_normalized.coordinate_frame)
top_right = SkyCoord(1500 * u.arcsec, 700 * u.arcsec, frame=map_normalized.coordinate_frame)
map_cropped = map_normalized.submap(bottom_left, top_right=top_right)
level_15_maps.append(map_cropped)
Export request pending. [id=JSOC_20231219_2730, status=2]
Waiting for 0 seconds...
20 URLs found for download. Full request totalling 151MB
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Finally, we create a sequence of maps and animate it
sequence = sunpy.map.Map(level_15_maps, sequence=True)
fig = plt.figure()
ax = fig.add_subplot(projection=sequence.maps[0])
ani = sequence.plot(axes=ax, norm=ImageNormalize(vmin=0, vmax=1e3, stretch=AsinhStretch()))
plt.show()
Total running time of the script: (1 minutes 49.842 seconds)