Overplotting SRS active region locations on a magnetograms

How to find and plot the location of an active region on an HMI magnetogram.

import numpy as np
import matplotlib.pyplot as plt

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

import sunpy.map
import sunpy.coordinates
from sunpy.io.special import srs
from sunpy.time import parse_time
from sunpy.net import Fido, attrs as a

For this example, we will search for and download a single HMI using Fido.

start_time = parse_time("2017-01-25")
end_time = start_time + TimeDelta(23*u.hour + 59*u.minute + 59*u.second)
results = Fido.search(a.Time(start_time, end_time),
                      a.Instrument('HMI') & a.vso.Physobs("LOS_magnetic_field"),
                      a.vso.Sample(60 * u.second))

Let’s select only the first file, download it and create a map.

result = results[0, 0]
file_name = Fido.fetch(result)
smap = sunpy.map.Map(file_name)

Download the SRS file.

srs_results = Fido.search(a.Time(start_time, end_time), a.Instrument('SRS_TABLE'))
srs_downloaded_files = Fido.fetch(srs_results)

We get one SRS file per day. To read this file, we pass the filename into the SRS reader. So now srs_table contains an astropy table.

srs_table = srs.read_srs(srs_downloaded_files[0])


ID Number Carrington Longitude  Area ... Mag Type Latitude Longitude
                   deg           uSH  ...            deg       deg
--- ------ -------------------- ----- ... -------- -------- ---------
  I  12626                241.0  10.0 ...    Alpha      8.0      74.0
  I  12627                192.0  30.0 ...     Beta      6.0      25.0
  I  12628                172.0 210.0 ...     Beta     13.0       5.0
  I  12629                109.0  70.0 ...     Beta     15.0     -59.0

We only need the rows which have ‘ID’ = ‘I’ or ‘IA’.

if 'I' in srs_table['ID'] or 'IA' in srs_table['ID']:
    srs_table = srs_table[np.logical_or(srs_table['ID'] == 'I',
                                        srs_table['ID'] == 'IA')]
    print("Warning : No I or IA entries for this date.")
    srs_table = None

Now we extract the latitudes, longitudes and the region numbers. We make an empty list if there are no ARs.

if srs_table is not None:
    lats = srs_table['Latitude']
    lngs = srs_table['Longitude']
    numbers = srs_table['Number']
    lats = lngs = numbers = []

Let’s plot the results by defining coordinates for each location.

ax = plt.subplot(projection=smap)
smap.plot(vmin=-120, vmax=120)

if len(lats) > 0:
    c = SkyCoord(lngs, lats, frame="heliographic_stonyhurst")
    ax.plot_coord(c, 'o')

    for i, num in enumerate(numbers):
        ax.annotate(num, (lngs[i].value, lats[i].value),

Total running time of the script: ( 0 minutes 13.095 seconds)

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