Calculate the GOES-XRS temperature and emission measure during a flare

This example shows you how to estimate the GOES-XRS isothermal temperature and emission measure during a solar flare. This is done using the observed flux ratio of the short (0.5-4 angstrom) to long (1-8 angstrom) channels, based on the methods described in White et al. (2005). The functionality available here is the same as the functionality available in SSWIDL.

import matplotlib.pyplot as plt

from sunpy import timeseries as ts
from sunpy.data.sample import GOES_XRS_TIMESERIES

from sunkit_instruments import goes_xrs

Let’s begin by creating a GOES-XRS timeseries. We can use the sample data here to load in an example of a flare.

goes_ts = ts.TimeSeries(GOES_XRS_TIMESERIES)
goes_ts.plot()

<Axes: ylabel='Watts m$^{-2}$'>

The estimation is only valid for large fluxes (i.e. during a flare), so let’s truncate the timeseries over the time of the flare.

goes_flare = goes_ts.truncate("2011-06-07 06:15", "2011-06-07 09:00")

Now let’s calculate the temperature and emission measure estimates from these channel fluxes. We can do this by using the function sunkit_instruments.goes_xrs.calculate_temperature_em which takes a sunpy.timeseries.sources.XRSTimeSeries and returns a new timeseries which contains both the respective temperature and emission measure values.

goes_temp_em = goes_xrs.calculate_temperature_em(goes_flare)

Traceback (most recent call last):
  File "/home/docs/checkouts/readthedocs.org/user_builds/sunkit-instruments/checkouts/stable/examples/calculate_goes_temperature_and_emission_measure.py", line 39, in <module>
    goes_temp_em = goes_xrs.calculate_temperature_em(goes_flare)
                   ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/docs/checkouts/readthedocs.org/user_builds/sunkit-instruments/conda/stable/lib/python3.12/site-packages/sunkit_instruments/goes_xrs/goes_chianti_tem.py", line 127, in calculate_temperature_em
    output = _chianti_temp_emiss(
             ^^^^^^^^^^^^^^^^^^^^
  File "/home/docs/checkouts/readthedocs.org/user_builds/sunkit-instruments/conda/stable/lib/python3.12/site-packages/sunpy/data/data_manager/manager.py", line 62, in wrapper
    self._download_and_cache_file(name, urls, sha_hash)
  File "/home/docs/checkouts/readthedocs.org/user_builds/sunkit-instruments/conda/stable/lib/python3.12/site-packages/sunpy/data/data_manager/manager.py", line 88, in _download_and_cache_file
    details = self._cache.get_by_hash(sha_hash)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/docs/checkouts/readthedocs.org/user_builds/sunkit-instruments/conda/stable/lib/python3.12/site-packages/sunpy/data/data_manager/cache.py", line 121, in get_by_hash
    details = self._storage.find_by_key('file_hash', sha_hash)
              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/docs/checkouts/readthedocs.org/user_builds/sunkit-instruments/conda/stable/lib/python3.12/site-packages/sunpy/data/data_manager/storage.py", line 156, in find_by_key
    cursor.execute(f'''SELECT * FROM {self._table_name}
sqlite3.OperationalError: no such column: "cb00c05850e3dc3bbd856eb07c1a372758d689d0845ee591d6e2531afeab0382" - should this be a string literal in single-quotes?

We can see that goes_temp_em is now a timeseries that contains the temperature and emission measure by printing out the column names.

print(goes_temp_em.columns)

Now let’s plot these all together.

fig, (ax1, ax2, ax3) = plt.subplots(3, sharex=True)
goes_flare.plot(axes=ax1)
goes_temp_em.plot(columns=["temperature"], axes=ax2)
goes_temp_em.plot(columns=["emission_measure"], axes=ax3)
ax3.set_yscale("log")
plt.show()