# HMI PFSS solutions

Calculating a PFSS solution from a HMI synoptic map.

This example shows how to calcualte a PFSS solution from a HMI synoptic map. There are a couple of important things that this example shows:

• HMI maps have non-standard metadata, so this needs to be fixed

• HMI synoptic maps are very big (1440 x 3600), so need to be downsampled in order to calculate the PFSS solution in a reasonable time.

First import the required modules

```import os

import astropy.units as u
import matplotlib.pyplot as plt
import sunpy.map
from sunpy.net import Fido
from sunpy.net import attrs as a

import pfsspy
import pfsspy.utils
```

Set up the search.

Note that for SunPy versions earlier than 2.0, a time attribute is needed to do the search, even if (in this case) it isn’t used, as the synoptic maps are labelled by Carrington rotation number instead of time

```time = a.Time('2010/01/01', '2010/01/01')
series = a.jsoc.Series('hmi.synoptic_mr_polfil_720s')
crot = a.jsoc.PrimeKey('CAR_ROT', 2210)
```

Do the search.

If you use this code, please replace this email address with your own one, registered here: http://jsoc.stanford.edu/ajax/register_email.html

```result = Fido.search(time, series, crot,
a.jsoc.Notify(os.environ["JSOC_EMAIL"]))
files = Fido.fetch(result)
```

Out:

```Export request pending. [id=JSOC_20211110_1525_X_IN, status=2]
Waiting for 0 seconds...

hmi.synoptic_mr_polfil_720s.2210.Mr_polfil.fits:   0%|          | 0.00/6.17M [00:00<?, ?B/s]

hmi.synoptic_mr_polfil_720s.2210.Mr_polfil.fits:   0%|          | 100/6.17M [00:00<2:03:02, 835B/s]

hmi.synoptic_mr_polfil_720s.2210.Mr_polfil.fits:   0%|          | 24.1k/6.17M [00:00<00:51, 119kB/s]

hmi.synoptic_mr_polfil_720s.2210.Mr_polfil.fits:   1%|1         | 92.1k/6.17M [00:00<00:18, 328kB/s]

hmi.synoptic_mr_polfil_720s.2210.Mr_polfil.fits:   4%|4         | 254k/6.17M [00:00<00:07, 740kB/s]

hmi.synoptic_mr_polfil_720s.2210.Mr_polfil.fits:  10%|#         | 626k/6.17M [00:00<00:03, 1.61MB/s]

hmi.synoptic_mr_polfil_720s.2210.Mr_polfil.fits:  20%|#9        | 1.21M/6.17M [00:00<00:01, 2.73MB/s]

hmi.synoptic_mr_polfil_720s.2210.Mr_polfil.fits:  34%|###4      | 2.10M/6.17M [00:00<00:00, 4.52MB/s]

hmi.synoptic_mr_polfil_720s.2210.Mr_polfil.fits:  49%|####9     | 3.04M/6.17M [00:00<00:00, 5.95MB/s]

hmi.synoptic_mr_polfil_720s.2210.Mr_polfil.fits:  68%|######7   | 4.17M/6.17M [00:01<00:00, 7.43MB/s]

hmi.synoptic_mr_polfil_720s.2210.Mr_polfil.fits:  85%|########5 | 5.27M/6.17M [00:01<00:00, 8.49MB/s]

```

```hmi_map = sunpy.map.Map(files[0])
print('Data shape: ', hmi_map.data.shape)
```

Out:

```Data shape:  (1440, 3600)
```

Since this map is far to big to calculate a PFSS solution quickly, lets resample it down to a smaller size.

```hmi_map = hmi_map.resample([360, 180] * u.pix)
print('New shape: ', hmi_map.data.shape)
```

Out:

```New shape:  (180, 360)
```

Now calculate the PFSS solution

```nrho = 35
pfss_out = pfsspy.pfss(pfss_in)
```

Using the Output object we can plot the source surface field, and the polarity inversion line.

```ss_br = pfss_out.source_surface_br
# Create the figure and axes
fig = plt.figure()
ax = plt.subplot(projection=ss_br)

# Plot the source surface map
ss_br.plot()
# Plot the polarity inversion line
ax.plot_coord(pfss_out.source_surface_pils[0])
# Plot formatting
plt.colorbar()
ax.set_title('Source surface magnetic field')

plt.show()
```

Out:

```/home/docs/checkouts/readthedocs.org/user_builds/pfsspy/envs/stable/lib/python3.7/site-packages/pfsspy/output.py:95: UserWarning: Could not parse unit string "Mx/cm^2" as a valid FITS unit.
See https://fits.gsfc.nasa.gov/fits_standard.html for the FITS unit standards.
warnings.warn(f'Could not parse unit string "{unit_str}" as a valid FITS unit.\n'