A quick and easy SJI

In this example we will show how to plot a South Pole SJI dataset.

You can get IRIS data with co-aligned SDO data (and more) from https://iris.lmsal.com/search/

import matplotlib.pyplot as plt
import pooch

from irispy.io import read_files

We start with getting the data. This is done by downloading the data from the IRIS archive.

In this case, we will use pooch as to keep this example self contained but using your browser will also work.

sji_filename = pooch.retrieve(
    "https://www.lmsal.com/solarsoft/irisa/data/level2_compressed/2023/02/11/20230211_083601_3880012095/iris_l2_20230211_083601_3880012095_SJI_2832_t000.fits.gz",
    known_hash="a4b4f108ed67aded876bb167f24f093e8401d836f7deb66c97a36da8dd226064",
)

Downloading data from 'https://www.lmsal.com/solarsoft/irisa/data/level2_compressed/2023/02/11/20230211_083601_3880012095/iris_l2_20230211_083601_3880012095_SJI_2832_t000.fits.gz' to file '/home/docs/.cache/pooch/b74a047a9a5d54358fbd7182c04f3948-iris_l2_20230211_083601_3880012095_SJI_2832_t000.fits.gz'.

We will now open the slit-jaw imager (SJI) file we just downloaded.

sji_2832 = read_files(sji_filename)
# Printing will give us an overview of the file.
print(sji_2832)

SJICube
-------
Observatory:           IRIS
Instrument:            SJI
Bandpass:              2832.0
Obs. Start:            2023-02-11T08:36:01.730
Obs. End:              2023-02-11T09:10:13.347
Instance Start:        2023-02-11T08:37:05.800
Instance End:          2023-02-11T09:09:09.200
Total Frames in Obs.:  None
IRIS Obs. id:          3880012095
IRIS Obs. Description: Very large coarse 64-step raster 126x175 64s   Deep x 30
Axis Types:            [('custom:pos.helioprojective.lon', 'custom:pos.helioprojective.lat', 'time', 'custom:CUSTOM', 'custom:CUSTOM', 'custom:CUSTOM', 'custom:CUSTOM', 'custom:CUSTOM', 'custom:CUSTOM', 'custom:CUSTOM', 'custom:CUSTOM', 'custom:CUSTOM'), ('custom:pos.helioprojective.lon', 'custom:pos.helioprojective.lat'), ('custom:pos.helioprojective.lon', 'custom:pos.helioprojective.lat')]
Roll:                  -0.000393857
Cube dimensions:       [  16. 1093. 1776.] pix

We will now plot the IRIS SJI data. You can also change the axis labels and ticks if you so desire. WCSAxes provides us an API we can use.

# Note that the .get_animation() is used to animate this example and is not required normally.
ax = sji_2832.plot().get_animation()
plt.xlabel("Helioprojective Longitude (Solar-X) [arcsec]")
plt.ylabel("Helioprojective Latitude (Solar-Y) [arcsec]")
plt.title(f"IRIS SJI {sji_2832.meta['TWAVE1']}", pad=20)

plt.show()

Once Loop Reflect