.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "generated/gallery/south_sji.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. .. rst-class:: sphx-glr-example-title .. _sphx_glr_generated_gallery_south_sji.py: ==================== 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/ .. GENERATED FROM PYTHON SOURCE LINES 10-16 .. code-block:: Python import matplotlib.pyplot as plt import pooch from irispy.io import read_files .. GENERATED FROM PYTHON SOURCE LINES 17-22 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. .. GENERATED FROM PYTHON SOURCE LINES 22-28 .. code-block:: Python 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", ) .. rst-class:: sphx-glr-script-out .. code-block:: none 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'. .. GENERATED FROM PYTHON SOURCE LINES 29-30 We will now open the slit-jaw imager (SJI) file we just downloaded. .. GENERATED FROM PYTHON SOURCE LINES 30-35 .. code-block:: Python sji_2832 = read_files(sji_filename) # Printing will give us an overview of the file. print(sji_2832) .. rst-class:: sphx-glr-script-out .. code-block:: none 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 .. GENERATED FROM PYTHON SOURCE LINES 36-39 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. `__ .. GENERATED FROM PYTHON SOURCE LINES 39-47 .. code-block:: Python # 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() .. container:: sphx-glr-animation .. raw:: html
.. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 22.032 seconds) .. _sphx_glr_download_generated_gallery_south_sji.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: south_sji.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: south_sji.py ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_