Analysis and Interpretation of IRIS data¶
This page contains instructions and materials for lectures and tutorials given by Tiago Pereira at the SOLARNET school hosted by MSSL in January 2021. There are two ways to work with the materials: download data and necessary packages into your computer (recommended), or online-only using Binder. The Binder option is slower, will timeout when not active, and is meant to be a failsafe option. You can use the Binder version by clicking the link below:
Running on your computer¶
If you have already followed the python setup for the SOLARNET school, all packages for the lectures and tutorial should already be installed. You can safely ignore the step below to create a new conda environment. The commands below assume you have a conda installation: miniconda (miniconda or Anaconda), and have git installed.
The first step is to clone the repository into a directory of your choice. Open a terminal and navigate to your preferred directory, and then clone the repository:
git clone https://github.com/tiagopereira/solarnet2021.git solarnet_iris
If you don't have git, you can instead download a zip file, but then it will be harder to keep the repository current in case there are updates.
You will end up with a directory called solarnet_iris. In the terminal, go to that directory. If have not yet installed the common python packages for the SOLARNET school, you can do it using the provided environment.yml (if you have, skip this step):
conda env create -f environment.yml
Then you need to activate the environment:
conda activate solarnet
The last step is to download some data files. Please download the following data files into the directory solarnet_iris/notebooks:
- iris_l2_20180102_153155_3610108077_SJI_1400_t000.fits.gz
- iris_l2_20140919_051712_3860608353_SJI_2832_t000.fits.gz
- iris_l2_20180102_153155_3610108077_raster.tar.gz
- aia_20140919_060030_1700_image_lev1.fits
These downloads are about 350 MB. The IRIS raster file as a tar archive (in this case with a single file). You will need to unpack it before starting:
tar zxvf iris_l2_20180102_153155_3610108077_raster.tar.gz
Once you have all the data files in the solarnet_iris/notebooks directory, you are ready to start. From the terminal, in the directory solarnet_iris/notebooks, start jupyter:
jupyter notebook