This package contains codes used for the creation of catalogs of interplanetary coronal mass ejections (ICMEs) and their analysis. This is a link to a google colab notebook for instructions how to read the catalogs produced with this package. The ICMECAT as the main result to be produced with this package is published at https://helioforecast.space/icmecat. It forms the largest living catalog of ICMEs.
Authors: C. Möstl, Austrian Space Weather Office, Geosphere Austria https:/helioforecast.space; contributions by E. E. Davies, E. Weiler, A. J. Weiss, R. L. Bailey, M. A. Reiss, C. L. Simon Wedlund, A. Isavnin, R. M. Winslow.
Current status (May 2024): ICME catalog and data downloads work. This is a continuation of work done in the EU HELCATS project (2014-2017): https://www.helcats-fp7.eu.
If you want to use parts of this code for generating results for peer-reviewed scientific publications, please contact me per email ([email protected]) or via https://twitter.com/chrisoutofspace or https://mastodon.social/@chrisoutofspace for co-authorships.
For running the jupyter notebooks (files with .ipynb) or the python scripts (.py), first activate the helio environment (for installation instructions, see bottom of this readme):
conda activate helio4
A data folder location can be set in config.py (e.g. data/) that contains all data files needed during the analysis. Outputs can be found in the folder results/ or subfolders therein, e.g. the files created for the ICMECAT are in folder icmecat/. Jupyter notebooks can be converted to scripts by e.g. for icmecat.ipynb to icmecat.py:
jupyter nbconvert --to script icmecat.ipynb
For some scripts there should be a systemwide installation of ffmpeg available.
Before running the icmecat scripts, you need to download data files the we made (in total around 10 GB) from this figshare repository: https://doi.org/10.6084/m9.figshare.11973693 and place these files in the a folder e.g. named "data", (the name of this folder is set by the variable data_path in file config.py).
This creates the ICMECAT catalog (also a jupyter notebook icmecat.ipynb is available, which can be run and edited by using jupyter notebook or jupyter lab):
python icmecat.py
The catalog is available in these formats: .p (pandas dataframe or numpy record array), .xlsx, .json, .csv, .html, .txt, .h5 (hdf5)
Load this catalog into python with
import pickle
file='icmecat/HELCATS_ICMECAT_v22_pandas.p'
[ic,header,parameters]=pickle.load( open(file, 'rb'))
"ic" is a pandas dataframe, the names of all parameters can be seen with
ic.keys()
and the data can be accessed by
ic.icmecat_id
ic.icme_start_time
ic.mo_bmax
ic.mo_sc_heliodistance
...
which works particularly well in ipython or a jupyter notebook. Further,
print(header)
print(parameters)
gives the header description and the list of all parameters with units.
Alternatively, you can load the ICMECAT with
import pickle
file='icmecat/HELCATS_ICMECAT_v22_numpy.p'
[ic_nprec,ic_np,header,parameters]=pickle.load( open(file, 'rb'))
which returns a numpy record array (ic_nprec) or a numpy structured array (ic_np) consisting of strings and floats.
In the pandas dataframe, all times (ic.icme_start_time, ic.mo_start_time, ic.mo_end_time) are python datetime objects. In the numpy arrays, these times are given in matplotlib format (fractional days since year 0001 Jan 1, plus 1 day). Both formats can be used directly plotting with matplotlib, but can also easily converted into many other formats by (given you have sunpy installed):
from sunpy.time import parse_time
parse_time(ic.icme_start_time).plot_date
parse_time(ic.icme_start_time).iso
...
use either (depending on your preference for jupyter lab, notebook or a script):
jupyter lab arrcat.ipynb
jupyter notebook arrcat.ipynb
python arrcat.py
These codes makes the HELCATS CME arrival catalog, see e.g. Möstl et al. (2017, Space Weather). The catalog is available in essentially the same formats as the ICMECAT, and can be used similarly to above.
Install python with miniconda:
on Linux:
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh
on MacOS:
curl -O https://repo.anaconda.com/miniconda/Miniconda3-latest-MacOSX-x86_64.sh
bash Miniconda3-latest-MacOSX-x86_64.sh
go to a directory of your choice
git clone https://github.com/cmoestl/heliocats
Create a conda environment using the "envs/env_helio4.yml", and activate the environment:
conda env create -f env_helio4.yml
conda activate helio4
Some codes at one point may need to use ffmpeg, which can be downloaded for Mac and Linux from this site: https://ffmpeg.org/download.html
or install from the command line
on Mac brew install ffmpeg
on Linux sudo apt install ffmpeg
MIT LICENSE Copyright 2020-2024, Christian Moestl, Emma Davies, Eva Weiler Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
