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# ClassifyStorms - an automated classifier for geomagnetic storm drivers based on machine learning techniques
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### Author
Leonie Pick, GFZ German Research Centre for Geoscieces, leonie.pick@gfz-potsdam.de

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### License

GNU General Public License, Version 3, 29 June 2007

Copyright © 2019 Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, 
Potsdam, Germany

ClassifyStorms is free software: you can redistribute it and/or modify it under the terms of the GNU 
General Public License as published by the Free Software Foundation, either version 3 of the License, 
or (at your option) any later version. ClassifyStorms is distributed in the hope that it will be useful, 
but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS 
FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have 
received a copy of the GNU General Public License along with this program. 
If not, see http://www.gnu.org/licenses/.

### Citation

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Pick, Leonie (2019): ClassifyStorms - An automated classifier for geomagnetic storm drivers based on 
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machine learning techniques. V. 1.0.1. GFZ Data Services. http://doi.org/10.5880/GFZ.2.3.2019.003
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### What is ClassifyStorms?
ClassifyStorms is a software package that performs a classification of geomagnetic storms according to their interplanetary driving 
mechanisms based exclusively on magnetometer measurements from ground.<br>
In the present version two such driver classes are considered. Class 0 holds storms driven by Corotating or Stream Interaction
Regions (C/SIRs) and Class 1 holds storms driven by Interplanetary Coronal Mass Ejections (ICMEs). The classification task is 
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executed by a supervised binary logistic regression model in the framework of python's scikit-learn library.
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### How to run ClassifyStorms?
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Download the latest release of the GitLab project 'ClassifyStorms' from https://gitext.gfz-potsdam.de/lpick/ClassifyStorms/-/releases by clicking on the 'Source code' 
button. Additionally, download the data set 'Input.nc' from GFZ Data Services ( http://doi.org/10.5880/GFZ.2.3.2019.003 ) and place it into 
the extracted directory 'ClassifyStorms-V.x.x.x'. Navigate to ClassifyStorms-V.x.x.x and start the jupyter server 
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(http://jupyter.org) by typing 'jupyter notebook' into the command line. This will open the jupyter 'Home' in your web 
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browser. Select 'ClassifyStorms.ipynb' from the list and run the notebook by clicking 'Run'.
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### Get involved!
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+ Fork the GitLab project 'ClassifyStorms' from http://gitext.gfz-potsdam.de/lpick/ClassifyStorms by clicking on the 'Fork' button (top right).
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+ Clone the forked project to a local directory.
+ Create a new development branch and apply your changes to it.
+ Commit your changes and push them to your forked project at GitLab. If you are done, merge the development branch into the master branch.  
+ Should you decide to share your work, create a merge request for your forked project's master branch (source) and the original 
project's master branch (destination). 

### References
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+ This software is a supplement to Pick et al., Earth and Space Science, 2019 (submitted).
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+ Details on the HMC index are given in Pick et al., JGR Space Physics, 2019 
( http://doi.org/10.1029/2018JA026185, with data published under http://doi.org/10.5880/GFZ.2.3.2018.006 ).