Update in accordance with master branch

ClassifyStorms.ipynb

@@ -8,13 +8,13 @@
     "\n",
     "**Author**: Leonie Pick, GFZ German Research Centre for Geoscieces, leonie.pick@gfz-potsdam.de<br>\n",
     "**Resources**:\n",
-    "+ This software is a supplement to Pick et al., GRL, 2019, submitted. The code blocks below produce the results presented in the article in seven steps. The nomenclature and section numbers used to comment the code refer to the article and its supporting information (Texts S1-S3).\n",
+    "+ GitLab project https://gitext.gfz-potsdam.de/lpick/ClassifyStorms.\n",
+    "+ The nomenclature and section numbers used to comment the code blocks below refer to Pick et al., GRL, 2019 (submitted) and its supporting information (Texts S1-S3).\n",
     "+ Details on the HMC index are given in Pick et al., JGR Space Physics, 2019 ( http://doi.org/10.1029/2018JA026185,<br>http://doi.org/10.5880/GFZ.2.3.2018.006 ).\n",
     "\n",
-    "**License**: This software is distributed under the GNU General Public Licence with Copyleft.<br>\n",
-    "**Requirements**: Input.nc, Imports.py, Modules.py (md), Plots.py (pl)<br>\n",
-    "**Software dependencies**: Python3 with NumPy(np), SciPy, Matplotlib, Pandas(pd), Xarray(xr), Scikit-\n",
-    "learn(sk)"
+    "**License**: This software is distributed under the GNU General Public License, Version 3, 29 June 2007.<br>\n",
+    "**Required files**: Input.nc (from ftp://ftp.gfz-potsdam.de/home/mag/pick/ClassifyStorms ), Imports.py, Modules.py and Plots.py from https://gitext.gfz-potsdam.de/lpick/ClassifyStorms ).<br>\n",
+    "**Directory structure**: This notebook and the required files are placed into one directory. In that directory, create a directory /Dump/ with the sub-directories /Out/ and /Fig/ if you want to save the results (Save=True, Plot=True). The default is Save=False, Plot=False."
    ]
   },
   {

Readme.md

-# An automatic classifier for geomagnetic storm drivers based on machine learning techniques
+# ClassifyStorms - An automatic classifier for geomagnetic storm drivers based on machine learning techniques
 
 ### Author
 Leonie Pick, GFZ German Research Centre for Geoscieces, leonie.pick@gfz-potsdam.de
 
+### 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
+
+Pick, Leonie (2019): ClassifyStorms - An automatic classifier for geomagnetic storm drivers based on 
+machine learning techniques. V. 1.0.0. GFZ Data Services. http://doi.org/10.5880/GFZ.2.3.2019.003
+
 ### 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 
-executed by a supervised binary logistic regression model in the framework of python's scikit-learn.
+executed by a supervised binary logistic regression model in the framework of python's scikit-learn library.
 
 ### How to run ClassifyStorms?
-Download the GitLab project 'ClassifyStorms' from https://gitext.gfz-potsdam.de/lpick/ClassifyStorms by clicking on the 'Download' 
-button. Additionally, download 'Input.nc' from ftp://ftp.gfz-potsdam.de/home/mag/pick/ClassifyStorms/ and place it into 
-the extracted directory ClassifyStorms-master. Navigate to ClassifyStorms-master and start the jupyter server 
-(https://jupyter.org/) by typing 'jupyter notebook' into the command line. This will open the jupyter 'Home' in your web 
+Download the GitLab project 'ClassifyStorms' from http://gitext.gfz-potsdam.de/lpick/ClassifyStorms by clicking on the 'Download' 
+button (top right). Additionally, download 'Input.nc' from ftp://ftp.gfz-potsdam.de/home/mag/pick/ClassifyStorms and place it into 
+the extracted directory 'ClassifyStorms-master'. Navigate to ClassifyStorms-master and start the jupyter server 
+(http://jupyter.org) by typing 'jupyter notebook' into the command line. This will open the jupyter 'Home' in your web 
 browser. Select 'ClassifyStorms.ipynb' from the list and run the notebook by clicking 'Run'.
 
 ### Get involved!
-+ Fork the GitLab project "ClassifyStorms" from https://gitext.gfz-potsdam.de/lpick/ClassifyStorms by clicking on the 'Fork' button.
++ Fork the GitLab project 'ClassifyStorms' from http://gitext.gfz-potsdam.de/lpick/ClassifyStorms by clicking on the 'Fork' button (top right).
 + 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.  
@@ -27,7 +47,5 @@ project's master branch (destination).
 
 ### References
 + The original version of this software is a supplement to Pick et al., GRL, 2019, submitted.
-+ Details on the HMC index are given in Pick et al., JGR Space Physics, 2019 ( http://doi.org/10.1029/2018JA026185,<br>http://doi.org/10.5880/GFZ.2.3.2018.006 ).
-
-### License
-This software is distributed under the GNU General Public Licence with Copyleft.
++ 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 ).