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Source code for the publications on "a non-linear Granger-causality framework to investigate climate–vegetation dynamics", by Papagiannopoulou et al., GMD & ERL 2017

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Climate - Vegetation Dynamics: a Granger causality framework

This repository contains the source codes used in the following publications:

Prerequisites

The script is mainly built using the following packages:

python 2.7.12 | Anaconda 2.3.0 (64-bit) (or higher)
scikit-learn

Running the tests

In order to test the framework, a test file is provided (test.csv). This file contains all features used in the publication for one pixel on earth.

The script allows you to test both the "linear" and "non-linear" framework. In order to execute these, use the following commands:

python GC_script.py test.csv linear
python GC_script.py test.csv non-linear

Output

The outcome of both tests provide you information on the explained variance of the baseline and full model as well as a quantification of the Granger causality. For more information, see publication.

The output should look as follows:

1. Linear case

Explained variance of baseline model: 0.076398
Explained variance of full model: 0.199819
Quantification of Granger causality: 0.123421
Total time: 58 seconds

2. Non-Linear case

Explained variance of baseline model: 0.055405
Explained variance of full model: 0.306413
Quantification of Granger causality: 0.251008
Total time: 6 seconds

License

This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details

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Source code for the publications on "a non-linear Granger-causality framework to investigate climate–vegetation dynamics", by Papagiannopoulou et al., GMD & ERL 2017

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