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Overview

CoPro

Welcome to CoPro, a machine-learning tool for conflict risk projections based on climate, environmental, and societal drivers.

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Installation

To install copro, first clone the code from GitHub. It is advised to create an individual python environment first. You can then install the model package into this environment.

$ git clone https://github.com/JannisHoch/copro.git
$ cd path/to/copro
$ conda env create -f environment.yml
$ conda activate copro
$ python setup.py develop

Execution

To be able to run the model, the conda environment has to be activated first.

$ conda activate copro

Example notebook

There are jupyter notebooks available to guide you through the model application process. They can all be run and converted to htmls by executing the provided shell-script.

$ cd path/to/copro/example
$ sh run.sh

It is of course also possible to execute the notebook cell by cell using jupyter notebook.

Runner script

To run the model from command line, a command line script is provided. All data and settings are retrieved from the settings-file which needs to be provided as inline argument.

There are two settings-files, one for evaluating the model for the reference situation, and another one for additionally making projections. To make a projection, both files need to be specified with the latter requiring the -proj flag.

$ cd path/to/copro/scripts
$ python runner.py ../example/example_settings.cfg
$ python runner.py ../example/example_settings.cfg -proj ../example/example_settings_proj.cfg

By default, output is stored to the output directory specified in the specific settings-file.

Documentation

Model documentation including model API can be found at http://copro.rtfd.io/

Code of conduct and Contributing

Please find the relevant information on our Code of Conduct and how to contribute to this package in the relevant files.

Authors

  • Jannis M. Hoch (Utrecht University)
  • Sophie de Bruin (Utrecht University, PBL)
  • Niko Wanders (Utrecht University)

Corrosponding author: Jannis M. Hoch (j.m.hoch@uu.nl)