CoPro

This is the documentation of CoPro, a machine-learning tool for conflict risk projections.

A software description paper was published in JOSS.

Main goal

With CoPro it is possible to apply machine-learning techniques to make projections of future areas at risk. CoPro was developed with a rather clear application in mind, unravelling the interplay of socio-economic development, climate change, and conflict occurrence. Nevertheless, we put a lot of emphasis on making it flexible. We hope that other, related questions about climate and conflict can be tackled as well, and that process understanding is deepened further.

Contents

• 1. Installation
  • 1.1. From GitHub
  • 1.2. From PyPI
  • 1.3. From conda
• 2. Execution
  • 2.1. Runner script
  • 2.2. Binder
• 3. Settings
  • 3.1. The cfg-file
  • 3.2. The sections
• Workflow
  • 1. Model initialization and selection procedure
  • 2. Obtaining samples matrix and target values
  • 3. Initializing and executing the machine-learning model
  • 4. Projecting conflict risk
• 4. Output
  • 4.1. Output folder structure
  • 4.2. List of output files
• 5. Post-processing
  • 5.1. plot_value_over_time.py
  • 5.2. avg_over_time.py
  • 5.3. plot_polygon_vals.py
  • 5.4. geojson2gif.py
• API
  • 1. The model pipeline
  • 2. The various models
  • 3. Selecting polygons and conflicts
  • 4. Machine learning
  • 5. Variable values
  • 6. XY-Data
  • 7. Work with conflict data
  • 8. Model evaluation
  • 9. Plotting
  • 10. Auxiliary functions

Authors

• Jannis M. Hoch (Utrecht University)

• Sophie de Bruin (Utrecht University, PBL)

• Niko Wanders (Utrecht University)

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

Indices and tables

• Search Page

• Index

1. Installation