Reproducible Discrete-Event Simulation in Python and R
Output analysis
β Parallel processing
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Python
R
Reproducible Discrete-Event Simulation in Python and R
Introduction
Reproducibility and RAPs
Guidelines
Open-source languages
Example conceptual models π©Ίπ§
Setup
Version control
Environments
Structuring as a package
Code organisation
Model inputs
Input modelling
Input data management
Parameters from script
Parameters from file
Parameter validation
Model building
β Randomness
β Entity generation
β Entity processing
Output analysis
β Performance measures
β Initialisation bias
β Replications
β Number of replications
β Parallel processing
Experimentation
β Scenario analysis
β Sensitivity analysis
Verification & validation
β Logging
β Tests
β Validation
Style & documentation
Linting
β Docstrings
β Documentation
β GitHub actions
Reports & manuscripts
β Producing tables and figures
β Full run
Collaboration & sharing
β Peer review
β Licensing
β Sharing and archiving
Citation
β Changelog
Further information
β Acknowledgements
Output analysis
β Parallel processing
β Parallel processing
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Reproducibility guidelines:
Heather et al. 2025: Optimise model run time.