r-motmo
The Mobility Transition Model (MoTMo) is a large scale agent-based model to simulate the private mobility demand. This is its reduced version (R-MoTMo).
Science Score: 26.0%
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Low similarity (11.9%) to scientific vocabulary
Repository
The Mobility Transition Model (MoTMo) is a large scale agent-based model to simulate the private mobility demand. This is its reduced version (R-MoTMo).
Basic Info
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Metadata Files
README.md
Reduced Mobility Transition Model (R-MoTMo)
| | | |---|---| | Author | Gesine Steudle | | Updated by | Anton Demidov | | Keywords | socio-technical systems, mobility demand, social learning, expected utility| | License | CC-BY-4.0 | | Read more | Reduced Mobility Transition Model (R-MoTMo) (comses.net/) | | Documentation | ReducedMoTMoODD |
The Mobility Transition Model (MoTMo) is a large scale agent-based model to simulate the private mobility demand in Germany until 2035. Here, we publish a very much reduced version of this model (R-MoTMo) which is designed to demonstrate the basic modelling ideas; the aim is by abstracting from the (empirical, technological, geographical, etc.) details to examine the feed-backs of individual decisions on the socio-technical system.
Version 1.0.0 Release Notes
In the file run.py, the simulation parameters can be set in parameters dictionary. The simulation name (part of the name of the saved result files) is created from the input parameters in simulationName field of parameters.
Run the file run.py to start a simulation. If plotResults is set True, the plots specified in plot_selection are done after the simulation is finished. (To plot results from saved files without a new simulation use the file justPlot.py.)
Updated
- The code was formatted;
- The names was transformed to snake_case;
- Encoding was added to parameters dictionary;
- Tools module was updated with new methods
save_to_fileandsave_json_to_file; - Some code improvements;
- Added some docstrings;
- Tools were transformed from class into a set of functions;
- Added Parameters and PlotSelection classes to avoid dictionary usage;
- Added functionality to save the chart to files, use
save_plotsto save the charts.
Requirements
Use this to install requirements automatically or just install them manually:
sh
pip install -r requirements.txt
Owner
- Name: antydemidov
- Login: antydemidov
- Kind: user
- Location: Saint Petersburg, Russia
- Repositories: 1
- Profile: https://github.com/antydemidov
CodeMeta (codemeta.json)
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"dateCreated": "2022-10-31T14:15:51.370985+00:00",
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"datePublished": "2022-12-06",
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