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# Geosimulation using fields and agents | ||
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This repository holds a Jupyter notebook demonstrating the Daisyworld model implementation in Campo, | ||
a YAML file to create the Python environment required to run the model, | ||
and necessary scripts for pre- and postprocessing. | ||
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You can run the Jupyter notebook either online using Google Colab, or locally on your own computer. | ||
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More information will be given in the [Agile 2023 workshop](https://agile-online.org/conference-2023/programme-2023/agile-workshops-2023). | ||
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## Running online in Google Colab | ||
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You need a Google account to run the notebook. | ||
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1. Open the notebook using the following link: | ||
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2. Create a copy of the notebook in your own Google Drive by using the *Copy to Drive* button. | ||
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3. After copying you can run the notebook. The first code cell will install the required software and may take a few minutes to complete. | ||
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## Running on your local machine | ||
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### How to install | ||
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A few steps are required to run the Jupyter notebook. | ||
General information on Jupyter notebooks and manuals can be found [here](https://jupyter.readthedocs.io/en/latest/). | ||
The user guide and short reference on Conda can be found [here](https://docs.conda.io/projects/conda/en/latest/user-guide/cheatsheet.html). | ||
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1. You will need a working Python environment, we recommend to install Miniconda. Follow their instructions given at: | ||
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[https://docs.conda.io/en/latest/miniconda.html](https://docs.conda.io/en/latest/miniconda.html) | ||
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2. Open a terminal (Linux/macOS) or Miniconda command prompt (Windows) and browse to a location where you want to store the course contents. | ||
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3. Clone this repository, or download and uncompress the zip file. Afterwards change to the `agile2023` folder. | ||
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4. Create the required Python environment: | ||
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Linux/macOS: | ||
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`conda env create -f environment/environment.yaml` | ||
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Windows: | ||
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`conda env create -f environment\environment.yaml` | ||
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The environment file will create a environment named *agile2023* using Python 3.11. In case you prefer a different name or Python version you need to edit the environment file. | ||
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### How to run | ||
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Activate the environment in the command prompt: | ||
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`conda activate agile2023` | ||
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Then change to the `notebook` folder. | ||
You can now start the Jupyter notebook from the command prompt. The notebook will open in your browser: | ||
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`jupyter lab course.ipynb` | ||
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## Further reading | ||
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Background on DaisyWorld: | ||
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[https://en.wikipedia.org/wiki/Daisyworld](https://en.wikipedia.org/wiki/Daisyworld) | ||
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Scientific literature about Campo and LUE: | ||
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M.P. de Bakker, K. de Jong, O. Schmitz, D. Karssenberg (2017). Design and demonstration of a data model to integrate agent-based and field-based modelling. Environmental Modelling & Software, 89, 172-189, DOI: [10.1016/j.envsoft.2016.11.016](https://doi.org/10.1016/j.envsoft.2016.11.016). | ||
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K. de Jong, D. Karssenberg (2019). A physical data model for spatio-temporal objects. Environmental Modelling & Software, 122, 104553, DOI: [10.1016/j.envsoft.2019.104553](https://doi.org/10.1016/j.envsoft.2019.104553). | ||
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K. de Jong, D. Panja, M. van Kreveld, D. Karssenberg (2021). An environmental modelling framework based on asynchronous many-tasks: Scalability and usability. Environmental Modelling & Software, 139, 104998, DOI: [10.1016/j.envsoft.2021.104998](https://doi.org/10.1016/j.envsoft.2021.104998). | ||
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[https://campo.computationalgeography.org/](https://campo.computationalgeography.org/) |