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Installation.md

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Installation of SIMSON

Back to overview.

Note: In its current version, SIMSON can only be fully used by members of the Potsdam Institute for Climate Impact Reserach (PIK).

SIMSON can be used for a multitude of purposes - creating own simulations, connecting it to other models, understanding the proposed economic module and ammending it for futher functionality.

The basic functionality of SIMSON can be analysed by skimming this documentation, the Bachelor's thesis on SIMSON and this github repository.

This section describes how to install SIMSON on your own device.

  1. Install Python 3

You can download Python here: https://www.python.org/downloads/ . For this project, Python 3 is required.

  1. Clone repository

Make sure that you have git installed, have generated a public ssh key and added it to your github account.

Clone the repository using $ git clone [email protected]:Merjo/simson.git from the parent directory of your choice.

  1. Install required dependencies

You can install all required dependencies using the command $ pip install -r requirements.txt

In some cases you might have to write pip3 instead of pip.

  1. Load data via submodules

The original data is stored on the Potsdam Institute of PIK's Gitlab server. It can not be shared with members of the public. Hence, active utilisation of SIMSON is restricted to PIK members.

They can be added to the Gitlab repository internally. Afterwards they can load the data in the submodules with the command $ git submodule update --recursive --remote.

  1. Set default working directory

The relative paths in the source code are adressed assuming the working directory to be the main SIMSON folder. Hence you need to set it as the default working directory. How this can be established varies on your integrated development environment (IDE) like PyCharm or VSCode.

For example, in PyCharm, this can be declared via clicking on the main project folder and choosingRun -> Edit Configurations.. -> Edit Configuration Templates... -> Working Directory.

  1. Running the code

Finally, the code can be tested by running some scripts. Most scripts in the src folder have a default test function that is called when running the script.

A great way to test SIMSON is running simson_base_model.py in src/base_model which should result in a success output on the console.

Another possibility is to run visualise_flows_and_stocks.py in src/visualisation. In the code, specific parameters can be set to get a matplotlib plot of predictions for specific flows and stocks in the SIMSON MFA (s. Fig. in the Introduction).

Go to section 3: Simulation