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#What is this

This is the result from my MBA in big data and artificial intelligence at the University of Sao Paulo.

#How is the code organized?

The code is very disorganized. Python is not my go to language and I was in rush so the code is very disorganized. Few functions, repeated lines.

That being said, there is a logic behind it. In the code section it is described in a little bit more detail.

#How to use it?

For this project there was a very important library that is simpsom. The version used it is in the folder simpsomlib, and the rest was installed as needed. If you want to reproduce you can probably use the file requirements.txt, however I had a few issues installing simpsom. Hence, the library used for the research in the repository.

#Organization (-ish)

Like stated before, the code is not very organized. However, there is a flow to it.

  1. gnu.py: Here is core of the research. In this file there is all the data treatment, parameters, everything how to the code was runned. Once in your desired enviroment, with python gnu.py you will get the results from this research.

  2. map_reader: simpsom has a way of saving the map's weight without the necessity to train again. This file uses the saved maps to generate some graphs used in the final essay.

  3. visualize_map: finally, it was necessary to understand the moving patterns of the animals and this file generated geographical maps with their movements.

#Results

The graphs resulted from this research are in the file graphs.zip