This project was made for the Evolutionary Computation class of the Informatics Engineering Master of the University of Coimbra
- Jessica Cunha, 2016239495, jessicac@student.dei.uc.pt
- Ricardo Paiva, 2016253100, rjpaiva@student.dei.uc.pt
- python3
- necessary libraries: random, copy, math, json, os, pandas, numpy, matplotlib, scipy,
- R
1 - Choose the parameters in the file parameters.py
that you want to test
2 - Run the file main.py
(see 2.1 if help is needed), and you'll see the best individual of each generation printed in the terminal. If you didn't changed the code, a folder will be created with the best individual of each generation and inside, a log folder with the fitness of all individuals of each generation. To avoid this folder of being generated see section 4
2.1 - You can run the code by using an IDE (suggestion: PyCharm) or, if you're using Linux or MacOS, the terminal, by running:
python3 main.py
For this you need to have R installed on your computer or the IDE RStudio.
1 - Open the file plot_generators.r
2 - Change the directory, to the folder where you have the files best.txt
(this will be generated when running the code in 1)
3 - Run the file by using RStudio or in the terminal:
Rscript plot_generator.r
1 - Open the file stat_alunos.py
2 - Change the code to load the data from the folder where your tests are. Note: The step 2 needs to be done first.
3 - Run the file by using an IDE or running in the terminal:
python3 stat_alunos.py
1 - Comment the lines 297 and 300-301 of the file main.py