Install¶
The latest release of SKPAR can be found on GitHub.
User (w/o sudo or root privilege):
pip3 install --upgrade --user skpar
Please omit the –user option above if installing within a virtual environment.
Developer:
Clone the repository and go to the newly created directory of the repository.
Issue the following command from the root directory of the repository.
pip3 install --upgrade --user -e .
Please omit the –user option above if installing within a virtual environment.
To uninstall:
pip3 uninstall skpar
Dependencies¶
SKPAR’s operation requires:
- YAML support, for setting up the optimisation,
- the DEAP library, for the Particle Swarm Optimisation engine,
- NumPy for data structures, and,
- Matplotlib for plotting.
Test¶
If cloning the repository, once installation of SKPAR and its dependencies is complete, it is important to ensure that the test suite runs without failures, so:
cd skpar_folder/test
python3 -m unittest
Tests runtime is under 30 sec and should result in no errors or failures.