Skeleton for Smith-Waterman project.

1. Implement Smith-Waterman algorithm.
2. Optimize a scoring matrix using a simulated annealing algorithm.

All functions are contained within SmithWaterman.py.

To use the package, first run

conda install --yes --file requirements.txt

to install all the dependencies in requirements.txt. Then the package's main function (located in hw2skeleton/__main__.py) can be run as follows

python -m hw2skeleton -P data test.txt

Testing is as simple as running

python -m pytest

from the root directory of this project.

Original design by Scott Pegg. Refactored and updated by Tamas Nagy.