Skeleton for clustering project.
- Implement a similarity metric (metric in io.py, compute similarity in cluster.py)
- Implement a clustering method based on a partitioning algorithm (used k means)
- Implement a clustering method based on a hierarchical algorithm (used agglomerative clustering)
- Answer the questions given in the homework assignment
The main file that you will need to modify is cluster.py and the corresponding test_cluster.py. utils.py contains helpful classes that you can use to represent Active Sites. io.py contains some reading and writing files for interacting with PDB files and writing out cluster info.
.
├── README.md
├── data
│ ...
├── hw2skeleton
│ ├── __init__.py
│ ├── __main__.py
│ ├── cluster.py
│ ├── io.py
│ └── utils.py
└── test
├── test_cluster.py
└── test_io.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.