In this repository we provide the implementation of the project "Volume maximization for cross approximation" of the class Low-Rank Approximation Techiques, MATH-403
Authors: Fabio Matti, Anna Paulish
You can reproduce our results with
git clone https://github.com/FMatti/ACA-SPSD.git
cd ACA-SPSD
python main.py
This takes about 5 minutes. If dependency problems arise, you can image our Python environment using
python -m venv .venv
source .venv/bin/activate # on Linux, macOS
.venv\Scripts\activate.bat # on Windows
pip install --upgrade pip
pip install -r requirements.txt
Our implementations require a Python version
Our implementations are located in the src/
directory. Our results can be found in the Jupyter notebook main.ipynb
or equivalently reproduced by running the Python script main.py
.
ACA-SPSD
│ README.md
| main.ipynb (Jupyter notebook with our results)
| main.py (equivalent Python script with our results)
|
└───src
| | algorithms.py (implementations of the two algorithms)
| | helpers.py (helper functions)
| | matrices.py (definition of the example matrices)