VaLPAS documentation#

Installation#

1. Clone the Repository#

git clone <repository-url>
cd <repository-name>

2. Create Virtual Environment#

Steps 2. & 3. are only necessary if an encapuslated virtual python environment is desired. An alternative to venv is to use conda. For more information on anaconda / conda refer to https://anaconda.org/. If no virtual environment is desired or already exists skip to Step 4.

python -m venv valpas-env

3. Activate Virtual Environment#

To activate the virtual environment use the appropirate command listed below.

Windows#
valpas-env\Scripts\activate
macOS/Linux#
source valpas-env/bin/activate

4. Install valpas#

pip install .

5. Install Additional Dependencies for Demonstration Notebook#

These dependencies are only necessary if the included demonstration notebook is being run locally.

pip install -r requirements.txt

Quick Setup (One Command)#

Windows#
python -m venv valpas-env && valpas-env\Scripts\activate && pip install . && pip install -r requirements.txt
macOS/Linux#
python -m venv valpas-env && source valpas-env/bin/activate && pip install . && pip install -r requirements.txt

Usage#

Starting the Environment#

Always activate the virtual environment before working on the project.

Windows#
valpas-env\Scripts\activate
macOS/Linux#
source valpas-env/bin/activate

Running Jupyter#

Once the environment is activated, start Jupyter:

jupyter notebook

or

jupyter lab

Deactivating the Environment#

When you’re done working:

deactivate

Dependencies#

The project uses the following main libraries:

  • Jupyter: Interactive notebook environment

  • PyTorch: Deep learning framework

  • Scikit-learn: Machine learning library

  • Matplotlib: Plotting library

  • Seaborn: Statistical data visualization

Troubleshooting#

Python Version Issues#

If you need a specific Python version, create the environment with:

python3.13 -m venv valpas-env  # Replace 3.13 with your desired version

PyTorch GPU Support#

For CUDA-enabled PyTorch installation, visit pytorch.org update torch with the appropriate command for your system.

pip install --force-reinstall torch torchvision --index-url <specified url>

Permission Issues#

If you encounter permission errors, try:

pip install --user .
pip install --user -r requirements.txt

API Reference#