Hypergraph Wavelets

Conda environment

We recommend the usage of a conda environment for running the experiments. The used conda environment can be found at environment.yml

Dataset download

The data can be downloaded on the following link: https://sea-ad-spatial-transcriptomics.s3.amazonaws.com/index.html#middle-temporal-gyrus/all_donors-h5ad/

You can then extract your zip file into the data/raw folder.

Dataset pre-processing

After all the data was extracted into the raw files, you can use the notebook found at : notebooks/create_patients_section_files.ipynb to process the raw data and divide the dataset from patients level to section level data. This notebook will create all the section data in the folder: data/interim/section_data

Extracting wavelets features

Once the data is on the correct location you can simple run python3 main.py

The resulting wavelets features will be stored on data/processed/wavelet_features

Evaluating performance

We evaluated performance using vendi score and linear probing. Each one of those can be computed on the following scripts:

python3 vendi.py

python3 linear_probing.py