Matrix-Weighted Networks

• Data
• Fig

Paper

• arXiv

To cite our work, please use the following BibTeX entry:

@article{tian2024matrix,
        title        = {Matrix-weighted networks for modeling multidimensional dynamics},
        author       = {Yu Tian and Sadamori Kojaku and Hiroki Sayama and Renaud Lambiotte},
        year         = 2024,
        publisher    = {{arXiv}},
        number       = {arXiv:2410.05188},
        eprint       = {arXiv:2410.05188},
        archiveprefix = {arxiv},
}

Reproducing Our Results

Setup

1. Set up the virtual environment and install the required packages:

   conda create -n matnet python=3.10
   conda activate matnet
   conda install -c conda-forge mamba -y
   mamba install -y -c bioconda -c conda-forge snakemake -y
   mamba install -c conda-forge graph-tool scikit-learn numpy==1.23.5 numba scipy pandas networkx seaborn matplotlib ipykernel tqdm black -y

2. Create a file config.yaml with the following content and place it under the workflow folder:

   data_dir: "data/"
   fig_dir: "figs/"

Run Simulation

Run the following command to execute the Snakemake workflow:

snakemake --cores 24 all

This will generate all files needed to produce the figures. Then, run

snakemake --cores 24 figs

You can change the number of cores to use, instead of 24.