Make sure python version 3.6.5 is installed.

For Mac users, go to the /backend directory and do

python -m venv venv
source venv/bin/activate
pip install -r requirements.txt

For windows users, go to the /backend directory and do

python -m venv venv
cd venv/bin
activate.bat
cd ../../
pip install -r requirements.txt

Under the virtual environment, go to the backend/bn_edge_weights directory and do

python setup.py install

Currently the data loading process is hard coded. You need to download the data from the google drive folder. Copy the /metadata folder and place it in the /backend directory, then do

python generate_open_source_data.py

This script preprocesses the data (filtering and converting numerical variables to categorical ones), then calculates pairwise distances for all the features and performs hierarchical clustering. The resulting data will be placed in the /data directory. A config file will also be generated under the /data directory (/data/config.json) that has the following format:

{
  "test_0": {
    "raw_data_file": "test_0_raw.bin",
    "data_file": "test_0.bin",
    "base_avg_data_file": "test_0_base_avg.bin",
    "pdist_file": "test_0_pdist.bin",
    "clustering_file": "test_0_clustering.bin"
  },
  "fao_fused_spatio_temporal_cut_10": {
    "raw_data_file": "fao_fused_spatio_temporal_cut_10_raw.bin",
    "data_file": "fao_fused_spatio_temporal_cut_10.bin",
    "base_avg_data_file": "fao_fused_spatio_temporal_cut_10_base_avg.bin",
    "pdist_file": "fao_fused_spatio_temporal_cut_10_pdsit.bin",
    "clustering_file": "fao_fused_spatio_temporal_cut_10_clustering.bin"
  }
}

This config file is to help the backend keep track of the existing datasets and their corresponding files.

python manage.py runserver

Clone the repository from sortable-matrix, and place the repo folder under the same parent directory of the /causenet project folder. Follow the instructions in sortable-matrix to install it.

Afterwards, go to the /frontend directory and do

npm install

npm start