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