The data for Supernova Classification using the Recurrent Neural Network in the CSST Ultra-Deep Field Survey

The data for Supernova Classification using the Recurrent Neural Network in the CSST Ultra-Deep Field Survey: This repository contains the datasets and analysis scripts. Project/├── README.md├── requirements.txt├── LICENSE│├── DATA/│ ├── TRAIN/│ └── TEST/│├── dataprocessing/│ ├── Data_processing.ipynb│ ├── combined_1aHEAD_and_ccHEAD_data.csv│ ├── covdict.npz│ ├── Pantheon+SH0ES.dat│ ├── PRED_vanilla_S_0_CLF_2_R_none_photometry_....pkl│ ├── SIDpar.csv│ ├── sname.txt│ ├── SNsel_data_noneZV63.csv│ ├── NPZ/│ └── TESTdataset/│└── BBC_fitting/ ├── BBC.ipynb ├── Flat_Cosmo_result_SN.pdf ├── flatcosmosBBC.npz ├── PRED_vanilla_S_0_CLF_2_R_none_photometry_....pkl └── SNsel_data_noneZV63.csv DATA: Contains the datasets used for training the SNN model, as well as the simulated data generated for this project. dataprocessing: Contains the preprocessing scripts for the classified supernova data. The light-curve fitting has already been performed, and the fitting results are included in the alldatadict* files. These files can be used directly without rerunning the fitting procedure. BBC fitting: Contains the scripts for performing BEAMS with Bias Corrections (BBC) fitting on the classified supernova sample.