Four sub-networks combined to produce a powerful predictor
Catersian Coordinates Network
Spherical Coordinates Network
Spherical Harmonics Network
Fourier Transform Network
@article{deepice,
author = {Fulford, Maxwell and Salvalaglio, Matteo and Molteni, Carla},
title = {DeepIce: a Deep Neural Network Approach to Identify Ice and Water Molecules},
journal = {Journal of Chemical Information and Modeling},
doi = {10.1021/acs.jcim.9b00005}}
python main_deepice.py --help
Training with 10 nearest neighbours, batch size of 30 and 5 epochs:
python main_deepIce.py --Train --nearest_neighbours 10 --batch_size 30 --n_epochs 5 --weights_file 'models/deepice_nn10.h5' --data 'data/deepice_traindata.npz' --output_weights 'models/deepice_nn10_trained.h5
Predicting on a simulation slab with 5760 molecules
python main_deepIce.py --Predict --data_file 'simulation_data.npz' --nearest_neighbours 10 --num_mols 5760
Evaluating accuracy on data set:
python main_deepIce.py --Evaluate --data_file 'data/deepice_testdata.npz' --nearest_neighbours 13