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I would like to provide my own datasest for retraining torisional-diffusion. There are some things that I do not know what value to put in for the pickle file. For example, the conformers dictionary has the following:
Degeneracy is not used in the code so it's safe to exclude. The boltzmann weight can be calculated if you know the energy and temperature since w = exp(-E/kbT) where E=energy, T=temperature, and kb=boltzmann constant.
Sorry for the delay and thank you very much @MatthewMasters for the answer!
All Matthew said is correct, moreover, if you don't use the Boltzmann weighted sampling (this is the way the ML community trains and evaluates these methods) you only need to have the rd_mol!
I would like to provide my own datasest for retraining torisional-diffusion. There are some things that I do not know what value to put in for the pickle file. For example, the conformers dictionary has the following:
{'geom_id': 123368967, 'set': 1, 'degeneracy': 3, 'totalenergy': -23.59133734, 'relativeenergy': 0.0, 'boltzmannweight': 0.8585, 'conformerweights': [0.28617, 0.28617, 0.28616], 'rd_mol': <rdkit.Chem.rdchem.Mol at 0x7f7b42014bd0>}
What should I put for boltzmannweight and degeneracy? Is there a setup script to take molfiles and convert them into the dataset for training?
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