JoshRackers / equivariant_electron_density

Generate and predict molecular electron densities with Euclidean Neural Networks
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Shape Discrepancy in ML-DNA training Data for 'coefficients', 'exponents', and 'norms' #4

Open 12138xs opened 1 week ago

12138xs commented 1 week ago

I am currently trying to reproduce the results of the ML-DNA section of your model. During this process, I encountered a discrepancy between the documented and actual data shapes for the 'coefficients', 'exponents', and 'norms' keys. The documentation specifies that these keys should have a shape of (n_atom, ...). However, the actual shape in the training data, as found at Zenodo link, is (n_atom + 2, ...). Could you please help identify the reason for this shape discrepancy? Any insights or clarifications would be greatly appreciated.

Thank you.

ajemyunglee commented 1 week ago

Hi,

I looked into this. The 'coefficients', 'exponents', and 'norms' have the correct shape. It turns out the data sets were missing information from the first two atoms. I've uploaded the corrected data sets as version 2 in the repository:

https://zenodo.org/records/13932625

Thanks for catching this, and good luck with your research!

On Mon, Oct 14, 2024 at 8:43 PM CenJH @.***> wrote:

I am currently trying to reproduce the results of the ML-DNA section of your model. During this process, I encountered a discrepancy between the documented and actual data shapes for the 'coefficients', 'exponents', and 'norms' keys. The documentation specifies that these keys should have a shape of (n_atom, ...). However, the actual shape in the training data, as found at Zenodo link https://zenodo.org/records/7072319, is (n_atom + 2, ...). Could you please help identify the reason for this shape discrepancy? Any insights or clarifications would be greatly appreciated.

Thank you.

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