fixed the coefficient before Lenard-jones terms #58
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update bugfix by master
jchodera
requested changes
Nov 2, 2020
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Looks good except the docstring!
Do you need to add a scaling factor that accounts for exceptions too?
Normally, 1-2 and 1-3 interactions are excluded, and 1-4 interactions are scaled.
AMBER sets this scaling at 0.5, but it could be flexible, or we could just have a network predict these exceptions specifically for every 1-4 pair for more flexibility.
| @@ -225,7 +225,7 @@ def lj( | |||
| torch.lt(x, switch), torch.zeros_like(sigma_over_x), sigma_over_x, | |||
| ) | |||
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| return epsilon * ( | |||
| return 4.0 * epsilon * ( | |||
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Line 192 (the docstring containing the functional form) should be updated too!
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