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One thing that could be a bit difficult for a new user is defining the functional group factory. One possible approach could be to attach a unique atom to the atom you want to bind to the metal (e.g At) and I could use that to require less python tinkering for the user.
In bidentate it becomes important to check whether the ancillary ligand has successfully bound to the metal because in some conformers this may not be possible -> I think this would best be checked and filtered in between the metal optimizer step and the xTB step using the functionality that checks how many bonds are different between intended and reperceived optimized structure
Try a different example (like eliminating two methyl groups with dppe) and log everything that needs to be changed so collaborators can try their own ligands.
Pass test if a certain number of conformers optimize successfully with pyGSM
Error handling (probably want to catch exceptions inside function that the parallel pool calls so individual errors don't break all conformers)
How do you programmatically determine if you're running in a codespace or github action and the number of CPUs
The text was updated successfully, but these errors were encountered:
One thing that could be a bit difficult for a new user is defining the functional group factory. One possible approach could be to attach a unique atom to the atom you want to bind to the metal (e.g At) and I could use that to require less python tinkering for the user.
The text was updated successfully, but these errors were encountered: