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First Thank you for update ORGAN!
in the recent logP update the ValueError you set, 0.0, is a "normal/right" value!
have a look:
low_logp = -2.12178879609
high_logp = 6.0429063424
logp = Crippen.MolLogP(Chem.MolFromSmiles(smile))
val = remap(logp, low_logp, high_logp)
val = np.clip(val, 0.0, 1.0)
return val
except ValueError:
return 0.0
-2.12 < 0.0 < 6.04
using this setting to train a set of smiles will end up all bad smiles because the value 0.0 is a "good" reward!
Maybe we can filter out bad smiles before calling logP?
The text was updated successfully, but these errors were encountered:
First Thank you for update ORGAN!
in the recent logP update the ValueError you set, 0.0, is a "normal/right" value!
have a look:
-2.12 < 0.0 < 6.04
using this setting to train a set of smiles will end up all bad smiles because the value 0.0 is a "good" reward!
Maybe we can filter out bad smiles before calling logP?
The text was updated successfully, but these errors were encountered: