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from syba.syba import SybaClassifier | |
def SYBAscore(smiles_list): | |
""" | |
Compute the average SYBA score for a list of SMILES strings. | |
Parameters: | |
- smiles_list (list of str): A list of SMILES strings representing molecules. | |
Returns: | |
- float: The average SYBA score for the list of molecules. | |
""" | |
syba = SybaClassifier() | |
syba.fitDefaultScore() | |
scores = [] | |
for smiles in smiles_list: | |
try: | |
score = syba.predict(smi=smiles) | |
scores.append(score) | |
except Exception as e: | |
print(f"Error processing SMILES '{smiles}': {e}") | |
continue | |
if scores: | |
return sum(scores) / len(scores) | |
else: | |
return None # Or handle empty list or all failed predictions as needed | |
syba = SybaClassifier() | |
syba.fitDefaultScore() | |
smi = "O=C(C)Oc1ccccc1C(=O)O" | |
print(syba.predict(smi)) | |