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saicharan2804
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ab2d2e2
1
Parent(s):
4081f26
Fixed error
Browse files- molgenevalmetric.py +27 -27
molgenevalmetric.py
CHANGED
@@ -36,7 +36,7 @@ sys.path.append(os.path.join(RDConfig.RDContribDir, 'SA_Score'))
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import sascorer
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import pandas as pd
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from fcd_torch import FCD
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from syba.syba import SybaClassifier
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# from tdc import Evaluator
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# from tdc import Oracle
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@@ -287,32 +287,32 @@ def fcd_metric(gen, train, n_jobs = 8, device = 'cuda:0'):
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fcd = FCD(device=device, n_jobs= n_jobs)
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return fcd(gen, train)
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def SYBAscore(gen):
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# def oracles(gen, train):
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# Result = {}
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import sascorer
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import pandas as pd
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from fcd_torch import FCD
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# from syba.syba import SybaClassifier
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# from tdc import Evaluator
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# from tdc import Oracle
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fcd = FCD(device=device, n_jobs= n_jobs)
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return fcd(gen, train)
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# def SYBAscore(gen):
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# """
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# Compute the average SYBA score for a list of SMILES strings.
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# Parameters:
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# - smiles_list (list of str): A list of SMILES strings representing molecules.
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# Returns:
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# - float: The average SYBA score for the list of molecules.
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# """
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# syba = SybaClassifier()
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# syba.fitDefaultScore()
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# scores = []
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# for smiles in gen:
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# try:
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# score = syba.predict(smi=smiles)
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# scores.append(score)
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# except Exception as e:
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# print(f"Error processing SMILES '{smiles}': {e}")
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# continue
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# if scores:
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# return sum(scores) / len(scores)
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# else:
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# return None # Or handle empty list or all failed predictions as needed
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# def oracles(gen, train):
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# Result = {}
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