dig.ggraph.evaluation¶
Evaluation interfaces under dig.ggraph.evaluation
.
Evaluator for constrained optimization task. |
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Evaluator for property optimization task. |
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Evaluator for random generation task. |
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class
ConstPropOptEvaluator
[source]¶ Evaluator for constrained optimization task. Metric is the average property improvements, similarities and success rates under the similarity threshold 0.0, 0.2, 0.4, 0.6.
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static
eval
(input_dict)[source]¶ Run evaluation in constrained optimization task. Compute the average property improvements, similarities and success rates under the similarity threshold 0.0, 0.2, 0.4, 0.6.
- Parameters
input_dict (dict) – A python dict with the following items: “mols_0”, “mols_2”, “mols_4”, “mols_6” — the list of optimized molecules under the similarity threshold 0.0, 0.2, 0.4, 0.6, all represented by rdkit Chem.RWMol or Chem.Mol objects; “inp_smiles” — the list of SMILES strings of input molecules to be optimized.
- Return type
dict
a python dict with the following items: 0, 2, 4, 6 — the metric values under the similarity threshold 0.0, 0.2, 0.4, 0.6. The metric values are given in the form of a tuple (success rate, mean of similarity, standard deviation of similarity, mean of property improvement, standard deviation of property improvement).
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static
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class
PropOptEvaluator
(prop_name='plogp')[source]¶ Evaluator for property optimization task. Metric is top-3 property scores among generated molecules.
- Parameters
prop_name (str) – A string indicating the name of the molecular property, use ‘plogp’ for penalized logP or ‘qed’ for Quantitative Estimate of Druglikeness (QED). (default:
plogp
)
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eval
(input_dict)[source]¶ Run evaluation in property optimization task. Find top-3 molucules which have highest property scores.
- Parameters
input_dict (dict) – A python dict with the following items: “mols” — a list of generated molecules reprsented by rdkit Chem.Mol or Chem.RWMol objects.
- Return type
dict
a python dict with the following items: 1 — information of molecule with the highest property score; 2 — information of molecule with the second highest property score; 3 — information of molecule with the third highest property score. The molecule information is given in the form of a tuple (SMILES string, property score).
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class
RandGenEvaluator
[source]¶ Evaluator for random generation task. Metric is validity ratio, uniqueness ratio, and novelty ratio (all represented in percentage).
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static
eval
(input_dict)[source]¶ Run evaluation in random generation task. Compute the validity ratio, uniqueness ratio and novelty ratio of generated molecules (all represented in percentage).
- Parameters
input_dict (dict) – A python dict with the following items: “mols” — the list of generated molecules reprsented by rdkit Chem.RWMol or Chem.Mol objects; “train_smiles” — the list of SMILES strings used for training.
- Return type
dict
a python dict with the following items: “valid_ratio” — validity percentage; “unique_ratio” — uniqueness percentage; “novel_ratio” — novelty percentage.
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static