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Update srbench.py
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@ -57,21 +57,19 @@ class SRbenchDataset(BaseDataset):
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return dataset
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def mydataset_postprocess(formula_str):
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# 1. 删除 Markdown 残留符号
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formula_str = formula_str.replace('×', '*').replace('·', '*').replace('÷', '/')
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formula_str = formula_str.replace('−', '-').replace('^', '**')
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formula_str = formula_str.replace('“', '"').replace('”', '"').replace('’', "'")
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# 2. 去除 markdown 反引号 ``` 和 $ 符号
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formula_str = formula_str.replace('`', '').replace('$', '').strip()
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# 3. 提取第一行公式(防止有多行解释性输出)
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formula_str = formula_str.split('\n')[0].strip()
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# 4. 用正则去除非合法字符(保留基本数学表达式)
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formula_str = re.sub(r'[^\w\s\+\-\*/\^\=\.\(\)]', '', formula_str)
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# 5. 确保左右去空格
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return formula_str.strip()
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class SRbenchDatasetEvaluator(BaseEvaluator):
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@ -122,7 +120,7 @@ class SRbenchDatasetEvaluator(BaseEvaluator):
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'R2': pd.Series(dtype=float),
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'SymbolicMatch': pd.Series(dtype=bool)
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})
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# 结构评分(用 LLM)
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for row in range(len(references)):
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#metrics['LLM_Score'] = float(self.llm_evaluate(predictions[row], references[row], mllm='gpt-4o'))
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n_var=self.dataset[row]["n_var"]
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