def compute()

in yourbench/pipeline/citation_score_filtering.py [0:0]

• 10 lines of code
• 7 McCabe index (conditional complexity)

    def compute(self, citations: Sequence[str], chunks: Sequence[str], answer: str) -> tuple[float, float, float]:
        if not citations or (not chunks and not answer):
            return 0.0, 0.0, 0.0

        citation_count = len(citations)
        chunk_scores = [max((self._ratio(c, ch) for ch in chunks), default=0) for c in citations]
        ans_scores = [self._ratio(c, answer) for c in citations]

        avg_chunk = sum(chunk_scores) / citation_count
        avg_ans = sum(ans_scores) / citation_count
        final = self.alpha * avg_chunk + self.beta * avg_ans

        return avg_ans, avg_chunk, final