def calc_ndcg()

in src/metrics.py [0:0]

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

def calc_ndcg(relevant_docs, retrieved_docs, k, score_type='rank',  retrieved_distances=None):
    if len(retrieved_docs) <2:
        return 0.00
    y_true = np.array([[1 if doc in relevant_docs else 0 for doc in retrieved_docs]])
    if score_type == 'rank':
        y_scores = np.array([[1 / (rank + 1) for rank in range(len(retrieved_docs))]])
    elif score_type == 'distance':
        y_scores = np.array([[1 - dist for dist in retrieved_distances]])
    ndcg = ndcg_score(y_true, y_scores, k=k)
    return ndcg