Update popularity bias at k

[nsbits]

Description

Line 118 in 'reclist/reclist/metrics/standard_metrics.py' (url)
The denominator should be len(p[:k)

def popularity_bias_at_k(y_preds, x_train, k=3):
    # estimate popularity from training data
    pop_map = collections.defaultdict(lambda : 0)
    num_interactions = 0
    for session in x_train:
        for event in session:
            pop_map[event] += 1
            num_interactions += 1
    # normalize popularity
    pop_map = {k:v/num_interactions for k,v in pop_map.items()}
    all_popularity = []
    for p in y_preds:
        average_pop = sum(pop_map.get(_, 0.0) for _ in p[:k]) / len(p) if len(p) > 0 else 0
        all_popularity.append(average_pop)
    return sum(all_popularity) / len(y_preds)

should not the len(_p) be len(_p[:k]) ?
we will be looking till the kth slice
This is what I think should be popularity_bias@k

def popularity_bias_at_k(y_preds, x_train, k=3):
    # estimate popularity from training data
    pop_map = collections.defaultdict(lambda : 0)
    num_interactions = 0
    for session in x_train:
        for event in session:
            pop_map[event] += 1
            num_interactions += 1
    # normalize popularity
    pop_map = {k:v/num_interactions for k,v in pop_map.items()}
    all_popularity = []
    for p in y_preds:
        average_pop = sum(pop_map.get(_, 0.0) for _ in p[:k]) / len(p[:k]) if len(p) > 0 else 0
        all_popularity.append(average_pop)
    return sum(all_popularity) / len(y_preds)