relevances.py

# return a list of relevances for supplied ids, given a dictionary of ratings
# unrated items get a score of zero
def get_relevances( ratings, ids ):
	r = [ 0. ] * len( ids )
	for i, x in enumerate( ids ):
		try:
			r[i] = ratings[x] - relevance_bias
		except KeyError:
			pass
	
	return r
			

# returns unsorted best possible relevances from the test set
# if the list is shorter than ndcg_k, it gets padded with zeros
def get_best_relevances( ratings, ids, ndcg_k ):
	r = [ ratings[x] - relevance_bias for x in ids if x in ratings and ratings[x] > relevance_bias ]
	
	if len( r ) < ndcg_k:
		return r + [ 0. ] * ( ndcg_k - len( r ))
	else:
		return r


def get_worst_relevances( ratings, ids, ndcg_k ):
	r = [ ratings[x] - relevance_bias for x in ids if x in ratings and ratings[x] < relevance_bias ]
	if len( r ) < ndcg_k:
		return r + [ 0. ] * ( ndcg_k - len( r ))
	else:
		return r