'Computes a neighborhood consisting of the  n users to a given user
based on the strategy implemented in this method.
Parameters
user_id:  int or string
ID of user for which to find most similar other users
data_model: DataModel instance
The data model that will be the source for the possible
candidates
similarity: string
The similarity to compute the neighborhood  (default = \'user_similarity\')
|user_similarity\'|
distance: function
Pairwise metric to compute the similarity between the users.
nhood_size: int
The neighborhood size (default = None all users)'

def user_neighborhood(self, user_id, data_model, similarity='user_similarity', distance=None, nhood_size=None, **params):

    user_ids = data_model.user_ids()
    return (user_ids[(user_ids != user_id)] if user_ids.size else user_ids)
