ALS.Recommend function coo_matrix index access problem

[msh-tf]

So the als.recommend function takes an 'int' for userid and a 'coo_matrix' for item_user_data.T which is a coo_matrix, however you cannot index coo_matrix that way so it fails for me

In [46]: ratings
Out[46]: 
<635810x14744082 sparse matrix of type '<class 'numpy.float64'>'
	with 115307196 stored elements in COOrdinate format>

In [47]: model.recommend(5, ratings.T)
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-46-2d2962f49703> in <module>()
----> 1 model.recommend(5, ratings.T)

/Users/ml/lib/python3.5/site-packages/implicit/als.py in recommend(self, userid, user_items, N)
     87 
     88         # calcualte the top N items, removing the users own liked items from the results
---> 89         liked = set(user_items[userid].indices)
     90         count = N + len(liked)
     91         if count < len(scores):

TypeError: 'coo_matrix' object does not support indexing

If not a coo_matrix what should I pass to the recommend function?

[benfred]

It should be a CSR matrix - I'll add some documentation this weekend to clear up, but something like 'model.recommend(5, ratings.T.tocsr())' should work.

[msh-tf]

Worked!
Thanks