Rename symbols to ensure consistency (#565)

cornac/data/dataset.py

@@ -645,7 +645,7 @@ class BasketDataset(Dataset):
     uir_tuple: tuple, required
         Tuple of 3 numpy arrays (user_indices, item_indices, rating_values).
 
-    basket_ids: numpy.array, required
+    basket_indices: numpy.array, required
         Array of basket indices corresponding to observation in `uir_tuple`.
 
     timestamps: numpy.array, optional, default: None
@@ -677,7 +677,7 @@ def __init__(
         bid_map,
         iid_map,
         uir_tuple,
-        basket_ids=None,
+        basket_indices=None,
         timestamps=None,
         extra_data=None,
         seed=None,
@@ -693,23 +693,31 @@ def __init__(
         )
         self.num_baskets = num_baskets
         self.bid_map = bid_map
-        self.basket_ids = basket_ids
+        self.basket_indices = basket_indices
         self.extra_data = extra_data
-        basket_sizes = list(Counter(basket_ids).values())
+        basket_sizes = list(Counter(basket_indices).values())
         self.max_basket_size = np.max(basket_sizes)
         self.min_basket_size = np.min(basket_sizes)
         self.avg_basket_size = np.mean(basket_sizes)
 
         self.__baskets = None
+        self.__basket_ids = None
         self.__user_basket_data = None
         self.__chrono_user_basket_data = None
 
+    @property
+    def basket_ids(self):
+        """Return the list of raw basket ids"""
+        if self.__basket_ids is None:
+            self.__basket_ids = list(self.bid_map.keys())
+        return self.__basket_ids
+
     @property
     def baskets(self):
         """A dictionary to store indices where basket ID appears in the data."""
         if self.__baskets is None:
             self.__baskets = defaultdict(list)
-            for idx, bid in enumerate(self.basket_ids):
+            for idx, bid in enumerate(self.basket_indices):
                 self.__baskets[bid].append(idx)
         return self.__baskets
 
@@ -836,7 +844,7 @@ def build(
             np.ones(len(u_indices), dtype="float"),
         )
 
-        basket_ids = np.asarray(b_indices, dtype="int")
+        basket_indices = np.asarray(b_indices, dtype="int")
 
         timestamps = (
             np.fromiter((int(data[i][3]) for i in valid_idx), dtype="int")
@@ -854,7 +862,7 @@ def build(
             bid_map=global_bid_map,
             iid_map=global_iid_map,
             uir_tuple=uir_tuple,
-            basket_ids=basket_ids,
+            basket_indices=basket_indices,
             timestamps=timestamps,
             extra_data=extra_data,
             seed=seed,

cornac/eval_methods/next_basket_evaluation.py

@@ -128,10 +128,10 @@ def get_gt_items(train_set, test_set, test_pos_items, exclude_unknowns):
             user_idx,
             item_indices,
             history_baskets=history_baskets,
-            history_basket_ids=bids[:-1],
+            history_bids=bids[:-1],
             uir_tuple=test_set.uir_tuple,
             baskets=test_set.baskets,
-            basket_ids=test_set.basket_ids,
+            basket_indices=test_set.basket_indices,
             extra_data=test_set.extra_data,
         )
 

cornac/models/gp_top/recom_gp_top.py

@@ -82,15 +82,13 @@ def score(self, user_idx, history_baskets, **kwargs):
 
         if self.use_personalized_popularity:
             if self.use_quantity:
-                history_basket_bids = kwargs.get("history_basket_ids")
+                history_bids = kwargs.get("history_bids")
                 baskets = kwargs.get("baskets")
                 p_item_freq = Counter()
-                (_, item_ids, _) = kwargs.get("uir_tuple")
                 extra_data = kwargs.get("extra_data")
-                for bid in history_basket_bids:
-                    ids = baskets[bid]
-                    for idx in ids:
-                        p_item_freq[item_ids[idx]] += extra_data[idx].get("quantity", 0)
+                for bid, iids in zip(history_bids, history_baskets):
+                    for idx, iid in zip(baskets[bid], iids):
+                        p_item_freq[iid] += extra_data[idx].get("quantity", 0)
             else:
                 p_item_freq = Counter([iid for iids in history_baskets for iid in iids])
             for iid, cnt in p_item_freq.most_common():