fix item_id field in repository datasets

pts/dataset/repository/_gp_copula_2019.py

@@ -149,6 +149,7 @@ def save_dataset(dataset_path: Path, ds_info: GPCopulaDataset):
                 # Handles adding categorical features of rolling
                 # evaluation dates
                 cat=[cat - ds_info.num_series * (cat // ds_info.num_series)],
+                item_id=cat,
             )
             for cat, data_entry in enumerate(dataset)
         ],

pts/dataset/repository/_lstnet.py

@@ -162,7 +162,10 @@ def generate_lstnet_dataset(dataset_path: Path, dataset_name: str):
         if len(sliced_ts) > 0:
             train_ts.append(
                 to_dict(
-                    target_values=sliced_ts.values, start=sliced_ts.index[0], cat=[cat],
+                    target_values=sliced_ts.values,
+                    start=sliced_ts.index[0],
+                    cat=[cat],
+                    item_id=cat,
                 )
             )
 

pts/dataset/repository/_m4.py

@@ -66,7 +66,9 @@ def generate_m4_dataset(
     save_to_file(
         train_file,
         [
-            to_dict(target_values=target, start=mock_start_dataset, cat=[cat])
+            to_dict(
+                target_values=target, start=mock_start_dataset, cat=[cat], item_id=cat
+            )
             for cat, target in enumerate(train_target_values)
         ],
     )
@@ -74,8 +76,10 @@ def generate_m4_dataset(
     save_to_file(
         test_file,
         [
-            to_dict(target_values=target, start=mock_start_dataset, cat=[cat])
+            to_dict(
+                target_values=target, start=mock_start_dataset, cat=[cat], item_id=cat
+            )
             for cat, target in enumerate(test_target_values)
         ],
     )
- 
+

pts/dataset/repository/_util.py

@@ -14,12 +14,17 @@
 import json
 import os
 from pathlib import Path
-from typing import Dict, List, Optional
+from typing import Dict, List, Optional, Any
 
 import numpy as np
 
 
-def to_dict(target_values: np.ndarray, start: str, cat: Optional[List[int]] = None):
+def to_dict(
+    target_values: np.ndarray,
+    start: str,
+    cat: Optional[List[int]] = None,
+    item_id: Optional[Any] = None,
+):
     def serialize(x):
         if np.isnan(x):
             return "NaN"
@@ -34,6 +39,9 @@ def to_dict(target_values: np.ndarray, start: str, cat: Optional[List[int]] = No
 
     if cat is not None:
         res["feat_static_cat"] = cat
+    
+    if item_id is not None:
+        res["item_id"] = item_id
 
     return res