fix NP formatting

Author: ahosler

ads/opctl/operator/lowcode/forecast/model/base_model.py

@@ -45,7 +45,6 @@
     SupportedModels,
     SpeedAccuracyMode,
 )
-from ..const import ForecastOutputColumns
 from ..operator_config import ForecastOperatorConfig, ForecastOperatorSpec
 from ads.common.decorator.runtime_dependency import runtime_dependency
 from .forecast_datasets import ForecastDatasets, ForecastOutput
@@ -711,9 +710,6 @@ def local_explainer(self, kernel_explainer, series_id, datetime_col_name) -> Non
         local_kernel_explnr_df = pd.DataFrame(
             local_kernel_explnr_vals, columns=data.columns
         )
-        local_kernel_explnr_df = local_kernel_explnr_df.rename(
-            {datetime_col_name: ForecastOutputColumns.DATE}, axis=0
-        )
         self.local_explanation[series_id] = local_kernel_explnr_df
 
     def get_explain_predict_fn(self, series_id, fcst_col_name="yhat"):

ads/opctl/operator/lowcode/forecast/model/neuralprophet.py

@@ -440,15 +440,17 @@ def explain_model(self):
         for s_id, expl_df in self.explanations_info.items():
             expl_df = expl_df.rename(rename_cols, axis=1)
             # Local Expl
-            self.local_explanation[s_id] = self.get_horizon(expl_df)
+            self.local_explanation[s_id] = self.get_horizon(expl_df).drop(
+                ["future_regressors_additive"], axis=1
+            )
             self.local_explanation[s_id]["Series"] = s_id
-
+            self.local_explanation[s_id].index.rename(self.dt_column_name, inplace=True)
             # Global Expl
             g_expl = self.drop_horizon(expl_df).mean()
             g_expl.name = s_id
             global_expl.append(g_expl)
         self.global_explanation = pd.concat(global_expl, axis=1)
-        self.formatted_global_explanation = self.global_explanation.drop(
+        self.global_explanation = self.global_explanation.drop(
             index=["future_regressors_additive"], axis=0
         )
         self.formatted_global_explanation = (

tests/operators/forecast/test_datasets.py

@@ -19,8 +19,8 @@
 
 
 DATASETS_LIST = [
-    # "AirPassengersDataset",
-    # "AusBeerDataset",
+    "AirPassengersDataset",
+    "AusBeerDataset",
     "AustralianTourismDataset",
     # # "ETTh1Dataset",
     # # "ETTh2Dataset",
@@ -34,7 +34,7 @@
     # # "ILINetDataset",
     # # "IceCreamHeaterDataset",
     # # "MonthlyMilkDataset",
-    # "MonthlyMilkIncompleteDataset",
+    "MonthlyMilkIncompleteDataset",
     # # "SunspotsDataset",
     # # "TaylorDataset",
     # # "TemperatureDataset",
@@ -43,7 +43,7 @@
     # "UberTLCDataset",
     #     "WeatherDataset",
     #     "WineDataset",
-    # "WoolyDataset",
+    "WoolyDataset",
 ]
 
 MODELS = [
@@ -93,7 +93,7 @@ def verify_explanations(global_fn, local_fn, yaml_i, additional_cols):
     glb_expl = pd.read_csv(global_fn, index_col=0)
     loc_expl = pd.read_csv(local_fn)
     assert loc_expl.shape[0] == PERIODS
-    for x in ["Date", "Series"]:
+    for x in [yaml_i["spec"]["datetime_column"]["name"], "Series"]:
         assert x in set(loc_expl.columns)
     for x in additional_cols:
         assert x in set(loc_expl.columns)