duplicate outputs

Author: ahosler

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

@@ -86,6 +86,7 @@ def _build_model(self) -> pd.DataFrame:
             model = pm.auto_arima(y=y, X=X_in, **self.spec.model_kwargs)
 
             fitted_values[target] = model.predict_in_sample(X=X_in)
+            print(f"y: {y.head(10), y.tail(10)}")
             actual_values[target] = y
 
             # Build future dataframe
@@ -107,12 +108,7 @@ def _build_model(self) -> pd.DataFrame:
             )
             yhat_clean = pd.DataFrame(yhat, index=yhat.index, columns=["yhat"])
 
-            dt_columns[target] = pd.concat(
-                [
-                    df_encoded[self.spec.datetime_column.name],
-                    pd.Series(yhat_clean.index),
-                ]
-            )
+            dt_columns[target] = (df_encoded[self.spec.datetime_column.name],)
             conf_int_clean = pd.DataFrame(
                 conf_int, index=yhat.index, columns=["yhat_lower", "yhat_upper"]
             )
@@ -137,10 +133,14 @@ def _build_model(self) -> pd.DataFrame:
         yhat_upper_name = ForecastOutputColumns.UPPER_BOUND
         yhat_lower_name = ForecastOutputColumns.LOWER_BOUND
         for cat in self.categories:
+            print(f"cat: {cat}")
             output_i = pd.DataFrame()
             output_i["Date"] = dt_columns[f"{col}_{cat}"]
             output_i = output_i.set_index("Date")
             output_i["Series"] = cat
+            print(f"output_i: {output_i}")
+            print(f"actual_values: {actual_values[f'{col}_{cat}']}")
+
             output_i["input_value"] = actual_values[f"{col}_{cat}"]
 
             output_i["fitted_value"] = fitted_values[f"{col}_{cat}"]