- fixed warning: ChainedAssignmentError

- added theta forcaster to auto-select-series

Author: skjoracle

ads/opctl/operator/lowcode/forecast/meta_selector.py

@@ -214,6 +214,12 @@ def __init__(self):
                 "model": "autots",
                 "priority": 17,
             },
+            # Rule 18: Theta Forecaster
+            "theta_0": {
+                "conditions": [],
+                "model": "theta",
+                "priority": 18,
+            },
         }
 
     def _evaluate_condition(self, value, operator, threshold):

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

@@ -346,40 +346,39 @@ def populate_series_output(
             ) from e
 
         if (output_i.shape[0] - self.horizon) == len(fit_val):
-            output_i["fitted_value"].iloc[: -self.horizon] = (
-                fit_val  # Note: may need to do len(output_i) - (len(fit_val) + horizon) : -horizon
-            )
+            output_i.loc[output_i.index[
+                : -self.horizon], "fitted_value"] = fit_val  # Note: may need to do len(output_i) - (len(fit_val) + horizon) : -horizon
         elif (output_i.shape[0] - self.horizon) > len(fit_val):
             logger.debug(
                 f"Fitted Values were only generated on a subset ({len(fit_val)}/{(output_i.shape[0] - self.horizon)}) of the data for Series: {series_id}."
             )
             start_idx = output_i.shape[0] - self.horizon - len(fit_val)
-            output_i["fitted_value"].iloc[start_idx : -self.horizon] = fit_val
+            output_i.loc[output_i.index[start_idx: -self.horizon], "fitted_value"] = fit_val
         else:
-            output_i["fitted_value"].iloc[start_idx : -self.horizon] = fit_val[
-                -(output_i.shape[0] - self.horizon) :
+            output_i.loc[output_i.index[start_idx: -self.horizon], "fitted_value"] = fit_val[
+                -(output_i.shape[0] - self.horizon):
             ]
 
         if len(forecast_val) != self.horizon:
             raise ValueError(
                 f"Attempting to set forecast along horizon ({self.horizon}) for series: {series_id}, however forecast is only length {len(forecast_val)}"
                 f"\nPlease refer to the troubleshooting guide at {TROUBLESHOOTING_GUIDE} for resolution steps."
             )
-        output_i["forecast_value"].iloc[-self.horizon :] = forecast_val
+        output_i.loc[output_i.index[-self.horizon:], "forecast_value"] = forecast_val
 
         if len(upper_bound) != self.horizon:
             raise ValueError(
                 f"Attempting to set upper_bound along horizon ({self.horizon}) for series: {series_id}, however upper_bound is only length {len(upper_bound)}"
                 f"\nPlease refer to the troubleshooting guide at {TROUBLESHOOTING_GUIDE} for resolution steps."
             )
-        output_i[self.upper_bound_name].iloc[-self.horizon :] = upper_bound
+        output_i.loc[output_i.index[-self.horizon:], self.upper_bound_name] = upper_bound
 
         if len(lower_bound) != self.horizon:
             raise ValueError(
                 f"Attempting to set lower_bound along horizon ({self.horizon}) for series: {series_id}, however lower_bound is only length {len(lower_bound)}"
                 f"\nPlease refer to the troubleshooting guide at {TROUBLESHOOTING_GUIDE} for resolution steps."
             )
-        output_i[self.lower_bound_name].iloc[-self.horizon :] = lower_bound
+        output_i.loc[output_i.index[-self.horizon:], self.lower_bound_name] = lower_bound
 
         self.series_id_map[series_id] = output_i
         self.verify_series_output(series_id)