Merge pull request #156 from ricardogsilva/155-api-error-when-retriev…

…ing-related-station-data

Adding logic for processing yearly station measurements

arpav_ppcv/operations.py

@@ -227,12 +227,15 @@ def get_coverage_time_series(
             )
             if station_data is not None:
                 raw_station_data, station = station_data
-                data_ = _process_seasonal_station_data(
+                data_ = _process_station_data(
                     raw_station_data,
                     observation_smoothing_strategies,
                     start,
                     end,
                     base_name=coverage.configuration.related_observation_variable.name,
+                    aggregation_type=(
+                        coverage.configuration.observation_variable_aggregation_type
+                    ),
                 )
                 station_data_series_key = "_".join(
                     (
@@ -325,32 +328,39 @@ def _get_station_data(
     return result
 
 
-def _process_seasonal_station_data(
+def _process_station_data(
     raw_data: list[observations.SeasonalMeasurement],
     smoothing_strategies: list[base.ObservationDataSmoothingStrategy],
     time_start: Optional[dt.datetime],
     time_end: Optional[dt.datetime],
     base_name: str,
-) -> pd.DataFrame:
+    aggregation_type: base.ObservationAggregationType,
+):
     df = pd.DataFrame([i.model_dump() for i in raw_data])
-    df = df[["value", "season", "year"]]
     df = df.rename(columns={"value": base_name})
-
-    df["season_month"] = (
-        df["season"]
-        .astype("string")
-        .replace(
-            {
-                "Season.WINTER": "01",
-                "Season.SPRING": "04",
-                "Season.SUMMER": "07",
-                "Season.AUTUMN": "10",
-            }
+    if aggregation_type == base.ObservationAggregationType.SEASONAL:
+        df["season_month"] = (
+            df["season"]
+            .astype("string")
+            .replace(
+                {
+                    "Season.WINTER": "01",
+                    "Season.SPRING": "04",
+                    "Season.SUMMER": "07",
+                    "Season.AUTUMN": "10",
+                }
+            )
         )
-    )
-    df["time"] = pd.to_datetime(
-        df["year"].astype("string") + "-" + df["season_month"] + "-01", utc=True
-    )
+        df["time"] = pd.to_datetime(
+            df["year"].astype("string") + "-" + df["season_month"] + "-01", utc=True
+        )
+    elif aggregation_type == base.ObservationAggregationType.YEARLY:
+        df["time"] = pd.to_datetime(df["year"].astype("string"), utc=True)
+    else:
+        raise RuntimeError(
+            f"Unable to process station data with aggregation type {aggregation_type}"
+        )
+
     df = df[[base_name, "time"]]
     df.set_index("time", inplace=True)
     if time_start is not None: