Update backend/api/routes/biology.py

backend/api/routes/biology.py

@@ -46,29 +46,23 @@ async def biology_rule_detail(rule_name: str, hub: DataHub = Depends(get_datahub
 @router.get("/chill-units")
 async def biology_chill_units(
     season_start: str = Query("2025-11-01", description="Season start (YYYY-MM-DD)"),
-    hub: DataHub = Depends(get_datahub),
 ):
-    """Accumulated chill units from IMS hourly temperature.
+    """Accumulated chill units from ThingsBoard on-site temperature.
 
+    Uses Air2 (under panels) and Air1 (open field/ambient) hourly averages.
     Model: T<=7 → +1 CU/h, 7<T<=10 → +0.5, 10<T<=18 → 0, T>18 → -1.
     Daily totals clipped at 0.
     """
     import numpy as np
     import pandas as pd
-
-    try:
-        df = hub.weather._load_df()
-        if df.empty:
-            return {"error": "No IMS data available"}
-        if "timestamp_utc" in df.columns:
-            df = df.set_index(pd.to_datetime(df["timestamp_utc"], utc=True))
-
-        start = pd.Timestamp(season_start, tz="UTC")
-        subset = df.loc[start:]
-        if subset.empty or "air_temperature_c" not in subset.columns:
-            return {"error": "No temperature data in season range"}
-
-        hourly = subset["air_temperature_c"].resample("1h").mean().dropna()
+    from datetime import datetime, timezone
+
+    def _compute_chill(df, temp_col="airTemperature"):
+        if df.empty or temp_col not in df.columns:
+            return [], 0.0
+        hourly = df[temp_col].resample("1h").mean().dropna()
+        if hourly.empty:
+            return [], 0.0
         temps = hourly.values
         chill_h = np.select(
             [temps <= 7, (temps > 7) & (temps <= 10), (temps > 10) & (temps <= 18), temps > 18],
@@ -76,17 +70,52 @@ async def biology_chill_units(
         )
         daily = pd.Series(chill_h, index=hourly.index).resample("D").sum().clip(lower=0)
         cumulative = daily.cumsum()
+        points = [
+            {"date": ts.strftime("%Y-%m-%d"), "cu": round(float(cumulative.loc[ts]), 1)}
+            for ts in daily.index
+        ]
+        return points, round(float(cumulative.iloc[-1]), 1) if len(cumulative) else 0.0
+
+    try:
+        from src.data.thingsboard_client import ThingsBoardClient
+
+        client = ThingsBoardClient()
+        start = pd.Timestamp(season_start, tz="UTC")
+        end = pd.Timestamp(datetime.now(timezone.utc))
+
+        # Fetch hourly avg temp from Air2 (under panels) and Air1 (open field)
+        df_panels = client.get_timeseries(
+            "Air2", ["airTemperature"], start=start, end=end,
+            interval_ms=3_600_000, agg="AVG", limit=10000,
+        )
+        df_open = client.get_timeseries(
+            "Air1", ["airTemperature"], start=start, end=end,
+            interval_ms=3_600_000, agg="AVG", limit=10000,
+        )
+
+        panels_data, panels_total = _compute_chill(df_panels)
+        open_data, open_total = _compute_chill(df_open)
+
+        # Merge into paired daily data for chart
+        panels_by_date = {p["date"]: p["cu"] for p in panels_data}
+        open_by_date = {p["date"]: p["cu"] for p in open_data}
+        all_dates = sorted(set(list(panels_by_date.keys()) + list(open_by_date.keys())))
+
+        daily = [
+            {
+                "date": d,
+                "under_panels": panels_by_date.get(d, None),
+                "open_field": open_by_date.get(d, None),
+            }
+            for d in all_dates
+        ]
 
         return {
             "season_start": season_start,
-            "total_chill_units": round(float(cumulative.iloc[-1]), 1) if len(cumulative) else 0,
-            "days_counted": len(daily),
-            "daily": [
-                {"date": ts.strftime("%Y-%m-%d"),
-                 "cumulative_cu": round(float(cumulative.loc[ts]), 1),
-                 "daily_cu": round(float(daily.loc[ts]), 1)}
-                for ts in daily.index
-            ],
+            "latest_under_panels": panels_total,
+            "latest_open_field": open_total,
+            "days_counted": len(all_dates),
+            "daily": daily,
         }
     except Exception as exc:
         log.error("Chill units failed: %s", exc)