Change for frontend

app.py

@@ -904,6 +904,7 @@ def calculate_verification_metrics(predictions_df=None, backtest_df=None):
         period_label = "Seneste 7 dages backtest"
 
     result = {
+        "target": "temperature",
         "periodLabel": period_label,
         "rmseDmi": None,
         "rmseMl": None,
@@ -964,6 +965,280 @@ def build_lead_bucket_rows(registry):
     return rows
 
 
+TARGET_LABELS = {
+    "temperature": "Temperatur",
+    "wind_speed": "Vindhastighed",
+    "wind_gust": "Vindstoed",
+    "rain_event": "Regnrisiko",
+    "rain_amount": "Regnmaengde",
+}
+
+LEAD_BUCKET_ORDER = ["1-6", "7-12", "13-24", "25-48"]
+
+
+def build_target_labels():
+    return dict(TARGET_LABELS)
+
+
+def build_explanations():
+    return {
+        "forecast": "Du ser DMI's prognose side om side med vores ML-justering, naar der er en aktiv model.",
+        "performance": "Her kan du sammenligne, hvad DMI sagde, hvad ML sagde, og hvad vejret faktisk endte med at blive.",
+        "sources": "DMI er grundprognosen. ML er vores lokale justering. Hvis en ML-model ikke er aktiv, viser vi DMI direkte.",
+    }
+
+
+def build_target_status(registry):
+    registry_targets = registry.get("targets", {}) if registry else {}
+    target_status = {}
+    for target_name in MODEL_FILES:
+        active_buckets = registry_targets.get(target_name, {}).get("active_buckets") or []
+        ordered_buckets = [bucket for bucket in LEAD_BUCKET_ORDER if bucket in active_buckets]
+        has_active_model = len(ordered_buckets) > 0
+        target_label = TARGET_LABELS.get(target_name, target_name)
+
+        if has_active_model:
+            status_label = "ML aktiv"
+            status_description = (
+                f"Vi viser baade DMI og ML for {target_label.lower()}, og ML bruges som den aktive prognose, naar den findes."
+            )
+        else:
+            status_label = "Vises som DMI-prognose"
+            status_description = (
+                f"Vi viser DMI direkte for {target_label.lower()}, fordi der ikke er en aktiv ML-model for dette signal endnu."
+            )
+
+        target_status[target_name] = {
+            "hasActiveModel": has_active_model,
+            "activeBuckets": ordered_buckets,
+            "statusLabel": status_label,
+            "statusDescription": status_description,
+        }
+
+    return target_status
+
+
+def choose_effective_value(ml_value, dmi_value, has_active_model):
+    if has_active_model and ml_value is not None:
+        return ml_value, "ml"
+    if dmi_value is not None:
+        return dmi_value, "dmi"
+    if ml_value is not None:
+        return ml_value, "ml"
+    return None, "dmi"
+
+
+def build_history_payload(predictions_df=None, backtest_df=None):
+    source_df = None
+
+    if predictions_df is not None and len(predictions_df) > 0:
+        verified = predictions_df[predictions_df["verified"].fillna(False).astype(bool)].copy()
+        if len(verified) > 0:
+            source_df = verified.sort_values("target_timestamp").tail(72).reset_index(drop=True)
+
+    if source_df is None and backtest_df is not None and len(backtest_df) > 0:
+        source_df = backtest_df.sort_values("target_timestamp").tail(72).reset_index(drop=True)
+
+    history = {
+        "temperature": [],
+        "wind": [],
+        "rain": [],
+    }
+
+    if source_df is None or len(source_df) == 0:
+        return history
+
+    for _, row in source_df.iterrows():
+        history["temperature"].append(
+            {
+                "timestamp": to_iso(row.get("target_timestamp")),
+                "dmiTemp": safe_number(row.get("dmi_temperature_2m_pred")),
+                "mlTemp": safe_number(row.get("ml_temp")),
+                "actualTemp": safe_number(row.get("actual_temp")),
+                "verified": True,
+            }
+        )
+        history["wind"].append(
+            {
+                "timestamp": to_iso(row.get("target_timestamp")),
+                "dmiWindSpeed": safe_number(row.get("dmi_windspeed_10m_pred")),
+                "mlWindSpeed": safe_number(row.get("ml_wind_speed")),
+                "actualWindSpeed": safe_number(row.get("actual_wind_speed")),
+                "dmiWindGust": safe_number(row.get("dmi_windgusts_10m_pred")),
+                "mlWindGust": safe_number(row.get("ml_wind_gust")),
+                "actualWindGust": safe_number(row.get("actual_wind_gust")),
+                "verified": True,
+            }
+        )
+
+        dmi_rain_prob = safe_number(row.get("dmi_precipitation_probability_pred"), digits=2, default=0.0) or 0.0
+        ml_rain_prob = round((safe_number(row.get("ml_rain_prob"), digits=4, default=0.0) or 0.0) * 100, 2)
+        actual_rain_amount = safe_number(
+            row.get("actual_rain_amount", row.get("actual_precipitation")),
+            digits=3,
+            default=None,
+        )
+        if actual_rain_amount is None:
+            actual_rain_amount = safe_number(row.get("actual_precipitation"), digits=3, default=None)
+        actual_rain_event = row.get("actual_rain_event")
+        if actual_rain_event is None or pd.isna(actual_rain_event):
+            if actual_rain_amount is None:
+                actual_rain_event = None
+            else:
+                actual_rain_event = 1 if actual_rain_amount > 0.1 else 0
+        else:
+            actual_rain_event = int(actual_rain_event)
+
+        history["rain"].append(
+            {
+                "timestamp": to_iso(row.get("target_timestamp")),
+                "dmiRainProb": dmi_rain_prob,
+                "mlRainProb": ml_rain_prob,
+                "actualRainEvent": actual_rain_event,
+                "dmiRainAmount": safe_number(row.get("dmi_precipitation_pred"), digits=3, default=0.0) or 0.0,
+                "mlRainAmount": safe_number(row.get("ml_rain_amount"), digits=3, default=0.0) or 0.0,
+                "actualRainAmount": actual_rain_amount,
+                "verified": True,
+            }
+        )
+
+    return history
+
+
+def build_forecast_row(row, target_status):
+    dmi_temp = safe_number(row.get("dmi_temperature_2m_pred"))
+    ml_temp = safe_number(row.get("ml_temp"))
+    dmi_wind_speed = safe_number(row.get("dmi_windspeed_10m_pred"))
+    ml_wind_speed = safe_number(row.get("ml_wind_speed"))
+    dmi_wind_gust = safe_number(row.get("dmi_windgusts_10m_pred"))
+    ml_wind_gust = safe_number(row.get("ml_wind_gust"))
+    dmi_rain_prob = safe_number(row.get("dmi_precipitation_probability_pred"), digits=2, default=0.0) or 0.0
+    ml_rain_prob = round((safe_number(row.get("ml_rain_prob"), digits=4, default=0.0) or 0.0) * 100, 2)
+    dmi_rain_amount = safe_number(row.get("dmi_precipitation_pred"), digits=3, default=0.0) or 0.0
+    ml_rain_amount = safe_number(row.get("ml_rain_amount"), digits=3, default=0.0) or 0.0
+
+    effective_temp, effective_temp_source = choose_effective_value(
+        ml_temp,
+        dmi_temp,
+        target_status["temperature"]["hasActiveModel"],
+    )
+    effective_wind_speed, effective_wind_speed_source = choose_effective_value(
+        ml_wind_speed,
+        dmi_wind_speed,
+        target_status["wind_speed"]["hasActiveModel"],
+    )
+    effective_wind_gust, effective_wind_gust_source = choose_effective_value(
+        ml_wind_gust,
+        dmi_wind_gust,
+        target_status["wind_gust"]["hasActiveModel"],
+    )
+    effective_rain_prob, effective_rain_prob_source = choose_effective_value(
+        ml_rain_prob,
+        dmi_rain_prob,
+        target_status["rain_event"]["hasActiveModel"],
+    )
+    effective_rain_amount, effective_rain_amount_source = choose_effective_value(
+        ml_rain_amount,
+        dmi_rain_amount,
+        target_status["rain_amount"]["hasActiveModel"],
+    )
+
+    return {
+        "timestamp": to_iso(row.get("target_timestamp")),
+        "hour": int(row["target_timestamp"].hour),
+        "leadTimeHours": int(row.get("lead_time_hours") or 0),
+        "dmiTemp": dmi_temp,
+        "mlTemp": ml_temp,
+        "effectiveTemp": effective_temp,
+        "effectiveTempSource": effective_temp_source,
+        "apparentTemp": safe_number(row.get("dmi_apparent_temperature_pred")),
+        "dmiWindSpeed": dmi_wind_speed,
+        "mlWindSpeed": ml_wind_speed,
+        "effectiveWindSpeed": effective_wind_speed,
+        "effectiveWindSpeedSource": effective_wind_speed_source,
+        "dmiWindGust": dmi_wind_gust,
+        "mlWindGust": ml_wind_gust,
+        "effectiveWindGust": effective_wind_gust,
+        "effectiveWindGustSource": effective_wind_gust_source,
+        "windDirection": safe_number(row.get("dmi_winddirection_10m_pred")),
+        "dmiRainProb": dmi_rain_prob,
+        "mlRainProb": ml_rain_prob,
+        "effectiveRainProb": effective_rain_prob or 0.0,
+        "effectiveRainProbSource": effective_rain_prob_source,
+        "dmiRainAmount": dmi_rain_amount,
+        "mlRainAmount": ml_rain_amount,
+        "effectiveRainAmount": effective_rain_amount or 0.0,
+        "effectiveRainAmountSource": effective_rain_amount_source,
+        "weatherCode": int(row.get("dmi_weather_code_pred")) if safe_number(row.get("dmi_weather_code_pred"), digits=0) is not None else None,
+        "cloudCover": safe_number(row.get("dmi_cloud_cover_pred")),
+        "humidity": safe_number(row.get("dmi_relative_humidity_2m_pred")),
+        "pressure": safe_number(row.get("dmi_pressure_msl_pred")),
+    }
+
+
+def build_current_payload(current_row):
+    if not current_row:
+        return {
+            "timestamp": to_iso(now_cph()),
+            "temp": None,
+            "dmiTemp": None,
+            "mlTemp": None,
+            "tempSource": "dmi",
+            "apparentTemp": None,
+            "windSpeed": None,
+            "dmiWindSpeed": None,
+            "mlWindSpeed": None,
+            "windSpeedSource": "dmi",
+            "windGust": None,
+            "dmiWindGust": None,
+            "mlWindGust": None,
+            "windGustSource": "dmi",
+            "windDirection": None,
+            "rainProb": 0.0,
+            "dmiRainProb": 0.0,
+            "mlRainProb": 0.0,
+            "rainProbSource": "dmi",
+            "rainAmount": 0.0,
+            "dmiRainAmount": 0.0,
+            "mlRainAmount": 0.0,
+            "rainAmountSource": "dmi",
+            "humidity": None,
+            "pressure": None,
+            "cloudCover": None,
+            "weatherCode": None,
+        }
+
+    return {
+        "timestamp": current_row["timestamp"],
+        "temp": current_row["effectiveTemp"],
+        "dmiTemp": current_row["dmiTemp"],
+        "mlTemp": current_row["mlTemp"],
+        "tempSource": current_row["effectiveTempSource"],
+        "apparentTemp": current_row["apparentTemp"],
+        "windSpeed": current_row["effectiveWindSpeed"],
+        "dmiWindSpeed": current_row["dmiWindSpeed"],
+        "mlWindSpeed": current_row["mlWindSpeed"],
+        "windSpeedSource": current_row["effectiveWindSpeedSource"],
+        "windGust": current_row["effectiveWindGust"],
+        "dmiWindGust": current_row["dmiWindGust"],
+        "mlWindGust": current_row["mlWindGust"],
+        "windGustSource": current_row["effectiveWindGustSource"],
+        "windDirection": current_row["windDirection"],
+        "rainProb": current_row["effectiveRainProb"],
+        "dmiRainProb": current_row["dmiRainProb"],
+        "mlRainProb": current_row["mlRainProb"],
+        "rainProbSource": current_row["effectiveRainProbSource"],
+        "rainAmount": current_row["effectiveRainAmount"],
+        "dmiRainAmount": current_row["dmiRainAmount"],
+        "mlRainAmount": current_row["mlRainAmount"],
+        "rainAmountSource": current_row["effectiveRainAmountSource"],
+        "humidity": current_row["humidity"],
+        "pressure": current_row["pressure"],
+        "cloudCover": current_row["cloudCover"],
+        "weatherCode": current_row["weatherCode"],
+    }
+
+
 def build_alert_rows(forecast_rows):
     """Derive lightweight alert messages from the live forecast."""
     alerts = []
@@ -977,10 +1252,28 @@ def build_alert_rows(forecast_rows):
             }
         ]
 
-    max_wind_speed = max((row.get("mlWindSpeed") or 0.0) for row in forecast_rows)
-    max_wind_gust = max((row.get("mlWindGust") or 0.0) for row in forecast_rows)
-    max_rain_prob = max((row.get("mlRainProb") or 0.0) for row in forecast_rows)
-    max_rain_amount = max((row.get("mlRainAmount") or 0.0) for row in forecast_rows)
+    max_wind_row = max(
+        forecast_rows,
+        key=lambda row: max(row.get("effectiveWindSpeed") or 0.0, row.get("effectiveWindGust") or 0.0),
+    )
+    max_rain_row = max(
+        forecast_rows,
+        key=lambda row: max(row.get("effectiveRainProb") or 0.0, row.get("effectiveRainAmount") or 0.0),
+    )
+    max_wind_speed = max_wind_row.get("effectiveWindSpeed") or 0.0
+    max_wind_gust = max_wind_row.get("effectiveWindGust") or 0.0
+    max_rain_prob = max_rain_row.get("effectiveRainProb") or 0.0
+    max_rain_amount = max_rain_row.get("effectiveRainAmount") or 0.0
+    wind_source = (
+        "ML"
+        if max_wind_row.get("effectiveWindSpeedSource") == "ml" or max_wind_row.get("effectiveWindGustSource") == "ml"
+        else "DMI"
+    )
+    rain_source = (
+        "ML"
+        if max_rain_row.get("effectiveRainProbSource") == "ml" or max_rain_row.get("effectiveRainAmountSource") == "ml"
+        else "DMI"
+    )
 
     if max_wind_speed >= 15 or max_wind_gust >= 20:
         alerts.append(
@@ -988,7 +1281,7 @@ def build_alert_rows(forecast_rows):
                 "type": "wind",
                 "severity": "warning",
                 "title": "Kraftig vind",
-                "message": f"ML forventer op til {max_wind_speed:.1f} m/s og vindstød op til {max_wind_gust:.1f} m/s i forecast-vinduet.",
+                "message": f"{wind_source} forventer op til {max_wind_speed:.1f} m/s og vindstoed op til {max_wind_gust:.1f} m/s i forecast-vinduet.",
             }
         )
 
@@ -997,8 +1290,8 @@ def build_alert_rows(forecast_rows):
             {
                 "type": "rain",
                 "severity": "warning",
-                "title": "Våd periode",
-                "message": f"ML forventer op til {max_rain_prob:.0f}% regnrisiko og {max_rain_amount:.1f} mm/time i forecast-vinduet.",
+                "title": "Vaad periode",
+                "message": f"{rain_source} forventer op til {max_rain_prob:.0f}% regnrisiko og {max_rain_amount:.1f} mm/time i forecast-vinduet.",
             }
         )
 
@@ -1021,9 +1314,11 @@ def build_frontend_snapshot():
     training_df, _ = load_existing_training_matrix()
     registry = load_json_from_dataset("model_registry.json", DATASET_NAME) or {}
     model_meta = load_json_from_dataset("model_meta.json", DATASET_NAME) or {}
+    target_status = build_target_status(registry)
 
     backtest_df = build_recent_backtest(training_df)
     verification = calculate_verification_metrics(predictions_df=predictions_df, backtest_df=backtest_df)
+    history = build_history_payload(predictions_df=predictions_df, backtest_df=backtest_df)
 
     future_df = None
     if predictions_df is not None and len(predictions_df) > 0:
@@ -1033,45 +1328,10 @@ def build_frontend_snapshot():
     forecast_rows = []
     if future_df is not None and len(future_df) > 0:
         for _, row in future_df.iterrows():
-            forecast_rows.append(
-                {
-                    "timestamp": to_iso(row.get("target_timestamp")),
-                    "hour": int(row["target_timestamp"].hour),
-                    "leadTimeHours": int(row.get("lead_time_hours") or 0),
-                    "dmiTemp": safe_number(row.get("dmi_temperature_2m_pred")),
-                    "mlTemp": safe_number(row.get("ml_temp")),
-                    "apparentTemp": safe_number(row.get("dmi_apparent_temperature_pred")),
-                    "dmiWindSpeed": safe_number(row.get("dmi_windspeed_10m_pred")),
-                    "mlWindSpeed": safe_number(row.get("ml_wind_speed")),
-                    "dmiWindGust": safe_number(row.get("dmi_windgusts_10m_pred")),
-                    "mlWindGust": safe_number(row.get("ml_wind_gust")),
-                    "windDirection": safe_number(row.get("dmi_winddirection_10m_pred")),
-                    "dmiRainProb": safe_number(row.get("dmi_precipitation_probability_pred"), digits=2, default=0.0) or 0.0,
-                    "mlRainProb": round((safe_number(row.get("ml_rain_prob"), digits=4, default=0.0) or 0.0) * 100, 2),
-                    "dmiRainAmount": safe_number(row.get("dmi_precipitation_pred"), digits=3, default=0.0) or 0.0,
-                    "mlRainAmount": safe_number(row.get("ml_rain_amount"), digits=3, default=0.0) or 0.0,
-                    "weatherCode": int(row.get("dmi_weather_code_pred")) if safe_number(row.get("dmi_weather_code_pred"), digits=0) is not None else None,
-                    "cloudCover": safe_number(row.get("dmi_cloud_cover_pred")),
-                    "humidity": safe_number(row.get("dmi_relative_humidity_2m_pred")),
-                    "pressure": safe_number(row.get("dmi_pressure_msl_pred")),
-                }
-            )
+            forecast_rows.append(build_forecast_row(row, target_status))
 
     current_row = forecast_rows[0] if forecast_rows else None
-    current = {
-        "timestamp": current_row["timestamp"] if current_row else to_iso(now_cph()),
-        "temp": current_row["mlTemp"] if current_row else None,
-        "apparentTemp": current_row["apparentTemp"] if current_row else None,
-        "windSpeed": current_row["mlWindSpeed"] if current_row else None,
-        "windGust": current_row["mlWindGust"] if current_row else None,
-        "windDirection": current_row["windDirection"] if current_row else None,
-        "rainProb": current_row["mlRainProb"] if current_row else 0.0,
-        "rainAmount": current_row["mlRainAmount"] if current_row else 0.0,
-        "humidity": current_row["humidity"] if current_row else None,
-        "pressure": current_row["pressure"] if current_row else None,
-        "cloudCover": current_row["cloudCover"] if current_row else None,
-        "weatherCode": current_row["weatherCode"] if current_row else None,
-    }
+    current = build_current_payload(current_row)
 
     feature_importance = []
     registry_revision = registry.get("generated_at")
@@ -1092,8 +1352,12 @@ def build_frontend_snapshot():
             "timezone": "Europe/Copenhagen",
         },
         "generatedAt": to_iso(now_cph()),
+        "targetLabels": build_target_labels(),
+        "explanations": build_explanations(),
+        "targetStatus": target_status,
         "current": current,
         "forecast": forecast_rows,
+        "history": history,
         "verification": verification,
         "leadBuckets": build_lead_bucket_rows(registry),
         "featureImportance": feature_importance[:24],