modified: app.py

modified:   static/css/style.css
	modified:   templates/weather.html

app.py

@@ -172,6 +172,140 @@ def _round_temp(k):
         return None
     return round(float(k), 1)
 
+def _clamp(value, min_value, max_value):
+    return max(min_value, min(max_value, value))
+
+def uv_risk_info(uv_index):
+    if uv_index is None:
+        return "–", "na"
+    uv = float(uv_index)
+    if uv < 3:
+        return "niedrig", "low"
+    if uv < 6:
+        return "moderat", "moderate"
+    if uv < 8:
+        return "hoch", "high"
+    if uv < 11:
+        return "sehr hoch", "very-high"
+    return "extrem", "extreme"
+
+def hour_confidence_score(temp_c, precip_mm, rain_prob, wind_kmh, gust_kmh, cloud_pct):
+    score = 100
+    if temp_c is None:
+        score -= 18
+    if precip_mm is not None:
+        score -= _clamp(precip_mm * 20, 0, 40)
+    if rain_prob is not None:
+        score -= _clamp(rain_prob * 0.35, 0, 30)
+    if wind_kmh is not None:
+        score -= _clamp((wind_kmh - 25) * 0.6, 0, 18)
+    if gust_kmh is not None:
+        score -= _clamp((gust_kmh - 45) * 0.45, 0, 16)
+    if cloud_pct is not None:
+        score -= _clamp((cloud_pct - 85) * 0.4, 0, 8)
+    score = int(round(_clamp(score, 5, 99)))
+    if score >= 80:
+        return score, "hoch"
+    if score >= 60:
+        return score, "mittel"
+    return score, "niedrig"
+
+def activity_score(temp_c, precip_mm, rain_prob, wind_kmh, gust_kmh, uv_index):
+    score = 100.0
+    if temp_c is not None:
+        score -= abs(temp_c - 20) * 3.5
+    if precip_mm is not None:
+        score -= _clamp(precip_mm * 35, 0, 45)
+    if rain_prob is not None:
+        score -= _clamp(rain_prob * 0.45, 0, 35)
+    if wind_kmh is not None:
+        score -= _clamp((wind_kmh - 18) * 0.7, 0, 16)
+    if gust_kmh is not None:
+        score -= _clamp((gust_kmh - 35) * 0.55, 0, 12)
+    if uv_index is not None and uv_index > 6:
+        score -= _clamp((uv_index - 6) * 6, 0, 16)
+    return int(round(_clamp(score, 0, 100)))
+
+def best_activity_window(forecast, horizon_hours=24, window_size=2):
+    hours = forecast[:horizon_hours]
+    if len(hours) < window_size:
+        return None
+    best = None
+    for i in range(0, len(hours) - window_size + 1):
+        segment = hours[i:i + window_size]
+        scores = [h.get("activity_score") for h in segment if h.get("activity_score") is not None]
+        if not scores:
+            continue
+        avg_score = round(sum(scores) / len(scores))
+        if best is None or avg_score > best["score"]:
+            best = {
+                "start": segment[0]["datetime"],
+                "end": segment[-1]["datetime"],
+                "score": int(avg_score),
+            }
+    return best
+
+def pressure_trend_info(forecast, step_hours=6):
+    if len(forecast) <= step_hours:
+        return None, None
+    p0 = forecast[0].get("pressure_hpa")
+    p1 = forecast[step_hours].get("pressure_hpa")
+    if p0 is None or p1 is None:
+        return None, None
+    delta = round(p1 - p0, 1)
+    if delta >= 1.5:
+        return delta, "steigend"
+    if delta <= -1.5:
+        return delta, "fallend"
+    return delta, "stabil"
+
+def temp_trend_info(forecast, step_hours=6):
+    if len(forecast) <= step_hours:
+        return None, None
+    t0 = forecast[0].get("temp_c")
+    t1 = forecast[step_hours].get("temp_c")
+    if t0 is None or t1 is None:
+        return None, None
+    delta = round(t1 - t0, 1)
+    if delta >= 1.0:
+        return delta, "waermer"
+    if delta <= -1.0:
+        return delta, "kaelter"
+    return delta, "konstant"
+
+def _parse_warning_datetime(value):
+    if value in (None, ""):
+        return None
+    try:
+        if isinstance(value, (int, float)):
+            ts = pd.Timestamp(value, unit="ms", tz="UTC")
+        else:
+            v = str(value).strip()
+            if v.isdigit():
+                ts = pd.Timestamp(int(v), unit="ms", tz="UTC")
+            else:
+                ts = pd.Timestamp(v)
+                if ts.tzinfo is None:
+                    ts = ts.tz_localize("UTC")
+        return ts.tz_convert(_get_berlin()).tz_localize(None).to_pydatetime()
+    except Exception:
+        return None
+
+def pick_daily_icon(hours):
+    if not hours:
+        return "☀️"
+    if any((h.get("temp_c") is not None and h["temp_c"] <= 0 and ((h.get("precip_mm") or 0) > 0.1 or (h.get("rain_prob") or 0) >= 50)) for h in hours):
+        return "❄️"
+    if any(((h.get("precip_mm") or 0) >= 0.6 or (h.get("rain_prob") or 0) >= 70) for h in hours):
+        return "🌧️"
+    clouds = [h.get("cloud_pct") for h in hours if h.get("cloud_pct") is not None]
+    avg_cloud = sum(clouds) / len(clouds) if clouds else 0
+    if avg_cloud > 80:
+        return "☁️"
+    if avg_cloud > 40:
+        return "⛅"
+    return "☀️"
+
 def feels_like(temp_c, wind_kmh, cloud_pct):
     if temp_c is None:
         return None
@@ -319,7 +453,10 @@ def get_mosmix_forecast(lat, lon, hours=72):
             wind_dir = float(wd) if not _isnan(wd) else None
             uv_raw   = p.get("uv_index")
             uv       = round(float(uv_raw),1) if not _isnan(uv_raw) else None
+            uv_label, uv_level = uv_risk_info(uv)
             feels    = feels_like(temp_c, wind_kmh, clouds)
+            confidence_score, confidence_label = hour_confidence_score(temp_c, precip, rain_prob, wind_kmh, gust_kmh, clouds)
+            a_score = activity_score(temp_c, precip, rain_prob, wind_kmh, gust_kmh, uv)
             dt_local = pd.Timestamp(date_val).tz_convert(berlin).tz_localize(None)
             forecast.append({
                 "datetime":     dt_local,
@@ -334,6 +471,11 @@ def get_mosmix_forecast(lat, lon, hours=72):
                 "sun_min":      sun_min,
                 "wind_dir":     wind_dir,
                 "uv_index":     uv,
+                "uv_label":     uv_label,
+                "uv_level":     uv_level,
+                "confidence":   confidence_score,
+                "confidence_label": confidence_label,
+                "activity_score": a_score,
                 "icon":         weather_icon(clouds, precip, rain_prob, temp_c),
             })
         result_data = (forecast, station_info)
@@ -343,7 +485,7 @@ def get_mosmix_forecast(lat, lon, hours=72):
         app.logger.exception("MOSMIX forecast loading failed")
         return [], {}
 
-def filter_unrealistic_warnings(warnings, forecast):
+def filter_unrealistic_warnings(warnings, forecast, now_local=None):
     """
     Filter out warnings that contradict the actual forecast.
     E.g., frost warning when min temp is > 0°C in next 48 hours.
@@ -356,29 +498,45 @@ def filter_unrealistic_warnings(warnings, forecast):
     rain_keywords = {"regen", "starkregen", "dauerregen"}
     
     try:
-        temps_48h = [h.get("temp_c") for h in forecast[:48] if h.get("temp_c") is not None]
-        precip_48h = [h.get("precip_mm") for h in forecast[:48] if h.get("precip_mm") is not None]
-        
-        min_temp_48h = min(temps_48h) if temps_48h else None
-        max_precip_48h = max(precip_48h) if precip_48h else 0
-        
         for w in warnings:
             warn_type = _normalize_text(w.get("type", ""))
             headline = _normalize_text(w.get("headline", ""))
+            onset_dt = _parse_warning_datetime(w.get("onset"))
+            expires_dt = _parse_warning_datetime(w.get("expires"))
+
+            if now_local and expires_dt and expires_dt < now_local:
+                continue
+
+            if onset_dt and expires_dt:
+                relevant_hours = [
+                    h for h in forecast[:48]
+                    if h.get("datetime") is not None and onset_dt <= h["datetime"] <= expires_dt
+                ]
+            else:
+                relevant_hours = forecast[:48]
+
+            temps = [h.get("temp_c") for h in relevant_hours if h.get("temp_c") is not None]
+            precip = [h.get("precip_mm") for h in relevant_hours if h.get("precip_mm") is not None]
+            rain_prob = [h.get("rain_prob") for h in relevant_hours if h.get("rain_prob") is not None]
+            min_temp = min(temps) if temps else None
+            max_precip = max(precip) if precip else 0
+            max_rain_prob = max(rain_prob) if rain_prob else 0
             
             skip = False
             
-            if min_temp_48h is not None and min_temp_48h > 2:
+            if min_temp is not None and min_temp > 3:
                 if any(kw in warn_type or kw in headline for kw in frost_keywords):
-                    app.logger.info("Filtered frost warning: min_temp %.1f°C", min_temp_48h)
+                    app.logger.info("Filtered frost warning: min_temp %.1f°C", min_temp)
                     skip = True
             
-            if max_precip_48h < 0.1:
+            if max_precip < 0.2 and max_rain_prob < 35:
                 if any(kw in warn_type or kw in headline for kw in rain_keywords):
-                    app.logger.info("Filtered rain warning: max_precip %.1f mm", max_precip_48h)
+                    app.logger.info("Filtered rain warning: max_precip %.1f mm", max_precip)
                     skip = True
             
             if not skip:
+                w["onset_dt"] = onset_dt
+                w["expires_dt"] = expires_dt
                 filtered.append(w)
     except Exception:
         app.logger.exception("Error filtering unrealistic warnings")
@@ -442,13 +600,17 @@ def wetter():
     forecast = forecast[current_idx:]
     sunrise, sunset, dawn, dusk = get_sun_times(lat, lon)
     warnings = get_dwd_warnings(lat, lon, state_hint=state_hint)
-    warnings = filter_unrealistic_warnings(warnings, forecast)
+    warnings = filter_unrealistic_warnings(warnings, forecast, now_local=now_local_dt.replace(tzinfo=None))
+    pressure_delta, pressure_trend = pressure_trend_info(forecast)
+    temp_delta_6h, temp_trend_6h = temp_trend_info(forecast)
+    best_window = best_activity_window(forecast, horizon_hours=24, window_size=2)
     daily = {}
     for h in forecast:
         dt  = h["datetime"]
         day = dt.date() if hasattr(dt,"date") else str(dt)[:10]
         if day not in daily:
-            daily[day] = {"temps":[], "precip":0.0, "cloud":[], "wind":[], "icons":[], "rain_prob":[], "uv":[]}
+            daily[day] = {"temps":[], "precip":0.0, "cloud":[], "wind":[], "icons":[], "rain_prob":[], "uv":[], "hours":[]}
+        daily[day]["hours"].append(h)
         if h["temp_c"] is not None: daily[day]["temps"].append(h["temp_c"])
         daily[day]["precip"] += h.get("precip_mm") or 0
         if h["cloud_pct"] is not None: daily[day]["cloud"].append(h["cloud_pct"])
@@ -467,14 +629,15 @@ def wetter():
             "cloud":     round(sum(d["cloud"])/len(d["cloud"])) if d["cloud"] else None,
             "wind_max":  max(d["wind"]) if d["wind"] else None,
             "uv_max":    max(d["uv"]) if d["uv"] else None,
-            "icon":      max(set(d["icons"]), key=d["icons"].count),
+            "icon":      pick_daily_icon(d["hours"]),
         })
-    chart_labels, chart_temps, chart_precip, chart_rain_prob = [], [], [], []
+    chart_labels, chart_temps, chart_feels, chart_precip, chart_rain_prob = [], [], [], [], []
     for h in forecast[:48]:
         dt = h["datetime"]
         label = dt.strftime("%d.%m %H:%M") if hasattr(dt,"strftime") else str(dt)[5:16]
         chart_labels.append(label)
         chart_temps.append(h["temp_c"])
+        chart_feels.append(h.get("feels_like"))
         chart_precip.append(h.get("precip_mm") or 0)
         chart_rain_prob.append(h.get("rain_prob") or 0)
     return render_template(
@@ -482,12 +645,16 @@ def wetter():
         ort=ort, display_name=display_name, lat=lat, lon=lon,
         station_name=station_name, station_id=station_id, station_dist=station_dist,
         current=current, now_local=now_local,
+        pressure_delta=pressure_delta, pressure_trend=pressure_trend,
+        temp_delta_6h=temp_delta_6h, temp_trend_6h=temp_trend_6h,
+        best_window=best_window,
         sunrise=sunrise, sunset=sunset,
         warnings=warnings,
         forecast=forecast[:48], daily=daily_summary,
-        chart_labels=chart_labels, chart_temps=chart_temps,
+        chart_labels=chart_labels, chart_temps=chart_temps, chart_feels=chart_feels,
         chart_precip=chart_precip, chart_rain_prob=chart_rain_prob,
         wind_dir_name=wind_direction_name,
+        uv_risk_info=uv_risk_info,
     )
 
 @app.route("/api/suggest")