template:
  - trigger:
      - platform: time_pattern
        minutes: /15
    action:
      - service: weather.get_forecasts
        data:
          type: hourly
        target:
          entity_id: weather.forecast_home
        response_variable: hourly
    sensor:
      - name: weather.forecast_hourly
        unique_id: weather.forecast_hourly
        state: "{{ now().isoformat() }}"
        attributes:
          forecast:  "{{ hourly['weather.forecast_home'].forecast }}"

WITH vars AS (
    SELECT 
        'weather.forecast_home' as sensor_clouds,   -- Weather Entity direkt: cloud_coverage aus state_attributes
        'weather.forecast_home' as sensor_uv,   -- Weather Entity direkt:  uv_index aus state_attributes
        'sensor.pv_panels_energy' as sensor_pv,
        'sensor.weather_forecast_hourly' as sensor_forecast,
        -- Berechnet den Versatz zwischen Lokalzeit und UTC (z.B. '+3600 seconds')
        -- Wird genutzt, um den Datumswechsel (00:00 Uhr) lokal zu triggern
        (strftime('%s', 'now', 'localtime') - strftime('%s', 'now')) || ' seconds' as offset
),

ids AS (
    /* Holt alle benötigten internen IDs für Statistiken und States aus der HA-Datenbank */
    SELECT 
        (SELECT id FROM statistics_meta WHERE statistic_id = (SELECT sensor_clouds FROM vars)) as w_id_stats,
        (SELECT metadata_id FROM states_meta WHERE entity_id = (SELECT sensor_clouds FROM vars)) as w_id_states,
        (SELECT id FROM statistics_meta WHERE statistic_id = (SELECT sensor_uv FROM vars)) as uv_id_stats,
        (SELECT metadata_id FROM states_meta WHERE entity_id = (SELECT sensor_uv FROM vars)) as uv_id_states,
        (SELECT id FROM statistics_meta WHERE statistic_id = (SELECT sensor_pv FROM vars) LIMIT 1) as p_id,
        (SELECT metadata_id FROM states_meta WHERE entity_id = (SELECT sensor_pv FROM vars) LIMIT 1) as p_id_states,
        (SELECT metadata_id FROM states_meta WHERE entity_id = (SELECT sensor_forecast FROM vars) LIMIT 1) as f_id,
        (SELECT metadata_id FROM states_meta WHERE entity_id = 'sun.sun') as sun_id
),

pv_activity AS (
    /* Sonnenaufgang = erster 'above_horizon'-Eintrag gestern (UTC-Epoche, direkt korrekt)       */
    /* Sonnenuntergang = erster 'below_horizon'-Eintrag NACH dem Sonnenaufgang gestern           */
    /* sun_start/sun_end = UTC HH:MM  → verwendet für BETWEEN mit UTC-Forecast-Datetimes (+00:00) */
    /* sun_start_local/sun_end_local = lokal HH:MM → nur für Phasenerkennung (vor/nach Auf/Unt)  */
    SELECT
        COALESCE((
            SELECT strftime('%H:%M', last_updated_ts, 'unixepoch')
            FROM states
            WHERE metadata_id = (SELECT sun_id FROM ids)
              AND date(last_updated_ts, 'unixepoch', (SELECT offset FROM vars)) = date('now', (SELECT offset FROM vars), '-1 day')
              AND state = 'above_horizon'
            ORDER BY last_updated_ts ASC LIMIT 1
        ), '05:30') as sun_start,
        COALESCE((
            SELECT strftime('%H:%M', last_updated_ts, 'unixepoch')
            FROM states
            WHERE metadata_id = (SELECT sun_id FROM ids)
              AND state = 'below_horizon'
              AND last_updated_ts > (
                  SELECT last_updated_ts FROM states
                  WHERE metadata_id = (SELECT sun_id FROM ids)
                    AND date(last_updated_ts, 'unixepoch', (SELECT offset FROM vars)) = date('now', (SELECT offset FROM vars), '-1 day')
                    AND state = 'above_horizon'
                  ORDER BY last_updated_ts ASC LIMIT 1
              )
            ORDER BY last_updated_ts ASC LIMIT 1
        ), '17:30') as sun_end,
        COALESCE((
            SELECT strftime('%H:%M', last_updated_ts, 'unixepoch', (SELECT offset FROM vars))
            FROM states
            WHERE metadata_id = (SELECT sun_id FROM ids)
              AND date(last_updated_ts, 'unixepoch', (SELECT offset FROM vars)) = date('now', (SELECT offset FROM vars), '-1 day')
              AND state = 'above_horizon'
            ORDER BY last_updated_ts ASC LIMIT 1
        ), '06:30') as sun_start_local,
        COALESCE((
            SELECT strftime('%H:%M', last_updated_ts, 'unixepoch', (SELECT offset FROM vars))
            FROM states
            WHERE metadata_id = (SELECT sun_id FROM ids)
              AND state = 'below_horizon'
              AND last_updated_ts > (
                  SELECT last_updated_ts FROM states
                  WHERE metadata_id = (SELECT sun_id FROM ids)
                    AND date(last_updated_ts, 'unixepoch', (SELECT offset FROM vars)) = date('now', (SELECT offset FROM vars), '-1 day')
                    AND state = 'above_horizon'
                  ORDER BY last_updated_ts ASC LIMIT 1
              )
            ORDER BY last_updated_ts ASC LIMIT 1
        ), '18:30') as sun_end_local
    FROM ids
),

forecast_val AS (
    /* Berechnet die durchschnittliche Bewölkung + UV-Index für den verbleibenden Teil des aktuellen Tages */
    SELECT COALESCE(
        (SELECT AVG(CAST(json_extract(f.value, '$.cloud_coverage') AS FLOAT)) 
         FROM states s 
         JOIN state_attributes a ON s.attributes_id = a.attributes_id, 
         json_each(a.shared_attrs, '$.forecast') f 
         WHERE s.metadata_id = (SELECT f_id FROM ids) 
           AND s.last_updated_ts = (SELECT MAX(last_updated_ts) FROM states WHERE metadata_id = (SELECT f_id FROM ids)) 
           -- Match forecast date against local "today" (via UTC offset)
           AND substr(json_extract(f.value, '$.datetime'), 1, 10) = date('now', (SELECT offset FROM vars))
           AND substr(json_extract(f.value, '$.datetime'), 12, 5) 
               BETWEEN CASE
                         -- Forecast slots are UTC: compare against UTC sun_start/sun_end.
                         -- Only the window START shifts: during local day use current UTC time
                         -- (remaining today); before/after local daylight use full-day window
                         -- (midnight use-case: forecast for the whole coming day).
                         WHEN strftime('%H:%M', 'now', (SELECT offset FROM vars))
                              BETWEEN (SELECT sun_start_local FROM pv_activity)
                                  AND (SELECT sun_end_local   FROM pv_activity)
                             THEN strftime('%H:%M', 'now')
                         ELSE (SELECT sun_start FROM pv_activity)
                       END
               AND (SELECT sun_end FROM pv_activity)
        ), 50.0) as f_avg,
        COALESCE(
        (SELECT AVG(CAST(json_extract(f.value, '$.uv_index') AS FLOAT)) 
         FROM states s 
         JOIN state_attributes a ON s.attributes_id = a.attributes_id, 
         json_each(a.shared_attrs, '$.forecast') f 
         WHERE s.metadata_id = (SELECT f_id FROM ids) 
           AND s.last_updated_ts = (SELECT MAX(last_updated_ts) FROM states WHERE metadata_id = (SELECT f_id FROM ids)) 
           AND substr(json_extract(f.value, '$.datetime'), 1, 10) = date('now', (SELECT offset FROM vars))
           AND substr(json_extract(f.value, '$.datetime'), 12, 5) 
               BETWEEN CASE
                         WHEN strftime('%H:%M', 'now', (SELECT offset FROM vars))
                              BETWEEN (SELECT sun_start_local FROM pv_activity)
                                  AND (SELECT sun_end_local   FROM pv_activity)
                             THEN strftime('%H:%M', 'now')
                         ELSE (SELECT sun_start FROM pv_activity)
                       END
               AND (SELECT sun_end FROM pv_activity)
        ), 0.0) as uv_avg
),

forecast_next_day AS (
    /* Berechnet die durchschnittliche Bewölkung + UV-Index für den gesamten nächsten Tag */
    SELECT COALESCE((
        SELECT AVG(CAST(json_extract(f.value, '$.cloud_coverage') AS FLOAT)) 
        FROM states s 
        JOIN state_attributes a ON s.attributes_id = a.attributes_id, 
        json_each(a.shared_attrs, '$.forecast') f 
        WHERE s.metadata_id = (SELECT f_id FROM ids) 
          AND s.last_updated_ts = (SELECT MAX(last_updated_ts) FROM states WHERE metadata_id = (SELECT f_id FROM ids)) 
          AND substr(json_extract(f.value, '$.datetime'), 1, 10) = date('now', (SELECT offset FROM vars), '+1 day') 
          AND substr(json_extract(f.value, '$.datetime'), 12, 5) BETWEEN (SELECT sun_start FROM pv_activity) AND (SELECT sun_end FROM pv_activity)
    ), 50.0) as f_avg_tomorrow,
    COALESCE((
        SELECT AVG(CAST(json_extract(f.value, '$.uv_index') AS FLOAT)) 
        FROM states s 
        JOIN state_attributes a ON s.attributes_id = a.attributes_id, 
        json_each(a.shared_attrs, '$.forecast') f 
        WHERE s.metadata_id = (SELECT f_id FROM ids) 
          AND s.last_updated_ts = (SELECT MAX(last_updated_ts) FROM states WHERE metadata_id = (SELECT f_id FROM ids)) 
          AND substr(json_extract(f.value, '$.datetime'), 1, 10) = date('now', (SELECT offset FROM vars), '+1 day') 
          AND substr(json_extract(f.value, '$.datetime'), 12, 5) BETWEEN (SELECT sun_start FROM pv_activity) AND (SELECT sun_end FROM pv_activity)
    ), 0.0) as uv_avg_tomorrow
),

cloud_history AS (
        /* Kombiniert Langzeit-Statistiken und kurzfristige States der Bewölkung für den historischen Vergleich */
        SELECT start_ts as ts,
                     CAST(COALESCE(mean, state) AS FLOAT) as val
        FROM statistics 
        WHERE metadata_id = (SELECT w_id_stats FROM ids) 
            AND start_ts > strftime('%s', 'now', '-60 days')
        UNION ALL
        SELECT s.last_updated_ts as ts, 
            CASE WHEN (SELECT sensor_clouds FROM vars) LIKE 'weather.%' 
                     THEN CAST(json_extract(a.shared_attrs, '$.cloud_coverage') AS FLOAT) 
                     ELSE CAST(s.state AS FLOAT) 
            END as val
        FROM states s 
        LEFT JOIN state_attributes a ON s.attributes_id = a.attributes_id 
        WHERE s.metadata_id = (SELECT w_id_states FROM ids) 
            AND ((SELECT sensor_clouds FROM vars) LIKE 'weather.%' OR NOT EXISTS (SELECT 1 FROM statistics WHERE metadata_id = (SELECT w_id_stats FROM ids)))
            AND s.last_updated_ts > strftime('%s', 'now', '-10 days') 
            AND s.state NOT IN ('unknown', 'unavailable', '')
),

uv_history AS (
        /* Kombiniert Langzeit-Statistiken und kurzfristige States des UV-Index für den historischen Vergleich */
        SELECT start_ts as ts,
                     CAST(COALESCE(mean, state) AS FLOAT) as uv_val
        FROM statistics 
        WHERE metadata_id = (SELECT uv_id_stats FROM ids) 
            AND start_ts > strftime('%s', 'now', '-60 days')
        UNION ALL
        SELECT s.last_updated_ts as ts, 
            CASE WHEN (SELECT sensor_uv FROM vars) LIKE 'weather.%' 
                     THEN CAST(json_extract(a.shared_attrs, '$.uv_index') AS FLOAT) 
                     ELSE CAST(s.state AS FLOAT) 
            END as uv_val
        FROM states s 
        LEFT JOIN state_attributes a ON s.attributes_id = a.attributes_id 
        WHERE s.metadata_id = (SELECT uv_id_states FROM ids) 
            AND ((SELECT sensor_uv FROM vars) LIKE 'weather.%' OR NOT EXISTS (SELECT 1 FROM statistics WHERE metadata_id = (SELECT uv_id_stats FROM ids)))
            AND s.last_updated_ts > strftime('%s', 'now', '-10 days') 
            AND s.state NOT IN ('unknown', 'unavailable', '')
),

matching_days AS (
    /* Findet vergangene Tage, deren Bewölkungs- und UV-Profil dem heutigen Forecast am nächsten kommt */
    SELECT 
        date(c.ts, 'unixepoch') as day, 
        AVG(CASE WHEN strftime('%H:%M', c.ts, 'unixepoch') BETWEEN (SELECT sun_start FROM pv_activity) AND (SELECT sun_end FROM pv_activity) THEN c.val END) as h_avg_total_val,
        AVG(CASE WHEN strftime('%H:%M', c.ts, 'unixepoch') >= strftime('%H:00', 'now') AND strftime('%H:%M', c.ts, 'unixepoch') <= (SELECT sun_end FROM pv_activity) THEN c.val END) as h_avg_rest_val,
        AVG(CASE WHEN strftime('%H:%M', u.ts, 'unixepoch') BETWEEN (SELECT sun_start FROM pv_activity) AND (SELECT sun_end FROM pv_activity) THEN u.uv_val END) as uv_avg_total_val,
        AVG(CASE WHEN strftime('%H:%M', u.ts, 'unixepoch') >= strftime('%H:00', 'now') AND strftime('%H:%M', u.ts, 'unixepoch') <= (SELECT sun_end FROM pv_activity) THEN u.uv_val END) as uv_avg_rest_val
    FROM cloud_history c
    JOIN uv_history u ON date(c.ts, 'unixepoch') = date(u.ts, 'unixepoch')
    -- Filtert die Historie: Alles vor dem heutigen lokalen Tag (Offset-gesteuert)
    WHERE date(c.ts, 'unixepoch') < date('now', (SELECT offset FROM vars)) 
    GROUP BY 1 
    HAVING h_avg_total_val IS NOT NULL AND h_avg_total_val > 0
    ORDER BY ABS(
        COALESCE(h_avg_rest_val, h_avg_total_val) -- Fallback auf Gesamt-Schnitt wenn Rest null ist
        - (SELECT f_avg FROM forecast_val)
    ) ASC
),

final_data AS (
    /* Ermittelt die realen PV-Erträge der passendsten historischen Tage */
    SELECT 
        md.*,
        (SELECT MAX(state) FROM statistics WHERE metadata_id = (SELECT p_id FROM ids) AND date(start_ts, 'unixepoch') = md.day) as day_max,
        (SELECT MIN(state) FROM statistics WHERE metadata_id = (SELECT p_id FROM ids) AND date(start_ts, 'unixepoch') = md.day AND state > 0) as day_min,
        COALESCE((SELECT state FROM statistics WHERE metadata_id = (SELECT p_id FROM ids) AND date(start_ts, 'unixepoch') = md.day AND strftime('%H', start_ts, 'unixepoch') = strftime('%H', 'now') LIMIT 1), (SELECT MIN(state) FROM statistics WHERE metadata_id = (SELECT p_id FROM ids) AND date(start_ts, 'unixepoch') = md.day AND state > 0)) as h_hour_curr,
        COALESCE((SELECT state FROM statistics WHERE metadata_id = (SELECT p_id FROM ids) AND date(start_ts, 'unixepoch') = md.day AND strftime('%H', start_ts, 'unixepoch') = strftime('%H', 'now', '-1 hour') LIMIT 1), (SELECT MIN(state) FROM statistics WHERE metadata_id = (SELECT p_id FROM ids) AND date(start_ts, 'unixepoch') = md.day AND state > 0)) as h_hour_prev
    FROM matching_days md
)

/* Generiert das finale JSON-Objekt für Home Assistant */
SELECT json_group_array(
    json_object(
        'date', day,
        'f_avg_today_remaining', (SELECT ROUND(f_avg, 1) FROM forecast_val),        
        'f_avg_tomorrow', (SELECT ROUND(f_avg_tomorrow, 1) FROM forecast_next_day),
        'uv_avg_today_remaining', (SELECT ROUND(uv_avg, 1) FROM forecast_val),
        'uv_avg_tomorrow', (SELECT ROUND(uv_avg_tomorrow, 1) FROM forecast_next_day),
        'h_avg_total', ROUND(h_avg_total_val, 1),
        /* COALESCE: before sunrise h_avg_rest_val is NULL (UTC window '23:xx'..'17:xx' empty) */
        /* Fall back to h_avg_total_val so Jinja cloud-matching works correctly at midnight.   */
        'h_avg_remaining', ROUND(COALESCE(h_avg_rest_val, h_avg_total_val), 1),
        'uv_avg_total', ROUND(uv_avg_total_val, 1),
        'uv_avg_remaining', ROUND(COALESCE(uv_avg_rest_val, uv_avg_total_val), 1),
        'yield_day_total', ROUND(day_max - day_min, 2),
        'yield_day_remaining', ROUND(CASE
            WHEN strftime('%H:%M', 'now', (SELECT offset FROM vars)) > (SELECT sun_end_local   FROM pv_activity)
                THEN 0.0
            WHEN strftime('%H:%M', 'now', (SELECT offset FROM vars)) < (SELECT sun_start_local FROM pv_activity)
                THEN (day_max - day_min)
            ELSE MAX(0, 
                ((h_hour_curr - h_hour_prev) * (1.0 - (CAST(strftime('%M', 'now') AS FLOAT) / 60.0)) * 
                  CASE 
                    WHEN strftime('%H', 'now') = strftime('%H', (SELECT sun_start FROM pv_activity)) THEN 0.85
                    WHEN strftime('%H', 'now') = strftime('%H', (SELECT sun_end FROM pv_activity)) THEN 0.70
                    ELSE 1.0 
                  END)
                + (day_max - h_hour_curr)
            )
        END, 2),
        'pv_start', (SELECT sun_start FROM pv_activity),
        'pv_end', (SELECT sun_end FROM pv_activity)
    )
) as json FROM final_data WHERE day_max > 0;

{# PV FORECAST: Remaining yield today – weighted avg + LOO + trend damping + back-test + cloud-gated penalty #}
{% set raw = value if value is defined else state_attr('sensor.pv_remaining_states', 'json') %}

{% if raw and raw != '[]' and raw is not none %}
  {% set data = raw | from_json %}

  {# --- 0. NIGHT-CHECK --- #}
  {% set offset_min = (now().utcoffset().total_seconds() / 60) | int %}
  {% set pv_end_utc = data[0].pv_end | default('17:30') %}
  {% set end_min_local = ((pv_end_utc.split(':')[0] | int) * 60 + (pv_end_utc.split(':')[1] | int) + offset_min) % 1440 %}
  {% if (now().hour * 60 + now().minute) > end_min_local %}
    0.0
  {% else %}

    {# --- 1. BASE DATA --- #}
    {% set f_avg = data[0].f_avg_today_remaining | float(default=50.0) %}
    {% set current_month = now().month %}
    {% set snow_factor_today = 1.0 %}

    {# --- 2. SEASONAL SNOW DETECTION (Dec/Jan/Feb) --- #}
    {% if current_month in [12, 1, 2] %}
      {% set yesterday_date = (now() - timedelta(days=1)).strftime('%Y-%m-%d') %}
      {% set yesterday_data = data | selectattr('date', 'equalto', yesterday_date) | list | first %}
      {% if yesterday_data is defined %}
        {% set yesterday_perf = yesterday_data.yield_day_remaining | float(0) / ([105 - yesterday_data.h_avg_remaining | float(0), 5] | max) %}
        {% if yesterday_perf < 0.02 %}{% set snow_factor_today = 0.1 %}{% endif %}
      {% endif %}
    {% endif %}

    {# --- 3. ASTRONOMICAL BASE DATA --- #}
    {% set doy = now().strftime('%j') | int(default=1) %}
    {% set latitude = latitude if latitude is defined else state_attr('zone.home', 'latitude') | float(48.0) %}
    {% set lat_rad = latitude * pi / 180 %}
    {% set decl = -0.4093 * cos(2 * pi * (doy + 10) / 365) %}
    {% set dl_today = 24 / pi * acos([[(-tan(lat_rad) * tan(decl)), -1.0] | max, 1.0] | min) %}
    {% set sun_today = 0.80 + 0.20 * cos((doy - 172) * 2 * pi / 365) %}

    {# --- 4. BUILD DATA POOL (dynamic UV weight, Recency-Bonus, Top 15) --- #}
    {% set f_uv_avg = data[0].uv_avg_today_remaining | float(default=0.0) %}
    {# uv_w scales with forecast cloud: 0% clouds → 30%, 100% clouds → 70% #}
    {% set uv_w = [0.3 + 0.4 * (f_avg / 100.0), 0.7] | min %}
    {% set ns_pool = namespace(items=[], total_w=0) %}
    {% for item in data %}
      {% set yield_raw = item.yield_day_remaining | float(default=0) %}
      {% set clouds = item.h_avg_remaining | float(default=0) %}
      {% set uv_hist = item.uv_avg_remaining | float(default=0) %}
      {% set dt_item = as_datetime(item.date) %}
      {% if dt_item is not none %}
        {% set item_day = dt_item.strftime('%j') | int(default=1) %}
        {% set decl_i = -0.4093 * cos(2 * pi * (item_day + 10) / 365) %}
        {% set dl_item = 24 / pi * acos([[(-tan(lat_rad) * tan(decl_i)), -1.0] | max, 1.0] | min) %}
        {% set sun_item = 0.80 + 0.20 * cos((item_day - 172) * 2 * pi / 365) %}
        {% set s_korr = (sun_today / sun_item) * (dl_today / dl_item) %}
        {% set y_korr = yield_raw * s_korr %}
        {% set diff_c = (clouds - f_avg) | abs %}
        {% if f_uv_avg > 0 %}
          {% set diff = diff_c * (1.0 - uv_w) + (uv_hist - f_uv_avg) | abs * 8.0 * uv_w %}
        {% else %}
          {% set diff = diff_c %}
        {% endif %}
        {% set days_ago = ((now().timestamp() - dt_item.timestamp()) / 86400) | int(0) %}
        {% set w = (1 / ([diff, 0.5] | max)) * (1.0 + 0.3 * ([1.0 - days_ago / 30.0, 0.0] | max)) %}
        {% if yield_raw > 0.05 or clouds > 95 or current_month in [12, 1, 2] %}
          {% set ns_pool.total_w = ns_pool.total_w + w %}
          {% set ns_pool.items = ns_pool.items + [{'date': item.date, 'h_avg': clouds, 'y_korr': y_korr, 'w': w, 'days_ago': days_ago}] %}
        {% endif %}
      {% endif %}
    {% endfor %}

    {# --- 5. FORECAST CALCULATION (Top 15, decision logic) --- #}
    {% set top15 = (ns_pool.items | sort(attribute='w', reverse=True))[:15] %}
    {% set ns_top = namespace(total_w=0) %}
    {% for item in top15 %}{% set ns_top.total_w = ns_top.total_w + item.w %}{% endfor %}
    {% set pool = top15 %}
    {% set brighter = pool | selectattr('h_avg', 'le', f_avg) | list %}
    {% set darker = pool | selectattr('h_avg', 'ge', f_avg) | list %}
    {% set res = 0 %}
    {% if brighter | count > 0 and darker | count == 0 %}
      {% set worst_day = brighter | sort(attribute='y_korr') | first %}
      {% set res = worst_day.y_korr * ([120 - f_avg, 5.0] | max / [120 - worst_day.h_avg, 5.0] | max) %}
    {% elif darker | count > 0 and pool | selectattr('h_avg', 'le', f_avg) | list | count == 0 %}
      {% set res = darker | map(attribute='y_korr') | max %}
    {% elif pool | count > 0 %}
      {% set ns_mix = namespace(ws=0) %}
      {% for item in pool %}{% set ns_mix.ws = ns_mix.ws + (item.y_korr * item.w) %}{% endfor %}
      {% set res = ns_mix.ws / (ns_top.total_w if ns_top.total_w > 0 else 1) %}
    {% endif %}

    {# --- 6. LOO CROSS-VALIDATION: down-weight outlier pool days --- #}
    {% set ns_cv = namespace(items=[]) %}
    {% for item_i in pool %}
      {% set ns_loo = namespace(w=0, wy=0) %}
      {% for item_j in pool %}
        {% if item_j.date != item_i.date %}
          {% set ns_loo.w  = ns_loo.w  + item_j.w %}
          {% set ns_loo.wy = ns_loo.wy + item_j.w * item_j.y_korr %}
        {% endif %}
      {% endfor %}
      {% set acc = ((item_i.y_korr / (ns_loo.wy / ns_loo.w)) * 100) | round(0) | int if (ns_loo.w > 0 and ns_loo.wy > 0) else 100 %}
      {% set ns_cv.items = ns_cv.items + [{'date': item_i.date, 'acc': acc}] %}
    {% endfor %}
    {% if pool | count > 1 %}
      {% set ns_corr = namespace(w=0, wy=0) %}
      {% for item_i in pool %}
        {% set cv = ns_cv.items | selectattr('date', 'equalto', item_i.date) | list %}
        {% set acc_factor = 1.0 / (1.0 + ((cv[0].acc - 100) | abs) / 100.0) if cv | length > 0 else 1.0 %}
        {% set ns_corr.w  = ns_corr.w  + item_i.w * acc_factor %}
        {% set ns_corr.wy = ns_corr.wy + item_i.y_korr * item_i.w * acc_factor %}
      {% endfor %}
      {% if ns_corr.w > 0 and ns_corr.wy > 0 %}{% set res = ns_corr.wy / ns_corr.w %}{% endif %}
    {% endif %}

    {# --- 7. TREND DAMPING: recent ≤14d avg >15% above older → dampen 50% of excess --- #}
    {% set ns_rec = namespace(w=0, wy=0) %}
    {% set ns_old = namespace(w=0, wy=0) %}
    {% for item_i in pool %}
      {% if item_i.days_ago <= 14 %}
        {% set ns_rec.w = ns_rec.w + item_i.w %}{% set ns_rec.wy = ns_rec.wy + item_i.y_korr * item_i.w %}
      {% else %}
        {% set ns_old.w = ns_old.w + item_i.w %}{% set ns_old.wy = ns_old.wy + item_i.y_korr * item_i.w %}
      {% endif %}
    {% endfor %}
    {% if ns_rec.w > 0 and ns_old.w > 0 %}
      {% set avg_rec = ns_rec.wy / ns_rec.w %}
      {% set avg_old = ns_old.wy / ns_old.w %}
      {% if avg_old > 0 and (avg_rec / avg_old) > 1.15 %}
        {% set res = res / (1.0 + 0.5 * ((avg_rec / avg_old) - 1.0)) %}
      {% endif %}
    {% endif %}

    {# --- 8. BACK-TEST: data-driven carry-through from consecutive shortfall pairs --- #}
    {% set ns_all = namespace(sum_y=0.0, count_y=0) %}
    {% for item in pool %}{% if item.y_korr > 0 %}{% set ns_all.sum_y = ns_all.sum_y + item.y_korr %}{% set ns_all.count_y = ns_all.count_y + 1 %}{% endif %}{% endfor %}
    {% set mean_y = ns_all.sum_y / ([ns_all.count_y, 1] | max) %}
    {% set ns_bt = namespace(total=0, useful=0, trigger_sum=0.0, carry_sum=0.0) %}
    {% for item_i in pool %}
      {% if item_i.y_korr >= 0.40 * mean_y and item_i.y_korr < 0.85 * mean_y %}
        {% set next_items = pool | selectattr('date', 'equalto', (as_datetime(item_i.date) + timedelta(days=1)).strftime('%Y-%m-%d')) | list %}
        {% if next_items | length > 0 %}
          {% set ns_bt.total = ns_bt.total + 1 %}
          {% set ns_bt.trigger_sum = ns_bt.trigger_sum + (1.0 - item_i.y_korr / mean_y) %}
          {% set ns_bt.carry_sum = ns_bt.carry_sum + ([1.0 - next_items[0].y_korr / mean_y, 0.0] | max) %}
          {% if next_items[0].y_korr < mean_y %}{% set ns_bt.useful = ns_bt.useful + 1 %}{% endif %}
        {% endif %}
      {% endif %}
    {% endfor %}
    {% set effective_carry = (ns_bt.carry_sum / ns_bt.trigger_sum) * (ns_bt.useful / ns_bt.total) if (ns_bt.total > 0 and ns_bt.trigger_sum > 0) else 0.3 %}

    {# --- 9. CLOUD-GATED YESTERDAY PENALTY (both days ≥60% cloudy) --- #}
    {% set yesterday_date_yp = (now() - timedelta(days=1)).strftime('%Y-%m-%d') %}
    {% set yest_cv = ns_cv.items | selectattr('date', 'equalto', yesterday_date_yp) | list %}
    {% set yest_item = pool | selectattr('date', 'equalto', yesterday_date_yp) | list %}
    {% set yest_clouds = yest_item[0].h_avg if yest_item | length > 0 else 0 %}
    {% if yest_cv | length > 0 %}
      {% set yest_acc = yest_cv[0].acc %}
      {% if yest_acc >= 40 and yest_acc < 85 and f_avg >= 60 and yest_clouds >= 60 %}
        {% set res = res * ([1.0 - effective_carry * (1.0 - yest_acc / 100.0), 0.5] | max) %}
      {% endif %}
    {% endif %}

    {# --- 10. FINAL SCALING --- #}
    {{ (res * snow_factor_today) | round(2) }}

  {% endif %}
{% else %}
  0.0
{% endif %}

{% set raw_json = state_attr('sensor.pv_remaining_states', 'json') %}
{% if raw_json and raw_json != '[]' and raw_json is not none %}
  {% set data = raw_json | from_json %}

  {% if data | length > 0 %}
    {% set f_avg = data[0].f_avg_today_remaining | float(default=50.0) %}
    {% set f_uv_avg = data[0].uv_avg_today_remaining | float(default=0.0) %}

    {# 0. NIGHT-CHECK #}
    {% set offset_min = (now().utcoffset().total_seconds() / 60) | int %}
    {% set pv_end_utc = data[0].pv_end | default('17:30') %}
    {% set end_min_local = ((pv_end_utc.split(':')[0] | int) * 60 + (pv_end_utc.split(':')[1] | int) + offset_min) % 1440 %}
    {% set is_night = (now().hour * 60 + now().minute) > end_min_local %}

    {# 1. SEASONAL SNOW DETECTION (Dec / Jan / Feb) #}
    {% set current_month = now().month %}
    {% set snow_factor_today = 1.0 %}
    {% if current_month in [12, 1, 2] %}
      {% set yesterday_date = (now() - timedelta(days=1)).strftime('%Y-%m-%d') %}
      {% set yesterday_data = data | selectattr('date', 'equalto', yesterday_date) | list | first %}
      {% if yesterday_data is defined %}
        {% set yesterday_perf = yesterday_data.yield_day_remaining | float(0) / ([105 - yesterday_data.h_avg_remaining | float(0), 5] | max) %}
        {% if yesterday_perf < 0.02 %}{% set snow_factor_today = 0.1 %}{% endif %}
      {% endif %}
    {% endif %}

    {# 2. ASTRONOMICAL BASE DATA #}
    {% set latitude = state_attr('zone.home', 'latitude') | float(48.0) %}
    {% set doy = now().strftime('%j') | int(default=1) %}
    {% set lat_rad = latitude * pi / 180 %}
    {% set decl = -0.4093 * cos(2 * pi * (doy + 10) / 365) %}
    {% set dl_today = 24 / pi * acos([[(-tan(lat_rad) * tan(decl)), -1.0] | max, 1.0] | min) %}
    {% set sun_today = 0.80 + 0.20 * cos((doy - 172) * 2 * pi / 365) %}

    {# 3. POOL (dynamic UV weight, Recency-Bonus, Top 15) #}
    {% set uv_w = [0.3 + 0.4 * (f_avg / 100.0), 0.7] | min %}
    {% set ns_pool = namespace(items=[], total_w=0) %}
    {% for item in data %}
      {% set yield_raw = item.yield_day_remaining | float(default=0) %}
      {% set clouds = item.h_avg_remaining | float(default=0) %}
      {% set clouds_total = item.h_avg_total | float(default=0) %}
      {% set uv = item.uv_avg_remaining | float(default=0) %}
      {% set item_dt = as_datetime(item.date) %}
      {% if item_dt is not none %}
        {% set item_day = item_dt.strftime('%j') | int(default=1) %}
        {% set decl_i = -0.4093 * cos(2 * pi * (item_day + 10) / 365) %}
        {% set dl_item = 24 / pi * acos([[(-tan(lat_rad) * tan(decl_i)), -1.0] | max, 1.0] | min) %}
        {% set sun_item = 0.80 + 0.20 * cos((item_day - 172) * 2 * pi / 365) %}
        {% set s_korr = (sun_today / sun_item) * (dl_today / dl_item) %}
        {% set diff_c = (clouds - f_avg) | abs %}
        {% if f_uv_avg > 0 %}
          {% set diff = diff_c * (1.0 - uv_w) + (uv - f_uv_avg) | abs * 8.0 * uv_w %}
        {% else %}
          {% set diff = diff_c %}
        {% endif %}
        {% set days_ago = ((now().timestamp() - item_dt.timestamp()) / 86400) | int(0) %}
        {% set w = (1 / ([diff, 0.5] | max)) * (1.0 + 0.3 * ([1.0 - days_ago / 30.0, 0.0] | max)) %}
        {% if yield_raw > 0.05 or clouds > 95 or current_month in [12, 1, 2] %}
          {% set ns_pool.total_w = ns_pool.total_w + w %}
          {% set ns_pool.items = ns_pool.items + [{'date': item.date, 'h_avg': clouds, 'h_avg_total': clouds_total, 'uv_avg': uv, 'y_korr': yield_raw * s_korr, 's_fakt': s_korr, 'w': w, 'yield_day_total': item.yield_day_total, 'days_ago': days_ago, 'filtered': false}] %}
        {% else %}
          {% set ns_pool.items = ns_pool.items + [{'date': item.date, 'h_avg': clouds, 'h_avg_total': clouds_total, 'uv_avg': uv, 'y_korr': yield_raw * s_korr, 's_fakt': s_korr, 'w': 0, 'yield_day_total': item.yield_day_total, 'days_ago': days_ago, 'filtered': true}] %}
        {% endif %}
      {% endif %}
    {% endfor %}

    {# Top 15 selection #}
    {% set top15 = (ns_pool.items | sort(attribute='w', reverse=True))[:15] %}
    {% set ns_top = namespace(total_w=0) %}
    {% for item in top15 %}{% if not item.filtered %}{% set ns_top.total_w = ns_top.total_w + item.w %}{% endif %}{% endfor %}
    {% set pool = top15 | selectattr('filtered', 'equalto', false) | list %}

    {# 4. Decision logic #}
    {% set brighter = pool | selectattr('h_avg', 'le', f_avg) | list %}
    {% set darker = pool | selectattr('h_avg', 'ge', f_avg) | list %}
    {% set res = 0 %}
    {% set method = "No data" %}
    {% if brighter | count > 0 and darker | count == 0 %}
      {% set method = "Light reduction" %}
      {% set worst_day = brighter | sort(attribute='y_korr') | first %}
      {% set res = worst_day.y_korr * ([120 - f_avg, 5.0] | max / [120 - worst_day.h_avg, 5.0] | max) %}
    {% elif darker | count > 0 and pool | selectattr('h_avg', 'le', f_avg) | list | count == 0 %}
      {% set method = "Max assumption" %}
      {% set res = darker | map(attribute='y_korr') | max %}
    {% elif pool | count > 0 %}
      {% set method = "Weighted average" %}
      {% set ns_mix = namespace(ws=0) %}
      {% for item in pool %}{% set ns_mix.ws = ns_mix.ws + (item.y_korr * item.w) %}{% endfor %}
      {% set res = ns_mix.ws / (ns_top.total_w if ns_top.total_w > 0 else 1) %}
    {% endif %}

    {# 5. LOO cross-validation #}
    {% set ns_cv = namespace(items=[]) %}
    {% for item_i in pool %}
      {% set ns_loo = namespace(w=0, wy=0) %}
      {% for item_j in pool %}
        {% if item_j.date != item_i.date %}
          {% set ns_loo.w = ns_loo.w + item_j.w %}{% set ns_loo.wy = ns_loo.wy + item_j.w * item_j.y_korr %}
        {% endif %}
      {% endfor %}
      {% set acc = ((item_i.y_korr / (ns_loo.wy / ns_loo.w)) * 100) | round(0) | int if (ns_loo.w > 0 and ns_loo.wy > 0) else 100 %}
      {% set ns_cv.items = ns_cv.items + [{'date': item_i.date, 'acc': acc}] %}
    {% endfor %}
    {% if pool | count > 1 %}
      {% set ns_corr = namespace(w=0, wy=0) %}
      {% for item_i in pool %}
        {% set cv = ns_cv.items | selectattr('date', 'equalto', item_i.date) | list %}
        {% set acc_factor = 1.0 / (1.0 + ((cv[0].acc - 100) | abs) / 100.0) if cv | length > 0 else 1.0 %}
        {% set ns_corr.w = ns_corr.w + item_i.w * acc_factor %}{% set ns_corr.wy = ns_corr.wy + item_i.y_korr * item_i.w * acc_factor %}
      {% endfor %}
      {% if ns_corr.w > 0 and ns_corr.wy > 0 %}{% set res = ns_corr.wy / ns_corr.w %}{% endif %}
    {% endif %}

    {# 6. Trend damping #}
    {% set ns_rec = namespace(w=0, wy=0) %}{% set ns_old = namespace(w=0, wy=0) %}
    {% for item_i in pool %}
      {% if item_i.days_ago <= 14 %}{% set ns_rec.w = ns_rec.w + item_i.w %}{% set ns_rec.wy = ns_rec.wy + item_i.y_korr * item_i.w %}
      {% else %}{% set ns_old.w = ns_old.w + item_i.w %}{% set ns_old.wy = ns_old.wy + item_i.y_korr * item_i.w %}{% endif %}
    {% endfor %}
    {% set trend_damped = false %}
    {% if ns_rec.w > 0 and ns_old.w > 0 %}
      {% set avg_rec = ns_rec.wy / ns_rec.w %}{% set avg_old = ns_old.wy / ns_old.w %}
      {% if avg_old > 0 and (avg_rec / avg_old) > 1.15 %}
        {% set res = res / (1.0 + 0.5 * ((avg_rec / avg_old) - 1.0)) %}{% set trend_damped = true %}
      {% endif %}
    {% endif %}

    {# 7. Back-test + Cloud-gated penalty #}
    {% set ns_all = namespace(sum_y=0.0, count_y=0) %}
    {% for item in pool %}{% if item.y_korr > 0 %}{% set ns_all.sum_y = ns_all.sum_y + item.y_korr %}{% set ns_all.count_y = ns_all.count_y + 1 %}{% endif %}{% endfor %}
    {% set mean_y = ns_all.sum_y / ([ns_all.count_y, 1] | max) %}
    {% set ns_bt = namespace(total=0, useful=0, trigger_sum=0.0, carry_sum=0.0) %}
    {% for item_i in pool %}
      {% if item_i.y_korr >= 0.40 * mean_y and item_i.y_korr < 0.85 * mean_y %}
        {% set next_items = pool | selectattr('date', 'equalto', (as_datetime(item_i.date) + timedelta(days=1)).strftime('%Y-%m-%d')) | list %}
        {% if next_items | length > 0 %}
          {% set ns_bt.total = ns_bt.total + 1 %}{% set ns_bt.trigger_sum = ns_bt.trigger_sum + (1.0 - item_i.y_korr / mean_y) %}
          {% set ns_bt.carry_sum = ns_bt.carry_sum + ([1.0 - next_items[0].y_korr / mean_y, 0.0] | max) %}
          {% if next_items[0].y_korr < mean_y %}{% set ns_bt.useful = ns_bt.useful + 1 %}{% endif %}
        {% endif %}
      {% endif %}
    {% endfor %}
    {% set effective_carry = (ns_bt.carry_sum / ns_bt.trigger_sum) * (ns_bt.useful / ns_bt.total) if (ns_bt.total > 0 and ns_bt.trigger_sum > 0) else 0.3 %}
    {% set yest_date = (now() - timedelta(days=1)).strftime('%Y-%m-%d') %}
    {% set yest_cv = ns_cv.items | selectattr('date', 'equalto', yest_date) | list %}
    {% set yest_item = pool | selectattr('date', 'equalto', yest_date) | list %}
    {% set yest_clouds = yest_item[0].h_avg if yest_item | length > 0 else 0 %}
    {% set penalty_applied = false %}
    {% if yest_cv | length > 0 %}
      {% set yest_acc = yest_cv[0].acc %}
      {% if yest_acc >= 40 and yest_acc < 85 and f_avg >= 60 and yest_clouds >= 60 %}
        {% set res = res * ([1.0 - effective_carry * (1.0 - yest_acc / 100.0), 0.5] | max) %}
        {% set penalty_applied = true %}
      {% endif %}
    {% endif %}

    {% set final_val = res * snow_factor_today %}

**Forecast:**
## {{ (0.0 if is_night else final_val | round(2)) }} kWh
*Basis: **{{ f_avg }}%** clouds · **{{ f_uv_avg | round(1) }}** UV · uv_w={{ (uv_w * 100) | round(0) | int }}% | **{{ method }}***
{% if snow_factor_today < 1.0 %}⚠️ **Schnee erkannt! (Faktor {{ (snow_factor_today * 100) | round(0) }}%)**{% endif %}
{% if trend_damped %}📉 Trend-Dämpfung aktiv{% endif %}
{% if penalty_applied %}☁️ Cloud-gated Penalty aktiv (carry={{ (effective_carry * 100) | round(0) | int }}%){% endif %}

| Datum | Tag-Bew. | Tag-Ertrag | Rest-Bew. | UV | Rest-Ertrag | LOO-Acc | Gewicht |
| :--- | :---: | :---: | :---: | :---: | :---: | :---: | :---: |
{%- for item in top15 %}
  {%- set cv = ns_cv.items | selectattr('date', 'equalto', item.date) | list %}
  {%- set acc_str = cv[0].acc | string + "%" if cv | length > 0 else "–" %}
| {{ item.date }} | {{ item.h_avg_total }}% | {{ item.yield_day_total }} | **{{ item.h_avg }}%** | {{ item.uv_avg | round(1) }} | **{{ (item.y_korr * snow_factor_today) | round(2) }} ({{ item.s_fakt | round(2) }}×)**{% if item.filtered %}❌{% endif %} | {{ acc_str }} | {{ (((item.w / ns_top.total_w) * 100) if ns_top.total_w > 0 else 0) | round(1) }}% |
{%- endfor %}

  {% else %}
**Keine Daten im SQL-Ergebnis.**
  {% endif %}
{% else %}
**Warte auf SQL-Daten...**
{% endif %}

{# PV FORECAST TOMORROW: weighted avg + LOO + trend damping + back-test + cloud-gated penalty #}
{% set raw_json = state_attr('sensor.pv_remaining_states', 'json') %}

{% if raw_json and raw_json != '[]' and raw_json is not none %}
  {% set data = raw_json | from_json %}

  {% set f_avg_tomorrow = data[0].f_avg_tomorrow | float(default=50.0) %}
  {% set f_uv_avg_tomorrow = data[0].uv_avg_tomorrow | float(default=0.0) %}

  {# ASTRONOMICAL BASE DATA FOR TOMORROW #}
  {% set latitude = latitude if latitude is defined else state_attr('zone.home', 'latitude') | float(48.0) %}
  {% set doy_tomorrow = (now() + timedelta(days=1)).strftime('%j') | int %}
  {% set lat_rad = latitude * pi / 180 %}
  {% set decl_tomorrow = -0.4093 * cos(2 * pi * (doy_tomorrow + 10) / 365) %}
  {% set dl_tomorrow = 24 / pi * acos([[(-tan(lat_rad) * tan(decl_tomorrow)), -1.0] | max, 1.0] | min) %}
  {% set sun_tomorrow = 0.80 + 0.20 * cos((doy_tomorrow - 172) * 2 * pi / 365) %}

  {# POOL: dynamic UV weight, Recency-Bonus, Top 15 #}
  {% set uv_w = [0.3 + 0.4 * (f_avg_tomorrow / 100.0), 0.7] | min %}
  {% set ns_pool = namespace(items=[], total_w=0) %}
  {% for item in data %}
    {% set yield_total = item.yield_day_total | float(default=0) %}
    {% set clouds_hist = item.h_avg_total | float(default=0) %}
    {% set uv_hist = item.uv_avg_total | float(default=0) %}
    {% set dt_item = as_datetime(item.date) %}
    {% if dt_item is not none %}
      {% set item_day = dt_item.strftime('%j') | int(default=1) %}
      {% set decl_i = -0.4093 * cos(2 * pi * (item_day + 10) / 365) %}
      {% set dl_item = 24 / pi * acos([[(-tan(lat_rad) * tan(decl_i)), -1.0] | max, 1.0] | min) %}
      {% set sun_item = 0.80 + 0.20 * cos((item_day - 172) * 2 * pi / 365) %}
      {% set s_korr = (sun_tomorrow / sun_item) * (dl_tomorrow / dl_item) %}
      {% set y_korr = yield_total * s_korr %}
      {% set diff_c = (clouds_hist - f_avg_tomorrow) | abs %}
      {% if f_uv_avg_tomorrow > 0 %}
        {% set diff = diff_c * (1.0 - uv_w) + (uv_hist - f_uv_avg_tomorrow) | abs * 8.0 * uv_w %}
      {% else %}
        {% set diff = diff_c %}
      {% endif %}
      {% set days_ago = ((now().timestamp() - dt_item.timestamp()) / 86400) | int(0) %}
      {% set w = (1 / ([diff, 0.5] | max)) * (1.0 + 0.3 * ([1.0 - days_ago / 30.0, 0.0] | max)) %}
      {% if yield_total > 0.05 %}
        {% set ns_pool.total_w = ns_pool.total_w + w %}
        {% set ns_pool.items = ns_pool.items + [{'date': item.date, 'h_avg': clouds_hist, 'w': w, 'y_korr': y_korr, 'days_ago': days_ago, 'filtered': false}] %}
      {% else %}
        {% set ns_pool.items = ns_pool.items + [{'date': item.date, 'h_avg': clouds_hist, 'w': 0, 'y_korr': y_korr, 'days_ago': days_ago, 'filtered': true}] %}
      {% endif %}
    {% endif %}
  {% endfor %}

  {% set top15 = (ns_pool.items | sort(attribute='w', reverse=True))[:15] %}
  {% set ns_top = namespace(total_w=0) %}
  {% for item in top15 %}{% if not item.filtered %}{% set ns_top.total_w = ns_top.total_w + item.w %}{% endif %}{% endfor %}
  {% set pool = top15 | selectattr('filtered', 'equalto', false) | list %}
  {% set brighter = pool | selectattr('h_avg', 'le', f_avg_tomorrow) | list %}
  {% set darker = pool | selectattr('h_avg', 'ge', f_avg_tomorrow) | list %}
  {% set res = 0 %}
  {% if brighter | count > 0 and darker | count == 0 %}
    {% set worst_day = brighter | sort(attribute='y_korr') | first %}
    {% set res = worst_day.y_korr * ([120 - f_avg_tomorrow, 5.0] | max / [120 - worst_day.h_avg, 5.0] | max) %}
  {% elif darker | count > 0 and pool | selectattr('h_avg', 'le', f_avg_tomorrow) | list | count == 0 %}
    {% set res = darker | map(attribute='y_korr') | max %}
  {% elif pool | count > 0 %}
    {% set ns_mix = namespace(ws=0) %}
    {% for item in pool %}{% set ns_mix.ws = ns_mix.ws + (item.y_korr * item.w) %}{% endfor %}
    {% set res = ns_mix.ws / (ns_top.total_w if ns_top.total_w > 0 else 1) %}
  {% endif %}

  {# LOO CROSS-VALIDATION #}
  {% set ns_cv = namespace(items=[]) %}
  {% for item_i in pool %}
    {% set ns_loo = namespace(w=0, wy=0) %}
    {% for item_j in pool %}
      {% if item_j.date != item_i.date %}{% set ns_loo.w = ns_loo.w + item_j.w %}{% set ns_loo.wy = ns_loo.wy + item_j.w * item_j.y_korr %}{% endif %}
    {% endfor %}
    {% set acc = ((item_i.y_korr / (ns_loo.wy / ns_loo.w)) * 100) | round(0) | int if (ns_loo.w > 0 and ns_loo.wy > 0) else 100 %}
    {% set ns_cv.items = ns_cv.items + [{'date': item_i.date, 'acc': acc}] %}
  {% endfor %}
  {% if pool | count > 1 %}
    {% set ns_corr = namespace(w=0, wy=0) %}
    {% for item_i in pool %}
      {% set cv = ns_cv.items | selectattr('date', 'equalto', item_i.date) | list %}
      {% set acc_factor = 1.0 / (1.0 + ((cv[0].acc - 100) | abs) / 100.0) if cv | length > 0 else 1.0 %}
      {% set ns_corr.w = ns_corr.w + item_i.w * acc_factor %}{% set ns_corr.wy = ns_corr.wy + item_i.y_korr * item_i.w * acc_factor %}
    {% endfor %}
    {% if ns_corr.w > 0 and ns_corr.wy > 0 %}{% set res = ns_corr.wy / ns_corr.w %}{% endif %}
  {% endif %}

  {# TREND DAMPING #}
  {% set ns_rec = namespace(w=0, wy=0) %}{% set ns_old = namespace(w=0, wy=0) %}
  {% for item_i in pool %}
    {% if item_i.days_ago <= 14 %}{% set ns_rec.w = ns_rec.w + item_i.w %}{% set ns_rec.wy = ns_rec.wy + item_i.y_korr * item_i.w %}
    {% else %}{% set ns_old.w = ns_old.w + item_i.w %}{% set ns_old.wy = ns_old.wy + item_i.y_korr * item_i.w %}{% endif %}
  {% endfor %}
  {% if ns_rec.w > 0 and ns_old.w > 0 %}
    {% set avg_rec = ns_rec.wy / ns_rec.w %}{% set avg_old = ns_old.wy / ns_old.w %}
    {% if avg_old > 0 and (avg_rec / avg_old) > 1.15 %}
      {% set res = res / (1.0 + 0.5 * ((avg_rec / avg_old) - 1.0)) %}
    {% endif %}
  {% endif %}

  {# BACK-TEST + CLOUD-GATED YESTERDAY PENALTY #}
  {% set ns_all = namespace(sum_y=0.0, count_y=0) %}
  {% for item in pool %}{% if item.y_korr > 0 %}{% set ns_all.sum_y = ns_all.sum_y + item.y_korr %}{% set ns_all.count_y = ns_all.count_y + 1 %}{% endif %}{% endfor %}
  {% set mean_y = ns_all.sum_y / ([ns_all.count_y, 1] | max) %}
  {% set ns_bt = namespace(total=0, useful=0, trigger_sum=0.0, carry_sum=0.0) %}
  {% for item_i in pool %}
    {% if item_i.y_korr >= 0.40 * mean_y and item_i.y_korr < 0.85 * mean_y %}
      {% set next_items = pool | selectattr('date', 'equalto', (as_datetime(item_i.date) + timedelta(days=1)).strftime('%Y-%m-%d')) | list %}
      {% if next_items | length > 0 %}
        {% set ns_bt.total = ns_bt.total + 1 %}{% set ns_bt.trigger_sum = ns_bt.trigger_sum + (1.0 - item_i.y_korr / mean_y) %}
        {% set ns_bt.carry_sum = ns_bt.carry_sum + ([1.0 - next_items[0].y_korr / mean_y, 0.0] | max) %}
        {% if next_items[0].y_korr < mean_y %}{% set ns_bt.useful = ns_bt.useful + 1 %}{% endif %}
      {% endif %}
    {% endif %}
  {% endfor %}
  {% set effective_carry = (ns_bt.carry_sum / ns_bt.trigger_sum) * (ns_bt.useful / ns_bt.total) if (ns_bt.total > 0 and ns_bt.trigger_sum > 0) else 0.3 %}
  {% set yesterday_date = (now() - timedelta(days=1)).strftime('%Y-%m-%d') %}
  {% set yest_cv = ns_cv.items | selectattr('date', 'equalto', yesterday_date) | list %}
  {% set yest_item = ns_pool.items | selectattr('date', 'equalto', yesterday_date) | selectattr('filtered', 'equalto', false) | list %}
  {% set yest_clouds = yest_item[0].h_avg if yest_item | length > 0 else 0 %}
  {% if yest_cv | length > 0 %}
    {% set yest_acc = yest_cv[0].acc %}
    {% if yest_acc >= 40 and yest_acc < 85 and f_avg_tomorrow >= 60 and yest_clouds >= 60 %}
      {% set res = res * ([1.0 - effective_carry * (1.0 - yest_acc / 100.0), 0.5] | max) %}
    {% endif %}
  {% endif %}

  {{ res | round(2) }}

{% else %}
  0.0
{% endif %}

{% set raw_json = state_attr('sensor.pv_remaining_states', 'json') %}
{% if raw_json and raw_json != '[]' and raw_json is not none %}
  {% set data = raw_json | from_json %}
  {# Nacht-Check #}
  {% set offset_min = (now().utcoffset().total_seconds() / 60) | int %}
  {% set pv_end_utc = data[0].pv_end | default('17:30') %}
  {% set end_min_local = ((pv_end_utc.split(':')[0] | int) * 60 + (pv_end_utc.split(':')[1] | int) + offset_min) % 1440 %}
  {% if (now().hour * 60 + now().minute) > end_min_local %}
    0.0
  {% else %}
    {% set f_avg = data[0].f_avg_today_remaining | float(default=50.0) %}
    {% set f_uv_avg = data[0].uv_avg_today_remaining | float(default=0.0) %}
    {% set doy = now().strftime('%j') | int(default=1) %}
    {% set latitude = latitude if latitude is defined else state_attr('zone.home', 'latitude') | float(48.0) %}
    {% set lat_rad = latitude * pi / 180 %}
    {% set decl = -0.4093 * cos(2 * pi * (doy + 10) / 365) %}
    {% set dl_today = 24 / pi * acos([[(-tan(lat_rad) * tan(decl)), -1.0] | max, 1.0] | min) %}
    {% set sun_today = 0.80 + 0.20 * cos((doy - 172) * 2 * pi / 365) %}
    {% set uv_w = [0.3 + 0.4 * (f_avg / 100.0), 0.7] | min %}
    {% set ns_pool = namespace(items=[]) %}
    {% for item in data %}
      {% set dt_item = as_datetime(item.date) %}
      {% if dt_item is not none %}
        {% set item_day = dt_item.strftime('%j') | int(default=1) %}
        {% set decl_i = -0.4093 * cos(2 * pi * (item_day + 10) / 365) %}
        {% set dl_item = 24 / pi * acos([[(-tan(lat_rad) * tan(decl_i)), -1.0] | max, 1.0] | min) %}
        {% set sun_item = 0.80 + 0.20 * cos((item_day - 172) * 2 * pi / 365) %}
        {% set s_korr = (sun_today / sun_item) * (dl_today / dl_item) %}
        {% set yield_korr = item.yield_day_remaining | float(default=0) * s_korr %}
        {% set uv_hist = item.uv_avg_remaining | float(default=0) %}
        {% set diff_c = (item.h_avg_remaining | float(default=0) - f_avg) | abs %}
        {% if f_uv_avg > 0 %}
          {% set diff = diff_c * (1.0 - uv_w) + (uv_hist - f_uv_avg) | abs * 8.0 * uv_w %}
        {% else %}
          {% set diff = diff_c %}
        {% endif %}
        {% set ns_pool.items = ns_pool.items + [{'diff': diff, 'y_korr': yield_korr}] %}
      {% endif %}
    {% endfor %}
    {% set top15 = (ns_pool.items | sort(attribute='diff'))[:15] %}
    {% set max_yield = top15 | map(attribute='y_korr') | max if top15 | count > 0 else 0 %}
    {{ max_yield | round(2) }}
  {% endif %}
{% else %}
  0
{% endif %}

{% set raw_json = state_attr('sensor.pv_remaining_states', 'json') %}
{% if raw_json and raw_json != '[]' and raw_json is not none %}
  {% set data = raw_json | from_json %}
  {# Nacht-Check #}
  {% set offset_min = (now().utcoffset().total_seconds() / 60) | int %}
  {% set pv_end_utc = data[0].pv_end | default('17:30') %}
  {% set end_min_local = ((pv_end_utc.split(':')[0] | int) * 60 + (pv_end_utc.split(':')[1] | int) + offset_min) % 1440 %}
  {% if (now().hour * 60 + now().minute) > end_min_local %}
    0.0
  {% else %}
    {% set f_avg = data[0].f_avg_today_remaining | float(default=50.0) %}
    {% set f_uv_avg = data[0].uv_avg_today_remaining | float(default=0.0) %}
    {% set current_month = now().month %}
    {% set doy = now().strftime('%j') | int(default=1) %}
    {% set latitude = latitude if latitude is defined else state_attr('zone.home', 'latitude') | float(48.0) %}
    {% set lat_rad = latitude * pi / 180 %}
    {% set decl = -0.4093 * cos(2 * pi * (doy + 10) / 365) %}
    {% set dl_today = 24 / pi * acos([[(-tan(lat_rad) * tan(decl)), -1.0] | max, 1.0] | min) %}
    {% set sun_today = 0.80 + 0.20 * cos((doy - 172) * 2 * pi / 365) %}
    {% set uv_w = [0.3 + 0.4 * (f_avg / 100.0), 0.7] | min %}
    {% set ns_pool = namespace(items=[]) %}
    {% for item in data %}
      {% set dt_item = as_datetime(item.date) %}
      {% if dt_item is not none %}
        {% set item_day = dt_item.strftime('%j') | int(default=1) %}
        {% set decl_i = -0.4093 * cos(2 * pi * (item_day + 10) / 365) %}
        {% set dl_item = 24 / pi * acos([[(-tan(lat_rad) * tan(decl_i)), -1.0] | max, 1.0] | min) %}
        {% set sun_item = 0.80 + 0.20 * cos((item_day - 172) * 2 * pi / 365) %}
        {% set s_korr = (sun_today / sun_item) * (dl_today / dl_item) %}
        {% set yield_korr = item.yield_day_remaining | float(default=0) * s_korr %}
        {% set uv_hist = item.uv_avg_remaining | float(default=0) %}
        {% set diff_c = (item.h_avg_remaining | float(default=0) - f_avg) | abs %}
        {% if f_uv_avg > 0 %}
          {% set diff = diff_c * (1.0 - uv_w) + (uv_hist - f_uv_avg) | abs * 8.0 * uv_w %}
        {% else %}
          {% set diff = diff_c %}
        {% endif %}
        {% set ns_pool.items = ns_pool.items + [{'diff': diff, 'h_avg': item.h_avg_remaining | float(0), 'y_korr': yield_korr}] %}
      {% endif %}
    {% endfor %}
    {% set top15 = (ns_pool.items | sort(attribute='diff'))[:15] %}
    {% set brighter = top15 | selectattr('h_avg', 'le', f_avg) | list %}
    {% set darker = top15 | selectattr('h_avg', 'gt', f_avg) | list %}
    {% set res = 0 %}
    {% if top15 | count > 0 %}
      {% if brighter | count > 0 and darker | count == 0 %}
        {% set worst = brighter | sort(attribute='y_korr') | first %}
        {% set res = worst.y_korr * ([120 - f_avg, 5.0] | max / [120 - worst.h_avg, 5.0] | max) %}
      {% elif darker | count > 0 and brighter | count == 0 %}
        {% set res = darker | map(attribute='y_korr') | min %}
      {% else %}
        {% set res = top15 | map(attribute='y_korr') | min %}
      {% endif %}
    {% endif %}
    {{ res | round(2) }}
  {% endif %}
{% else %}
  0
{% endif %}