Aggiorna script backup e bot meteo Telegram.

Co-authored-by: Cursor <cursoragent@cursor.com>

scripts/raspiBackup_loogle_post.sh

@@ -1,16 +1,50 @@
 #!/bin/bash
 # raspiBackup post extension — notifica Loogle Casa (solo WebApp).
+#
+# RaspiBackup chiama il post hook PRIMA di STARTSERVICES: su Pi2 Casa è giù
+# (before-stop ferma loogle-casa, STOPSERVICES ferma docker). Non notificare
+# subito: systemd-run stacca dal cgroup e riprova finché l'API risponde.
+#
 # Sourced da raspiBackup: $1 = return code backup.
+# Eseguito da systemd-run: $1 = --wait-send
+
+LOOGLE_NOTIFY="/home/daniely/docker/loogle-casa/scripts/loogle-notify.sh"
+MAX_TRIES="${LOOGLE_BACKUP_NOTIFY_TRIES:-36}"
+SLEEP_SECS="${LOOGLE_BACKUP_NOTIFY_SLEEP:-5}"
+
+wait_send() {
+    local title="$1" body="$2" severity="$3" tag="$4"
+    local i
+    if [[ ! -x "$LOOGLE_NOTIFY" ]]; then
+        echo "loogle-notify.sh assente" >&2
+        exit 0
+    fi
+    for ((i = 1; i <= MAX_TRIES; i++)); do
+        if "$LOOGLE_NOTIFY" --title "$title" --body "$body" --category raspi_backup \
+            --severity "$severity" --tag "$tag"; then
+            echo "notify ok try=$i tag=$tag"
+            exit 0
+        fi
+        echo "notify retry $i/$MAX_TRIES tag=$tag" >&2
+        sleep "$SLEEP_SECS"
+    done
+    echo "notify failed after ${MAX_TRIES} tries tag=$tag" >&2
+    exit 1
+}
+
+if [[ "${1:-}" == "--wait-send" ]]; then
+    wait_send "${2:-}" "${3:-}" "${4:-info}" "${5:-raspi_backup}"
+    exit $?
+fi
 
 RC="${1:-1}"
-LOOGLE_NOTIFY="/home/daniely/docker/loogle-casa/scripts/loogle-notify.sh"
+HOST="${HOSTNAME:-$(hostname)}"
+HOST="${HOST%%.*}"
 
 if [[ ! -x "$LOOGLE_NOTIFY" ]]; then
     return 0 2>/dev/null || exit 0
 fi
 
-HOST="${HOSTNAME:-$(hostname)}"
-
 if (( RC == 0 )); then
     TITLE="Backup completato"
     BODY="Backup di ${HOST} terminato con successo."
@@ -21,7 +55,19 @@ else
     SEVERITY="error"
 fi
 
-"$LOOGLE_NOTIFY" --title "$TITLE" --body "$BODY" --category raspi_backup \
+TAG="raspi_backup-${HOST}"
-    --severity "$SEVERITY" &
+SELF="$(readlink -f "${BASH_SOURCE[0]:-$0}" 2>/dev/null || echo /usr/local/bin/raspiBackup_loogle_post.sh)"
+
+# Stacca dal servizio raspiBackup (KillMode=control-group) e aspetta Casa.
+if command -v systemd-run >/dev/null 2>&1; then
+    systemd-run --quiet --collect \
+        --description="Loogle Casa raspiBackup notify ${HOST}" \
+        /bin/bash "$SELF" --wait-send "$TITLE" "$BODY" "$SEVERITY" "$TAG" \
+        || true
+else
+    nohup /bin/bash "$SELF" --wait-send "$TITLE" "$BODY" "$SEVERITY" "$TAG" \
+        >/dev/null 2>&1 &
+    disown 2>/dev/null || true
+fi
 
 return 0 2>/dev/null || exit 0

services/telegram-bot/meteo.py

@@ -17,6 +17,7 @@ from open_meteo_precip import (
     CASA_TZ,
     daily_precip_from_hourly,
     hourly_precip_mm,
+    hourly_table_should_show,
     is_casa,
 )
 
@@ -499,16 +500,15 @@ def generate_weather_report(lat, lon, location_name, debug_mode=False, cc="IT",
         day_date = dt.date()
         is_new_day = (current_day is not None and day_date != current_day)
         
-        # Determina se mostrare questo timestamp in base alla posizione nelle 48h
+        # Prime 24h: ogni ora. Dalla 25a alla 48a: ogni 2 ore, ma mai nascondere
-        # Prime 24h: ogni ora (step=1)
+        # un'ora con precipitazione (altrimenti il picco cade sulle ore dispari
-        # Dalla 25a alla 48a: ogni 2 ore (step=2)
+        # e la tabella 48h mostra 5 mm mentre Meteo7 ha 22.4 mm sul giorno).
-        if hours_from_start < 24:
+        Pr_early = get_val(l_prec[idx], 0)
-            step = 1  # Prime 24h: dettaglio 1 ora
+        Rain_early = get_val(l_rain[idx], 0)
-        else:
+        Showers_early = get_val(l_showers[idx], 0) if idx < len(l_showers) else 0
-            step = 2  # Dalla 25a alla 48a: dettaglio 2 ore
+        Code_early = int(get_val(l_code[idx], 0))
-        
+        Pr_display = hourly_precip_mm(Pr_early, Rain_early, Showers_early)
-        # Controlla se questo timestamp deve essere mostrato
+        should_show = hourly_table_should_show(hours_from_start, Pr_display, Code_early)
-        should_show = (hours_from_start % step == 0)
         
         # Se è un nuovo giorno, chiudi il blocco precedente
         if is_new_day and current_block_lines:
@@ -541,12 +541,11 @@ def generate_weather_report(lat, lon, location_name, debug_mode=False, cc="IT",
             elif diff >= 2.5: t_suffix = "H"
             t_s = f"{int(round(T))}{t_suffix}"
 
-            Pr = get_val(l_prec[idx], 0)
+            Pr = Pr_early
             Sn = get_val(l_snow[idx], 0)
-            Code = int(get_val(l_code[idx], 0))
+            Code = Code_early
-            Rain = get_val(l_rain[idx], 0)
+            Rain = Rain_early
-            Showers = get_val(l_showers[idx], 0) if idx < len(l_showers) else 0
+            Showers = Showers_early
-            Pr_display = hourly_precip_mm(Pr, Rain, Showers)
             
             # Determina se è neve
             is_snowing = Sn > 0 or (Code in [71, 73, 75, 77, 85, 86])
@@ -676,7 +675,7 @@ def generate_weather_report(lat, lon, location_name, debug_mode=False, cc="IT",
 
     legend = {
         "temp": "W=wind chill, H=heat index",
-        "precip": "G=grandine, Z=ghiacciato, N=neve",
+        "precip": "G=grandine, Z=ghiacciato, N=neve. Dalla 25ª ora: secco ogni 2h, pioggia sempre visibile",
         "cloud": "FOG=nebbia",
         "sky": "Icona condizioni (☀️🌧️⛈️…)",
         "sx": "☃️ neve · 🧊 ghiaccio · ⚡/🌪️ temporali · 🥵 caldo · ☔️ pioggia · 💨 vento forte",

services/telegram-bot/open_meteo_precip.py

@@ -41,6 +41,9 @@ ICON_DAILY_VARS = (
 
 PRECIP_HOURLY_KEYS = ("precipitation", "rain", "showers", "snowfall")
 PRECIP_DAILY_KEYS = ("precipitation_sum", "rain_sum", "showers_sum", "snowfall_sum", "precipitation_hours")
+WMO_PRECIP_CODES = frozenset(
+    list(range(51, 68)) + list(range(71, 78)) + list(range(80, 83)) + [85, 86, 95, 96, 99]
+)
 
 
 def is_casa(lat: float, lon: float, tol: float = 0.01) -> bool:
@@ -84,6 +87,61 @@ def daily_precip_from_hourly(hourly: Dict) -> Dict[str, float]:
     return dict(out)
 
 
+def daily_component_from_hourly(hourly: Dict, key: str) -> Dict[str, float]:
+    """Somma un campo orario (rain, showers, snowfall) per data locale YYYY-MM-DD."""
+    times = hourly.get("time") or []
+    arr = hourly.get(key) or []
+    out: Dict[str, float] = defaultdict(float)
+    for i, t in enumerate(times):
+        if not t or i >= len(arr) or arr[i] is None:
+            continue
+        try:
+            out[str(t)[:10]] += float(arr[i])
+        except (TypeError, ValueError):
+            continue
+    return dict(out)
+
+
+def apply_hourly_daily_precip(daily: Dict, hourly: Dict) -> Dict:
+    """Allinea i totali daily alla somma delle ore (stessa metrica della tabella oraria)."""
+    daily = dict(daily)
+    times = daily.get("time") or []
+    mapping = {
+        "precipitation_sum": daily_precip_from_hourly(hourly),
+        "rain_sum": daily_component_from_hourly(hourly, "rain"),
+        "showers_sum": daily_component_from_hourly(hourly, "showers"),
+        "snowfall_sum": daily_component_from_hourly(hourly, "snowfall"),
+    }
+    for key, totals in mapping.items():
+        arr = list(daily.get(key) or [])
+        while len(arr) < len(times):
+            arr.append(None)
+        for i, t in enumerate(times):
+            d = str(t)[:10]
+            if d in totals:
+                arr[i] = round(totals[d], 2)
+        daily[key] = arr
+    return daily
+
+
+def hourly_table_should_show(hours_from_start: int, precip_mm: float, weathercode: int = 0) -> bool:
+    """
+    Tabella 48h: prime 24 ore tutte; dalle 25 alle 48 ogni 2 ore,
+    ma un'ora con precipitazione (mm o codice WMO) non viene mai omessa.
+    """
+    if hours_from_start < 24:
+        return True
+    if hours_from_start % 2 == 0:
+        return True
+    if float(precip_mm or 0) >= 0.1:
+        return True
+    try:
+        code = int(weathercode or 0)
+    except (TypeError, ValueError):
+        code = 0
+    return code in WMO_PRECIP_CODES
+
+
 def daily_precip_sum(daily: Dict, date_str: str) -> Optional[float]:
     times = daily.get("time") or []
     arr = daily.get("precipitation_sum") or []
@@ -125,8 +183,19 @@ def fetch_icon_italia(
     return None
 
 
+def _time_key(t) -> str:
+    if not t:
+        return ""
+    return str(t).strip()[:16]
+
+
 def _index_by_time(section: Dict) -> Dict[str, int]:
-    return {str(t): i for i, t in enumerate(section.get("time") or [])}
+    out: Dict[str, int] = {}
+    for i, t in enumerate(section.get("time") or []):
+        k = _time_key(t)
+        if k:
+            out[k] = i
+    return out
 
 
 def overlay_icon_precip_on_hourly(target: Dict, icon_hourly: Dict) -> Dict:

services/telegram-bot/previsione7.py

@@ -18,7 +18,7 @@ from open_meteo_precip import (
     CASA_LAT,
     CASA_LON,
     CASA_TZ,
-    daily_precip_from_hourly,
+    apply_hourly_daily_precip,
     fetch_icon_italia,
     hourly_precip_at_index,
     hourly_precip_series,
@@ -560,6 +560,7 @@ def merge_multi_model_forecast(models_data, forecast_days=10):
             "snowfall": [],
             "snow_depth": [],
             "rain": [],
+            "showers": [],
             "weathercode": [],
             "windspeed_10m": [],
             "winddirection_10m": [],
@@ -1055,67 +1056,55 @@ def analyze_daily_events(times, codes, probs, precip, winds, temps, dewpoints, s
                 start_ice = i
                 ice_type = current_ice_condition
 
-    # 2. PRECIPITAZIONI
+    # 2. PRECIPITAZIONI — tot_mm è sempre la somma del solo blocco orario (mai il totale giorno)
+    def _precip_type_at(idx):
+        code_val = codes[idx] if idx < len(codes) and codes[idx] is not None else 0
+        t_val = temps[idx] if idx < len(temps) and temps[idx] is not None else None
+        try:
+            code_val = int(code_val) if code_val is not None else 0
+        except (ValueError, TypeError):
+            code_val = 0
+        return get_precip_type(code_val, temp=t_val)
+
+    def _emit_rain(start, end_inclusive, rain_type):
+        if end_inclusive < start:
+            return
+        block_precip = precip[start:end_inclusive + 1]
+        block_precip_clean = [p for p in block_precip if p is not None]
+        tot_mm = sum(float(p) for p in block_precip_clean)
+        if tot_mm <= 0:
+            return
+        hours_str = _format_event_hours(times, start, end_inclusive)
+        avg_intensity = tot_mm / len(block_precip) if block_precip else 0
+        events.append(
+            f"{rain_type} ({get_intensity_label(avg_intensity)}):\n"
+            f"      🕒 {hours_str} | 💧 {tot_mm:.1f}mm"
+        )
+
     in_rain = False
     start_idx = 0
     current_rain_type = ""
-    
+
     for i in range(len(times)):
         p_val = precip[i] if i < len(precip) and precip[i] is not None else 0
         is_raining = p_val >= MIN_MM_PER_EVENTO
-        
+        is_last = i == len(times) - 1
+
         if is_raining and not in_rain:
             in_rain = True
             start_idx = i
-            code_val = codes[i] if i < len(codes) and codes[i] is not None else 0
+            current_rain_type = _precip_type_at(i)
-            t_val = temps[i] if i < len(temps) and temps[i] is not None else None
+        elif in_rain and is_raining:
-            try:
+            new_type = _precip_type_at(i)
-                code_val = int(code_val) if code_val is not None else 0
-            except (ValueError, TypeError):
-                code_val = 0
-            current_rain_type = get_precip_type(code_val, temp=t_val)
-        elif in_rain and is_raining and i < len(codes):
-            code_val = codes[i] if codes[i] is not None else 0
-            t_val = temps[i] if i < len(temps) and temps[i] is not None else None
-            try:
-                code_val = int(code_val) if code_val is not None else 0
-            except (ValueError, TypeError):
-                code_val = 0
-            new_type = get_precip_type(code_val, temp=t_val)
             if new_type != current_rain_type:
-                end_inclusive = i - 1
+                _emit_rain(start_idx, i - 1, current_rain_type)
-                block_precip = precip[start_idx:i] if i <= len(precip) else precip[start_idx:]
-                block_precip_clean = [p for p in block_precip if p is not None]
-                tot_mm = sum(block_precip_clean)
-                hours_str = _format_event_hours(times, start_idx, end_inclusive)
-                avg_intensity = tot_mm / len(block_precip) if block_precip else 0
-                
-                events.append(
-                    f"{current_rain_type} ({get_intensity_label(avg_intensity)}):\n"
-                    f"      🕒 {hours_str} | 💧 {tot_mm:.1f}mm"
-                )
                 start_idx = i
                 current_rain_type = new_type
-        elif (not is_raining and in_rain) or (in_rain and i == len(times)-1):
+
+        if in_rain and (not is_raining or is_last):
+            end_inclusive = i if is_raining else i - 1
+            _emit_rain(start_idx, end_inclusive, current_rain_type)
             in_rain = False
-            if not is_raining:
-                end_inclusive = i - 1
-                end_slice = i
-            else:
-                end_inclusive = i
-                end_slice = i + 1
-            block_precip = precip[start_idx:end_slice] if end_slice <= len(precip) else precip[start_idx:]
-            block_precip_clean = [p for p in block_precip if p is not None]
-            tot_mm = sum(block_precip_clean)
-            
-            if tot_mm > 0 and end_inclusive >= start_idx:
-                hours_str = _format_event_hours(times, start_idx, end_inclusive)
-                avg_intensity = tot_mm / len(block_precip) if block_precip else 0
-                
-                events.append(
-                    f"{current_rain_type} ({get_intensity_label(avg_intensity)}):\n"
-                    f"      🕒 {hours_str} | 💧 {tot_mm:.1f}mm"
-                )
 
     # 3. VENTO
     if winds:
@@ -1249,16 +1238,7 @@ def _apply_unified_precip(hourly: Dict, daily: Dict, casa: bool) -> Tuple[Dict,
         if icon_d.get("time"):
             daily = overlay_icon_precip_on_daily(daily, icon_d)
     hourly["precipitation"] = hourly_precip_series(hourly)
-    totals = daily_precip_from_hourly(hourly)
+    daily = apply_hourly_daily_precip(daily, hourly)
-    times = daily.get("time") or []
-    psum = list(daily.get("precipitation_sum") or [])
-    while len(psum) < len(times):
-        psum.append(None)
-    for i, t in enumerate(times):
-        d = str(t)[:10]
-        if d in totals:
-            psum[i] = round(totals[d], 2)
-    daily["precipitation_sum"] = psum
     return hourly, daily
 
 
@@ -1806,27 +1786,36 @@ def format_weather_context_report(models_data, location_name, country_code, as_j
         if day_info['precip_sum'] > 0.1:
             # Caratterizza usando dati daily se disponibili
             precip_parts = []
-            
+            snow_sum = day_info.get("snowfall_sum", 0) or 0
-            # Neve (solo con aria abbastanza fredda: evita cm spurii in estate)
+            rain_sum = day_info.get("rain_sum", 0) or 0
-            if day_info.get('snowfall_sum', 0) > 0.1 and day_info['t_min'] <= ICE_EVENT_MAX_AIR_TEMP:
+            showers_sum = day_info.get("showers_sum", 0) or 0
-                precip_parts.append(f"❄️ {day_info['snowfall_sum']:.1f}cm")
+            precip_sum = day_info.get("precip_sum", 0) or 0
-            
+
-            # Pioggia
+            if snow_sum > 0.1 and day_info["t_min"] <= ICE_EVENT_MAX_AIR_TEMP:
-            if day_info.get('rain_sum', 0) > 0.1:
+                precip_parts.append(f"❄️ {snow_sum:.1f}cm")
-                precip_parts.append(f"🌧️ {day_info['rain_sum']:.1f}mm")
+
-            
+            overlapping = (
-            # Temporali (showers)
+                rain_sum > 0.1 and showers_sum > 0.1 and (
-            if day_info.get('showers_sum', 0) > 0.1:
+                    abs(rain_sum - precip_sum) < 0.25
-                precip_parts.append(f"⛈️ {day_info['showers_sum']:.1f}mm")
+                    or abs(showers_sum - precip_sum) < 0.25
-            
+                    or (rain_sum + showers_sum) > precip_sum + 0.3
-            # Se non abbiamo dati daily dettagliati, usa il tipo generale
+                )
-            if not precip_parts:
+            )
-                precip_symbol = "❄️" if day_info['precip_type'] == "snow" else "⛈️" if day_info['precip_type'] in ("hail", "thunderstorms") else "🌨️" if day_info['precip_type'] == "mixed" else "🌧️"
+            if overlapping or (rain_sum <= 0.1 and showers_sum <= 0.1):
-                precip_parts.append(f"{precip_symbol} {day_info['precip_sum']:.1f}mm")
+                if precip_sum > 0.1:
-            elif day_info['precip_sum'] > 0.1 and day_info.get('snowfall_sum', 0) > 0.1 and day_info['t_min'] > ICE_EVENT_MAX_AIR_TEMP:
+                    precip_symbol = (
-                # snowfall spurio a caldo: assicurati che l'accumulo pioggia totale sia visibile
+                        "❄️" if day_info["precip_type"] == "snow"
-                if not any("🌧️" in p or "⛈️" in p for p in precip_parts):
+                        else "⛈️" if day_info["precip_type"] in ("hail", "thunderstorms")
-                    precip_parts.append(f"🌧️ {day_info['precip_sum']:.1f}mm")
+                        else "🌨️" if day_info["precip_type"] == "mixed"
+                        else "🌧️"
+                    )
+                    if not (day_info["precip_type"] == "snow" and snow_sum > 0.1 and day_info["t_min"] <= ICE_EVENT_MAX_AIR_TEMP):
+                        precip_parts.append(f"{precip_symbol} {precip_sum:.1f}mm")
+            else:
+                if rain_sum > 0.1:
+                    precip_parts.append(f"🌧️ {rain_sum:.1f}mm")
+                if showers_sum > 0.1:
+                    precip_parts.append(f"⛈️ {showers_sum:.1f}mm")
             
             line += f" | {' + '.join(precip_parts)}"
         

services/telegram-bot/test_hourly_table_show.py

@@ -0,0 +1,86 @@
+#!/usr/bin/env python3
+"""Regressione visibilità ore nella tabella meteo 48h."""
+import sys
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).resolve().parent))
+
+from open_meteo_precip import (
+    apply_hourly_daily_precip,
+    hourly_table_should_show,
+    overlay_icon_precip_on_hourly,
+)
+
+
+def test_first_24h_all_shown():
+    for h in range(24):
+        assert hourly_table_should_show(h, 0.0, 3) is True
+
+
+def test_second_day_even_hours_shown():
+    assert hourly_table_should_show(24, 0.0, 3) is True   # lun 08
+    assert hourly_table_should_show(32, 5.0, 63) is True  # lun 16
+
+
+def test_second_day_odd_dry_hidden():
+    assert hourly_table_should_show(31, 0.0, 3) is False  # lun 15 secco
+
+
+def test_second_day_odd_wet_shown():
+    # Caso reale 17/08/2026: 15:00 = 17.4 mm (code 65) era nascosto → 48h mostrava solo 5 mm alle 16
+    assert hourly_table_should_show(31, 17.4, 65) is True
+    assert hourly_table_should_show(31, 0.0, 65) is True  # codice precip anche con mm 0
+
+
+def test_apply_hourly_daily_precip_matches_hours():
+    hourly = {
+        "time": [f"2026-08-17T{h:02d}:00" for h in range(24)],
+        "precipitation": [0.0] * 24,
+        "rain": [0.0] * 24,
+        "showers": [0.0] * 24,
+        "snowfall": [0.0] * 24,
+    }
+    hourly["rain"][15] = 17.4
+    hourly["rain"][16] = 5.0
+    hourly["precipitation"][15] = 17.4
+    hourly["precipitation"][16] = 5.0
+    daily = {
+        "time": ["2026-08-17"],
+        "precipitation_sum": [18.0],
+        "rain_sum": [18.0],
+        "showers_sum": [20.0],
+        "snowfall_sum": [0.0],
+    }
+    out = apply_hourly_daily_precip(daily, hourly)
+    assert out["precipitation_sum"][0] == 22.4
+    assert out["rain_sum"][0] == 22.4
+    assert out["showers_sum"][0] == 0.0
+
+
+def test_overlay_matches_normalized_timestamps():
+    target = {
+        "time": ["2026-08-17T15:00"],
+        "precipitation": [0.0],
+        "rain": [0.0],
+        "showers": [0.0],
+        "snowfall": [0.0],
+    }
+    icon = {
+        "time": ["2026-08-17T15:00:00"],
+        "precipitation": [17.4],
+        "rain": [17.4],
+        "showers": [0.0],
+        "snowfall": [0.0],
+    }
+    out = overlay_icon_precip_on_hourly(target, icon)
+    assert abs(out["precipitation"][0] - 17.4) < 0.01
+
+
+if __name__ == "__main__":
+    test_first_24h_all_shown()
+    test_second_day_even_hours_shown()
+    test_second_day_odd_dry_hidden()
+    test_second_day_odd_wet_shown()
+    test_apply_hourly_daily_precip_matches_hours()
+    test_overlay_matches_normalized_timestamps()
+    print("OK hourly_table_should_show")

services/telegram-bot/test_previsione7_interpretation.py

@@ -109,6 +109,62 @@ def test_real_gelicidio_cold():
     print("OK real gelicidio at subzero")
 
 
+def test_monday_storm_event_mm_is_hourly_sum():
+    """15:00=17.4 + 16:00=5.0 → un evento 22.4 mm, non 5 mm né 22.4 ripetuto."""
+    times = [f"2026-08-17T{h:02d}:00" for h in range(24)]
+    precip = [0.0] * 24
+    precip[15] = 17.4
+    precip[16] = 5.0
+    codes = [3] * 24
+    codes[15] = 65
+    codes[16] = 63
+    temps = [26.0] * 24
+    events = analyze_daily_events(
+        times, codes, None, precip, [18.0] * 24, temps, [16.0] * 24,
+        snowfalls=[0.0] * 24, rains=precip[:],
+    )
+    rain_ev = [e for e in events if "🕒" in e]
+    assert len(rain_ev) == 1, rain_ev
+    assert "15:00-17:00" in rain_ev[0]
+    assert "22.4mm" in rain_ev[0]
+    assert rain_ev[0].count("22.4mm") == 1
+    print("OK lun 17 15-17h = 22.4mm")
+
+
+def test_three_pulses_keep_own_mm_not_daily_total():
+    times = [f"2026-08-16T{h:02d}:00" for h in range(24)]
+    precip = [0.0] * 24
+    precip[10] = 18.0
+    precip[14] = 19.0
+    precip[18] = 20.0
+    events = analyze_daily_events(
+        times, [63] * 24, None, precip, [10.0] * 24, [24.0] * 24, [14.0] * 24,
+        snowfalls=[0.0] * 24, rains=precip[:],
+    )
+    rain_ev = [e for e in events if "🕒" in e]
+    assert len(rain_ev) == 3, rain_ev
+    assert "18.0mm" in rain_ev[0]
+    assert "19.0mm" in rain_ev[1]
+    assert "20.0mm" in rain_ev[2]
+    assert all("57.0mm" not in e for e in rain_ev)
+    print("OK tre fasce con mm propri")
+
+
+def test_last_hour_rain_is_emitted():
+    times = [f"2026-08-17T{h:02d}:00" for h in range(24)]
+    precip = [0.0] * 24
+    precip[23] = 4.2
+    events = analyze_daily_events(
+        times, [61] * 24, None, precip, [8.0] * 24, [20.0] * 24, [12.0] * 24,
+        snowfalls=[0.0] * 24, rains=precip[:],
+    )
+    rain_ev = [e for e in events if "🕒" in e]
+    assert rain_ev, events
+    assert "23:00-00:00" in rain_ev[0]
+    assert "4.2mm" in rain_ev[0]
+    print("OK pioggia ultima ora del giorno")
+
+
 if __name__ == "__main__":
     test_weathercode_mode_not_median()
     test_get_precip_type_temp_gate()
@@ -116,4 +172,7 @@ if __name__ == "__main__":
     test_single_hour_event_range()
     test_trend_max_min_not_media()
     test_real_gelicidio_cold()
+    test_monday_storm_event_mm_is_hourly_sum()
+    test_three_pulses_keep_own_mm_not_daily_total()
+    test_last_hour_rain_is_emitted()
     print("\nAll interpretation regression checks passed.")