"""Experience temperature for iot_panel (not HSI).

Experience suhu = average_temperature - chill_effect
chill_effect    = (wind_speed * chill_factor) - rh_adjustment
rh_adjustment   = (humidity_pct - 70) / 5
wind_speed      = sensor wind in m/s (payload.data.wind / 10 when stored in tenths)

Chill factor is linearly interpolated from bird age (days).
"""

from __future__ import annotations

CHILL_FACTOR_POINTS = (
    (0, 8.0),
    (1, 8.0),
    (7, 7.0),
    (14, 6.0),
    (21, 4.5),
    (28, 3.5),
    (35, 3.5),
    (42, 3.0),
)


def sensor_celsius(sensor: dict | float | int | None) -> float | None:
    if sensor is None:
        return None
    if isinstance(sensor, (int, float)):
        return float(sensor)
    raw = sensor.get("value")
    if raw is None:
        return None
    cal = float(sensor.get("calibration") or 0)
    return (float(raw) + cal) / 10.0


def sensor_humidity_pct(sensor: dict | float | int | None, fallback: float | None) -> float:
    if isinstance(sensor, dict):
        raw = sensor.get("value")
        if raw is not None:
            cal = float(sensor.get("calibration") or 0)
            return (float(raw) + cal) / 10.0
    if isinstance(sensor, (int, float)):
        return float(sensor)
    if fallback is None:
        return 70.0
    value = float(fallback)
    return value / 10.0 if value > 100 else value


def wind_ms(payload_wind: float | int | None, sensors_wind: dict | float | int | None) -> float:
    """Use measured wind directly (not kipas aktif × 0.35)."""
    if isinstance(sensors_wind, dict) and sensors_wind.get("value") is not None:
        return float(sensors_wind["value"]) / 10.0
    if isinstance(sensors_wind, (int, float)):
        return float(sensors_wind)
    if payload_wind is None:
        return 0.0
    return float(payload_wind) / 10.0


def average_inside_temp_c(sensors: dict | None, actual_temperature: float | int | None) -> float:
    if sensors:
        readings = [
            v
            for v in (
                sensor_celsius(sensors.get("temperature1")),
                sensor_celsius(sensors.get("temperature2")),
                sensor_celsius(sensors.get("temperature3")),
            )
            if v is not None
        ]
        if readings:
            return sum(readings) / len(readings)
    if actual_temperature is None:
        return 0.0
    value = float(actual_temperature)
    return value / 10.0 if value > 100 else value


def chicken_chill_factor(age: float) -> float:
    if age <= CHILL_FACTOR_POINTS[0][0]:
        return CHILL_FACTOR_POINTS[0][1]
    for idx in range(1, len(CHILL_FACTOR_POINTS)):
        prev_age, prev_factor = CHILL_FACTOR_POINTS[idx - 1]
        next_age, next_factor = CHILL_FACTOR_POINTS[idx]
        if age > next_age:
            continue
        span = next_age - prev_age
        if span <= 0:
            return next_factor
        progress = (age - prev_age) / span
        return prev_factor + (next_factor - prev_factor) * progress
    return CHILL_FACTOR_POINTS[-1][1]


def experience_temperature(
    *,
    average_temperature: float,
    wind_speed: float,
    humidity_pct: float,
    age_days: float,
) -> float:
    chill_factor = chicken_chill_factor(age_days)
    rh_adjustment = (humidity_pct - 70.0) / 5.0
    chill_effect = wind_speed * chill_factor - rh_adjustment
    return average_temperature - chill_effect


def panel_fields_from_payload(data: dict, age_days: int) -> dict:
    sensors = data.get("sensors") or {}
    humidity = sensor_humidity_pct(sensors.get("humidity"), data.get("humidity"))
    wind_speed = wind_ms(data.get("wind"), sensors.get("wind"))
    avg_temp = average_inside_temp_c(sensors, data.get("actualTemperature"))
    water = data.get("water")
    if water is None and isinstance(sensors.get("water"), dict):
        water = sensors["water"].get("value")
    return {
        "wind_speed": round(wind_speed, 4),
        "humidity": round(humidity, 4),
        "water_total": float(water or 0),
        "average_temperature": round(avg_temp, 4),
        "experience_temperature": round(
            experience_temperature(
                average_temperature=avg_temp,
                wind_speed=wind_speed,
                humidity_pct=humidity,
                age_days=age_days,
            ),
            4,
        ),
        "chill_factor": round(chicken_chill_factor(age_days), 4),
    }


# Lantai 2 has no device in the public flocks API. Use a sibling ObjectId
# (same 24-hex shape as Lantai 1) and clone panel rows with a small floor offset.
LANTAI_1_IOT_FLOCK_ID = "686df69f407b21002da8750c"
LANTAI_2_IOT_FLOCK_ID = "686df69f407b21002da8750d"

LANTAI_2_ADJUST = {
    "wind_speed_delta": -0.05,
    "humidity_delta": 1.2,
    "average_temperature_delta": -0.3,
    "water_total_factor": 0.96,
}


def clone_lantai2_panel_row(row: dict) -> dict:
    """Copy a Lantai 1 daily panel row onto Lantai 2, then recompute experience suhu."""
    age = int(row["age"])
    wind = max(0.0, float(row["wind_speed"]) + LANTAI_2_ADJUST["wind_speed_delta"])
    humidity = min(100.0, max(0.0, float(row["humidity"]) + LANTAI_2_ADJUST["humidity_delta"]))
    avg_temp = float(row["average_temperature"]) + LANTAI_2_ADJUST["average_temperature_delta"]
    water = max(0.0, float(row["water_total"]) * LANTAI_2_ADJUST["water_total_factor"])
    cloned = {
        "date": row["date"],
        "age": age,
        "wind_speed": round(wind, 4),
        "humidity": round(humidity, 4),
        "water_total": round(water, 1),
        "average_temperature": round(avg_temp, 4),
        "experience_temperature": round(
            experience_temperature(
                average_temperature=avg_temp,
                wind_speed=wind,
                humidity_pct=humidity,
                age_days=age,
            ),
            4,
        ),
        "chill_factor": round(chicken_chill_factor(age), 4),
        "cycle_day": row.get("cycle_day"),
    }
    return cloned