from __future__ import annotations

import os

import pandas as pd

from ..ingest import TOPIC_USBL
from ..models import Anomaly
from .base import Rule


class UsblSnrLowRule(Rule):
    """Fire when SNR stays below threshold for `consec` consecutive samples."""

    name = "usbl_snr_low"
    topic = TOPIC_USBL
    severity = "warn"

    def __init__(
        self,
        subject: str = "AUV000",
        min_snr_db: float | None = None,
        consec: int = 3,
    ) -> None:
        super().__init__(subject)
        if min_snr_db is None:
            min_snr_db = float(os.environ.get("USBL_SNR_LOW", 5.0))
        self.min_snr_db = min_snr_db
        self.consec = consec

    def detect(self, df: pd.DataFrame) -> list[Anomaly]:
        if df.empty or len(df) < self.consec:
            return []
        low = df["snr_db"] < self.min_snr_db
        run = low.astype(int).groupby((~low).cumsum()).cumsum()
        anomalies: list[Anomaly] = []
        fired_run = -1
        runs_id = (~low).cumsum()
        for idx in df.index:
            if run.iloc[idx] >= self.consec and runs_id.iloc[idx] != fired_run:
                fired_run = int(runs_id.iloc[idx])
                anomalies.append(
                    self._make(
                        ts=float(df.at[idx, "ts"]),
                        value=float(df.at[idx, "snr_db"]),
                        context={
                            "min_snr_db": self.min_snr_db,
                            "consec": self.consec,
                        },
                    )
                )
        return anomalies