"""IMU-only fallback drift evaluator for NFT-RES-01 (AZ-432 / AC-3.5 + AC-NEW-7).

A pure-vision-blackout (no spoof) lasting 30 s is injected by
``fixtures/injectors/blackout_spoof.py --no-spoof``. The SUT must
fall back to IMU-only dead reckoning. AC-3.5 + AC-NEW-7 prescribe two
drift budgets at the end of the blackout, depending on whether the
CombinedImuFactor (PreintegratedCombinedMeasurements) is active:

* sub-case (a) — no good IMU → ``drift ≤ NO_IMU_BUDGET_M`` (100 m).
* sub-case (b) — CombinedImuFactor active (SUT default config) →
  ``drift ≤ GOOD_IMU_BUDGET_M`` (50 m).

Drift is the Vincenty distance between the SUT's last estimate at
blackout end and the ground-truth position at the same timestamp.

The scenario test owns the orchestration (window injection,
sub-case selection, fixture loading). This module owns the pure
arithmetic + CSV evidence.

Public-boundary discipline: does NOT import any
``src/gps_denied_onboard`` symbol; consumes only typed samples that
the scenario adapter projects out of the boundary observers.
"""

from __future__ import annotations

import csv
from dataclasses import dataclass
from pathlib import Path
from typing import Iterable, Sequence

from .geo import distance_m

# AC-2 / AC-3
NO_IMU_BUDGET_M = 100.0
GOOD_IMU_BUDGET_M = 50.0
# AC-1 — accept windows within ±2 s of the nominal 30 s.
WINDOW_NOMINAL_S = 30.0
WINDOW_TOLERANCE_S = 2.0

SUBCASE_NO_IMU = "no_imu"
SUBCASE_GOOD_IMU = "good_imu_combined_factor"
ALLOWED_SUBCASES = (SUBCASE_NO_IMU, SUBCASE_GOOD_IMU)


@dataclass(frozen=True)
class PositionSample:
    """One WGS84 sample tagged with a monotonic-ms timestamp.

    Used for both the SUT's outbound estimate stream and the ground-truth
    track. Both streams must share the same monotonic clock so the
    scenario can pick the "at blackout end" sample by interpolation /
    nearest-neighbour lookup.
    """

    monotonic_ms: int
    lat_deg: float
    lon_deg: float


@dataclass(frozen=True)
class BlackoutWindow:
    """The injector-emitted window the evaluator is bound to."""

    onset_monotonic_ms: int
    end_monotonic_ms: int

    @property
    def duration_s(self) -> float:
        return (self.end_monotonic_ms - self.onset_monotonic_ms) / 1000.0

    @property
    def window_in_spec(self) -> bool:
        """AC-1: window duration must be within ±2 s of nominal 30 s."""
        return abs(self.duration_s - WINDOW_NOMINAL_S) <= WINDOW_TOLERANCE_S


@dataclass(frozen=True)
class SubCaseReport:
    """Drift result for a single sub-case (no_imu / good_imu)."""

    subcase: str
    drift_m: float | None
    budget_m: float
    estimate_at_end: PositionSample | None
    gt_at_end: PositionSample | None

    @property
    def passes(self) -> bool:
        return self.drift_m is not None and self.drift_m <= self.budget_m


@dataclass(frozen=True)
class ImuFallbackReport:
    """Aggregate NFT-RES-01 result for one parameterization."""

    window: BlackoutWindow
    sub_cases: tuple[SubCaseReport, ...]

    @property
    def passes_window(self) -> bool:
        return self.window.window_in_spec

    @property
    def passes(self) -> bool:
        return self.passes_window and all(s.passes for s in self.sub_cases)

    def by_subcase(self, subcase: str) -> SubCaseReport:
        for s in self.sub_cases:
            if s.subcase == subcase:
                return s
        raise KeyError(f"sub-case {subcase!r} not present in report")


def _pick_at_or_before(
    samples: Sequence[PositionSample], t_ms: int
) -> PositionSample | None:
    """Return the latest sample with ``monotonic_ms ≤ t_ms`` (None if none qualify).

    Tests against the closest sample on the "left" of the boundary —
    drift evaluation must NOT extrapolate past the captured window.
    """
    chosen: PositionSample | None = None
    for s in samples:
        if s.monotonic_ms <= t_ms:
            if chosen is None or s.monotonic_ms > chosen.monotonic_ms:
                chosen = s
    return chosen


def evaluate_subcase(
    window: BlackoutWindow,
    estimates: Sequence[PositionSample],
    ground_truth: Sequence[PositionSample],
    *,
    subcase: str,
    budget_m: float | None = None,
) -> SubCaseReport:
    """Compute drift for one sub-case.

    `subcase` selects the budget when `budget_m` is omitted: 100 m for
    ``no_imu``, 50 m for ``good_imu_combined_factor``. Unknown sub-case
    names raise ``ValueError`` so a typo at the call site fails loud
    instead of silently relaxing the budget.
    """
    if subcase not in ALLOWED_SUBCASES:
        raise ValueError(
            f"subcase must be one of {ALLOWED_SUBCASES}; got {subcase!r}"
        )
    if budget_m is None:
        budget_m = (
            NO_IMU_BUDGET_M if subcase == SUBCASE_NO_IMU else GOOD_IMU_BUDGET_M
        )
    estimate_end = _pick_at_or_before(estimates, window.end_monotonic_ms)
    gt_end = _pick_at_or_before(ground_truth, window.end_monotonic_ms)
    drift: float | None
    if estimate_end is None or gt_end is None:
        drift = None
    else:
        drift = distance_m(
            estimate_end.lat_deg,
            estimate_end.lon_deg,
            gt_end.lat_deg,
            gt_end.lon_deg,
        )
    return SubCaseReport(
        subcase=subcase,
        drift_m=drift,
        budget_m=budget_m,
        estimate_at_end=estimate_end,
        gt_at_end=gt_end,
    )


def evaluate(
    window: BlackoutWindow,
    *,
    sub_cases: Iterable[tuple[str, Sequence[PositionSample], Sequence[PositionSample]]],
) -> ImuFallbackReport:
    """Compute the aggregate report across multiple sub-cases.

    Each tuple is ``(subcase_name, estimates, ground_truth)``. The
    evaluator does not require both sub-cases to be present — a scenario
    that can only exercise one path still gets a partial report whose
    ``passes`` is False (because the missing sub-case has no drift).
    """
    reports: list[SubCaseReport] = []
    for subcase, estimates, ground_truth in sub_cases:
        reports.append(evaluate_subcase(window, estimates, ground_truth, subcase=subcase))
    return ImuFallbackReport(window=window, sub_cases=tuple(reports))


def write_csv_evidence(out_path: Path, report: ImuFallbackReport) -> Path:
    """Aggregate-summary CSV (one row per sub-case)."""
    out_path.parent.mkdir(parents=True, exist_ok=True)
    with out_path.open("w", newline="") as fh:
        writer = csv.writer(fh)
        writer.writerow(
            [
                "subcase",
                "window_duration_s",
                "window_in_spec",
                "drift_m",
                "budget_m",
                "estimate_end_lat",
                "estimate_end_lon",
                "gt_end_lat",
                "gt_end_lon",
                "passes",
            ]
        )
        for sub in report.sub_cases:
            writer.writerow(
                [
                    sub.subcase,
                    f"{report.window.duration_s:.3f}",
                    "true" if report.passes_window else "false",
                    "" if sub.drift_m is None else f"{sub.drift_m:.3f}",
                    f"{sub.budget_m:.3f}",
                    "" if sub.estimate_at_end is None else f"{sub.estimate_at_end.lat_deg:.7f}",
                    "" if sub.estimate_at_end is None else f"{sub.estimate_at_end.lon_deg:.7f}",
                    "" if sub.gt_at_end is None else f"{sub.gt_at_end.lat_deg:.7f}",
                    "" if sub.gt_at_end is None else f"{sub.gt_at_end.lon_deg:.7f}",
                    "true" if sub.passes else "false",
                ]
            )
    return out_path