gendesign/tradein-mvp/backend/tests/test_estimator_quarter_index.py

"""Unit tests for #764 — per-cadastral-quarter price index gap-correction.

Tests покрывают:
  - _quarter_from_cadastre: парсинг кадастрового номера в квартал
  - _apply_quarter_index: чистая математика корректировки (без БД)
  - _lookup_quarter_index: DB-хелпер с мокнутой Session
  - Guard-1: anchor_tier не None → no-op (same-building anchor)
  - Guard-1b: IMV-blended → no-op
  - Guard-2: >0.6 аналогов в целевом квартале → no-op
  - Sparse fallback: нет строки / n_deals < min_n → no-op
  - Bimodal guard: price_index>2.0 AND n_deals<50 → no-op
  - Flag off → точное старое поведение

Паттерн: os.environ.setdefault перед импортом (как test_estimator_pure_units.py).
Чистые хелперы — без БД. DB-хелпер — мокнутая Session.
estimate_quality-level тесты — через anyio.run + полный stub-пач всех I/O.
"""

from __future__ import annotations

import os
from typing import Any
from unittest.mock import AsyncMock, MagicMock, patch

os.environ.setdefault("DATABASE_URL", "postgresql+psycopg://test:test@localhost:5432/test")

import anyio
import pytest

from app.services.estimator import (
    _apply_quarter_index,
    _lookup_quarter_index,
    _lookup_quarter_indexes,
    _quarter_from_cadastre,
)

# ─────────────────────────────────────────────────────────────────────────────
# _quarter_from_cadastre
# ─────────────────────────────────────────────────────────────────────────────


def test_quarter_from_cadastre_standard() -> None:
    """Нормальный кадастровый номер дома → квартал (первые три части)."""
    assert _quarter_from_cadastre("66:41:0204016:350") == "66:41:0204016"


def test_quarter_from_cadastre_7digit_block() -> None:
    """7-значный блок квартала → корректно."""
    assert _quarter_from_cadastre("66:41:0401017:100") == "66:41:0401017"


def test_quarter_from_cadastre_none_input() -> None:
    assert _quarter_from_cadastre(None) is None


def test_quarter_from_cadastre_empty_string() -> None:
    assert _quarter_from_cadastre("") is None


def test_quarter_from_cadastre_too_few_parts() -> None:
    assert _quarter_from_cadastre("66:41") is None


def test_quarter_from_cadastre_non_numeric_third_part() -> None:
    """Третья часть не числовая → None (не кадастровый квартал)."""
    assert _quarter_from_cadastre("66:41:BADDATA:100") is None


def test_quarter_from_cadastre_no_fourth_part() -> None:
    """Три части без объекта — само по себе квартал: возвращаем как есть."""
    result = _quarter_from_cadastre("66:41:0204016")
    assert result == "66:41:0204016"


# ─────────────────────────────────────────────────────────────────────────────
# _apply_quarter_index — чистая математика
# ─────────────────────────────────────────────────────────────────────────────


def test_apply_quarter_index_basic_math() -> None:
    """Базовый кейс: target_index=1.2, avg_analog=1.0 → factor=1.2."""
    ppm2, median, low, high, factor = _apply_quarter_index(
        base_median_ppm2=100_000.0,
        base_median_price=5_000_000,
        base_range_low=4_000_000,
        base_range_high=6_000_000,
        target_index=1.2,
        avg_analog_index=1.0,
    )
    assert abs(factor - 1.2) < 1e-9
    assert abs(ppm2 - 120_000.0) < 1.0
    assert median == round(5_000_000 * 1.2)
    assert low == round(4_000_000 * 1.2)
    assert high == round(6_000_000 * 1.2)


def test_apply_quarter_index_gap_correction() -> None:
    """Gap-correction: target=1.3, avg_analog=1.1 → factor=1.3/1.1 ≈ 1.182."""
    _, median, _, _, factor = _apply_quarter_index(
        base_median_ppm2=200_000.0,
        base_median_price=10_000_000,
        base_range_low=8_000_000,
        base_range_high=12_000_000,
        target_index=1.3,
        avg_analog_index=1.1,
    )
    expected_factor = 1.3 / 1.1
    assert abs(factor - expected_factor) < 1e-9
    assert median == round(10_000_000 * expected_factor)


def test_apply_quarter_index_same_quarter_noop() -> None:
    """target_index == avg_analog_index → factor=1.0, медиана не меняется."""
    _, median, low, high, factor = _apply_quarter_index(
        base_median_ppm2=150_000.0,
        base_median_price=7_500_000,
        base_range_low=6_000_000,
        base_range_high=9_000_000,
        target_index=1.05,
        avg_analog_index=1.05,
    )
    assert abs(factor - 1.0) < 1e-9
    assert median == 7_500_000
    assert low == 6_000_000
    assert high == 9_000_000


def test_apply_quarter_index_downcorrection() -> None:
    """target_index < avg_analog_index → factor < 1.0 (коррекция вниз тоже работает)."""
    _, median, _, _, factor = _apply_quarter_index(
        base_median_ppm2=100_000.0,
        base_median_price=5_000_000,
        base_range_low=4_000_000,
        base_range_high=6_000_000,
        target_index=0.9,
        avg_analog_index=1.0,
    )
    assert factor < 1.0
    assert median == round(5_000_000 * 0.9)


# ─────────────────────────────────────────────────────────────────────────────
# _lookup_quarter_index — мокнутая Session
# ─────────────────────────────────────────────────────────────────────────────


def test_lookup_quarter_index_returns_row() -> None:
    """Нормальная строка → возвращает (price_index, n_deals)."""
    mock_db = MagicMock()
    mock_db.execute.return_value.mappings.return_value.first.return_value = {
        "price_index": 1.25,
        "n_deals": 42,
    }
    result = _lookup_quarter_index(mock_db, quarter_cad_number="66:41:0204016", min_n_deals=10)
    assert result is not None
    qi, n = result
    assert abs(qi - 1.25) < 1e-9
    assert n == 42


def test_lookup_quarter_index_none_when_no_row() -> None:
    """Нет строки → None."""
    mock_db = MagicMock()
    mock_db.execute.return_value.mappings.return_value.first.return_value = None
    result = _lookup_quarter_index(mock_db, quarter_cad_number="66:41:9999999", min_n_deals=10)
    assert result is None


def test_lookup_quarter_index_fdw_exception_graceful() -> None:
    """FDW exception → None (graceful, no re-raise)."""
    mock_db = MagicMock()
    mock_db.execute.side_effect = RuntimeError("FDW connection refused")
    result = _lookup_quarter_index(mock_db, quarter_cad_number="66:41:0204016", min_n_deals=10)
    assert result is None


def test_lookup_quarter_index_no_cast_colon_colon_in_sql() -> None:
    """SQL текст хелпера не должен содержать :x::type (psycopg v3 rule)."""
    mock_db = MagicMock()
    mock_db.execute.return_value.mappings.return_value.first.return_value = None
    _lookup_quarter_index(mock_db, quarter_cad_number="66:41:0204016", min_n_deals=10)
    args, _ = mock_db.execute.call_args
    sql_text = str(args[0])
    # psycopg v3: CAST(:x AS type), never :x::type
    import re

    assert not re.search(r":[a-z_]+::[a-z]", sql_text), f"::type cast found in SQL: {sql_text}"


# ─────────────────────────────────────────────────────────────────────────────
# _lookup_quarter_indexes (plural) — батч-хелпер
# ─────────────────────────────────────────────────────────────────────────────


def test_lookup_quarter_indexes_returns_dict() -> None:
    """Нормальный результат → словарь {quarter: price_index}."""
    mock_db = MagicMock()
    mock_db.execute.return_value.mappings.return_value.all.return_value = [
        {"quarter_cad_number": "66:41:0204016", "price_index": 1.25},
        {"quarter_cad_number": "66:41:9998888", "price_index": 0.95},
    ]
    result = _lookup_quarter_indexes(
        mock_db,
        quarter_cad_numbers=["66:41:0204016", "66:41:9998888"],
        min_n_deals=10,
    )
    assert result == {"66:41:0204016": 1.25, "66:41:9998888": 0.95}


def test_lookup_quarter_indexes_empty_input_returns_empty() -> None:
    """Пустой список кварталов → {} без обращения к БД."""
    mock_db = MagicMock()
    result = _lookup_quarter_indexes(mock_db, quarter_cad_numbers=[], min_n_deals=10)
    assert result == {}
    mock_db.execute.assert_not_called()


def test_lookup_quarter_indexes_fdw_exception_returns_empty() -> None:
    """FDW exception → {} (graceful, no re-raise)."""
    mock_db = MagicMock()
    mock_db.execute.side_effect = RuntimeError("FDW connection refused")
    result = _lookup_quarter_indexes(
        mock_db,
        quarter_cad_numbers=["66:41:0204016"],
        min_n_deals=10,
    )
    assert result == {}


def test_lookup_quarter_indexes_deduplicates_input() -> None:
    """Дублирующиеся кварталы в списке — передаются в БД без дублей."""
    mock_db = MagicMock()
    mock_db.execute.return_value.mappings.return_value.all.return_value = [
        {"quarter_cad_number": "66:41:0204016", "price_index": 1.1},
    ]
    _lookup_quarter_indexes(
        mock_db,
        quarter_cad_numbers=["66:41:0204016", "66:41:0204016", "66:41:0204016"],
        min_n_deals=5,
    )
    passed_params = mock_db.execute.call_args[0][1]
    assert passed_params["quarters"] == ["66:41:0204016"]


def test_lookup_quarter_indexes_no_cast_colon_colon_in_sql() -> None:
    """Батч-хелпер: SQL не содержит :x::type (psycopg v3 rule)."""
    import re

    mock_db = MagicMock()
    mock_db.execute.return_value.mappings.return_value.all.return_value = []
    _lookup_quarter_indexes(
        mock_db,
        quarter_cad_numbers=["66:41:0204016"],
        min_n_deals=10,
    )
    args, _ = mock_db.execute.call_args
    sql_text = str(args[0])
    assert not re.search(r":[a-z_]+::[a-z]", sql_text), f"::type cast found in SQL: {sql_text}"


def test_lookup_quarter_indexes_uses_any_cast_array_idiom() -> None:
    """SQL батч-хелпера содержит ANY(CAST(:quarters AS varchar[])) — pgpsycopg3 idiom."""
    mock_db = MagicMock()
    mock_db.execute.return_value.mappings.return_value.all.return_value = []
    _lookup_quarter_indexes(
        mock_db,
        quarter_cad_numbers=["66:41:0204016"],
        min_n_deals=10,
    )
    args, _ = mock_db.execute.call_args
    sql_text = str(args[0])
    assert "ANY(CAST(:quarters AS varchar[]))" in sql_text


def test_lookup_quarter_indexes_multi_quarter_factor_matches_single() -> None:
    """Батч возвращает те же значения, что N одиночных вызовов — математика идентична.

    Аналоги: 2 лота из квартала A (index=1.2, ppm2=100k),
             1 лот из квартала B (index=0.8, ppm2=200k).
    Ожидаемый avg_analog_index = (100k*1.2 + 100k*1.2 + 200k*0.8) / (100k+100k+200k)
                                = (120k + 120k + 160k) / 400k = 400k/400k = 1.0.
    """
    index_map = {"66:41:AAAAAAA": 1.2, "66:41:BBBBBBB": 0.8}
    analog_lots = [
        ("66:41:AAAAAAA", 100_000.0),
        ("66:41:AAAAAAA", 100_000.0),
        ("66:41:BBBBBBB", 200_000.0),
    ]
    weighted_sum = sum(ppm2 * index_map[q] for q, ppm2 in analog_lots)
    weight_total = sum(ppm2 for _, ppm2 in analog_lots)
    avg_analog_index = weighted_sum / weight_total
    assert abs(avg_analog_index - 1.0) < 1e-9, f"Expected 1.0, got {avg_analog_index}"


# ─────────────────────────────────────────────────────────────────────────────
# Helpers for estimate_quality integration tests (full I/O stub)
# ─────────────────────────────────────────────────────────────────────────────

_BASE_PPM2 = 150_000.0
_AREA = 40.0


def _make_listing_qi(
    *,
    price_per_m2: float = _BASE_PPM2,
    area_m2: float = _AREA,
    building_cadastral_number: str | None = None,
) -> dict[str, Any]:
    from datetime import UTC, datetime

    price_rub = price_per_m2 * area_m2
    return {
        "source": "cian",
        "source_url": "https://cian.ru/offer/1",
        "address": "ЕКБ, ул. Тестовая, 5",
        "lat": 56.838,
        "lon": 60.595,
        "rooms": 1,
        "area_m2": area_m2,
        "floor": 4,
        "total_floors": 16,
        "price_rub": price_rub,
        "price_per_m2": price_per_m2,
        "listing_date": datetime(2026, 5, 1),
        "days_on_market": 10,
        "photo_urls": [],
        "scraped_at": datetime(2026, 5, 20, tzinfo=UTC),
        "distance_m": 100.0,
        "relevance_score": 0.1,
        "building_cadastral_number": building_cadastral_number,
    }


def _make_fake_geo_qi():
    from app.services.geocoder import GeocodeResult

    return GeocodeResult(
        lat=56.838,
        lon=60.595,
        full_address="Свердловская обл., Екатеринбург, ул. Тестовая, 5",
        provider="nominatim",
    )


def _make_payload_qi(rooms: int = 1, area_m2: float = _AREA):
    from app.schemas.trade_in import TradeInEstimateInput

    return TradeInEstimateInput(
        address="ЕКБ, ул. Тестовая, 5",
        area_m2=area_m2,
        rooms=rooms,
        floor=4,
        total_floors=16,
    )


def _make_fake_dadata(house_cadnum: str | None):
    """Minimal DadataAddressResult stub с нужным house_cadnum."""
    from app.services.dadata import DadataAddressResult

    return DadataAddressResult(
        canonical_address="Свердловская обл., Екатеринбург, ул. Тестовая, 5",
        house_cadnum=house_cadnum,
        house_fias_id=None,
        lat=56.838,
        lon=60.595,
        qc_geo=1,
        qc_house=1,
        kladr_id=None,
        okato=None,
        oktmo=None,
        metro=[],
        raw={},
    )


def _run_estimate_qi(
    analogs: list[dict[str, Any]],
    dadata_cadnum: str | None,
    qi_lookup_result: tuple[float, int] | None,
    *,
    anchor_tier_override: str | None = None,
):
    """Запускает estimate_quality с полным stub-пачем I/O; возвращает AggregatedEstimate."""
    from app.services.estimator import estimate_quality

    db = MagicMock()
    payload = _make_payload_qi()

    dadata_obj = _make_fake_dadata(dadata_cadnum) if dadata_cadnum is not None else None

    # Батч-хелпер возвращает словарь: для каждого переданного квартала — тот же индекс,
    # что qi_lookup_result[0], если qi_lookup_result не None; иначе пустой dict.
    def _fake_lookup_indexes(db_arg, *, quarter_cad_numbers, min_n_deals):
        if qi_lookup_result is None:
            return {}
        return {q: qi_lookup_result[0] for q in quarter_cad_numbers}

    async def _run():
        with (
            patch(
                "app.services.estimator.geocode",
                new=AsyncMock(return_value=_make_fake_geo_qi()),
            ),
            patch(
                "app.services.estimator.dadata_clean_address",
                new=AsyncMock(return_value=dadata_obj),
            ),
            patch("app.services.estimator.match_house_readonly", return_value=None),
            patch("app.services.estimator.get_house_metadata", new=AsyncMock(return_value=None)),
            patch(
                "app.services.estimator._fetch_analogs",
                return_value=(list(analogs), False, "W"),
            ),
            patch("app.services.estimator._fetch_deals", return_value=[]),
            patch("app.services.estimator._fetch_dkp_corridor", return_value=None),
            patch(
                "app.services.estimator._get_or_fetch_imv_cached",
                new=AsyncMock(return_value=None),
            ),
            patch(
                "app.services.estimator._get_or_fetch_yandex_valuation_cached",
                new=AsyncMock(return_value=None),
            ),
            patch(
                "app.services.estimator.estimate_via_cian_valuation",
                new=AsyncMock(return_value=None),
            ),
            patch(
                "app.services.estimator._get_asking_sold_ratio",
                return_value=(None, None),
            ),
            patch("app.services.estimator._fetch_house_imv_anchor", return_value=None),
            # Stub singular target-quarter lookup
            patch(
                "app.services.estimator._lookup_quarter_index",
                return_value=qi_lookup_result,
            ),
            # Stub batched analog-quarter lookup
            patch(
                "app.services.estimator._lookup_quarter_indexes",
                side_effect=_fake_lookup_indexes,
            ),
        ):
            return await estimate_quality(payload, db)

    return anyio.run(_run)


# ─────────────────────────────────────────────────────────────────────────────
# Integration: gap-correction applied in pure-radius path
# ─────────────────────────────────────────────────────────────────────────────

_OTHER_QUARTER = "66:41:9998888"
_TARGET_QUARTER = "66:41:0204016"

_ANALOGS_OTHER_QUARTER = [
    _make_listing_qi(
        price_per_m2=_BASE_PPM2,
        building_cadastral_number=f"{_OTHER_QUARTER}:100",
    )
    for _ in range(3)
]


def test_quarter_index_correction_applied() -> None:
    """Gap-correction срабатывает в pure-radius пути.

    target_index=1.2, avg_analog_index=1.0 (аналоги без известного квартала →
    avg=1.0) → factor=1.2 → median должен вырасти на ×1.2.
    """
    base_median = round(_BASE_PPM2 * _AREA)  # 6_000_000

    # Аналоги из ДРУГОГО квартала (building_cadastral_number = OTHER_QUARTER:100)
    # _lookup_quarter_index для аналогов вернёт тот же (1.2, 30) что и для target —
    # avg_analog_index = 1.2, factor = 1.2/1.2 = 1.0 (no change!).
    # Чтобы увидеть ненулевую коррекцию, делаем аналоги БЕЗ кадастрового номера
    # → avg_analog_index = 1.0 → factor = 1.2.
    analogs_no_cadnum = [
        _make_listing_qi(price_per_m2=_BASE_PPM2, building_cadastral_number=None) for _ in range(3)
    ]
    est = _run_estimate_qi(
        analogs=analogs_no_cadnum,
        dadata_cadnum=f"{_TARGET_QUARTER}:350",
        qi_lookup_result=(1.2, 30),
    )
    expected_median = round(base_median * 1.2)
    assert est.median_price_rub == expected_median
    # Disclosure должна содержать упоминание квартала
    assert est.confidence_explanation is not None
    assert "квартал" in est.confidence_explanation.lower()


# ─────────────────────────────────────────────────────────────────────────────
# Guard-2: >0.6 аналогов в целевом квартале → no-op
# ─────────────────────────────────────────────────────────────────────────────


def test_guard2_skip_when_majority_analogs_in_target_quarter() -> None:
    """Guard-2: >60% аналогов из целевого квартала → индекс не применяется."""
    # 4 аналога в target квартале, 1 в другом → ratio = 4/5 = 0.8 > 0.6 → skip
    target_cadnum = f"{_TARGET_QUARTER}:100"
    other_cadnum = f"{_OTHER_QUARTER}:100"
    analogs = [
        _make_listing_qi(price_per_m2=_BASE_PPM2, building_cadastral_number=target_cadnum),
        _make_listing_qi(price_per_m2=_BASE_PPM2, building_cadastral_number=target_cadnum),
        _make_listing_qi(price_per_m2=_BASE_PPM2, building_cadastral_number=target_cadnum),
        _make_listing_qi(price_per_m2=_BASE_PPM2, building_cadastral_number=target_cadnum),
        _make_listing_qi(price_per_m2=_BASE_PPM2, building_cadastral_number=other_cadnum),
    ]
    base_median = round(_BASE_PPM2 * _AREA)
    est = _run_estimate_qi(
        analogs=analogs,
        dadata_cadnum=f"{_TARGET_QUARTER}:350",
        qi_lookup_result=(1.5, 30),  # high index — but guard-2 should skip
    )
    # Медиана НЕ должна изменяться
    assert est.median_price_rub == base_median


# ─────────────────────────────────────────────────────────────────────────────
# Sparse fallback: нет строки → no-op
# ─────────────────────────────────────────────────────────────────────────────


def test_sparse_fallback_no_row_noop() -> None:
    """_lookup_quarter_index вернул None → no-op, медиана не меняется."""
    analogs_no_cadnum = [
        _make_listing_qi(price_per_m2=_BASE_PPM2, building_cadastral_number=None) for _ in range(3)
    ]
    base_median = round(_BASE_PPM2 * _AREA)
    est = _run_estimate_qi(
        analogs=analogs_no_cadnum,
        dadata_cadnum=f"{_TARGET_QUARTER}:350",
        qi_lookup_result=None,  # sparse
    )
    assert est.median_price_rub == base_median


# ─────────────────────────────────────────────────────────────────────────────
# Bimodal guard: price_index>2.0 AND n_deals<50 → no-op
# ─────────────────────────────────────────────────────────────────────────────


def test_bimodal_guard_skips_high_index_small_n() -> None:
    """Bimodal guard: price_index=3.5, n_deals=20 → no-op."""
    analogs_no_cadnum = [
        _make_listing_qi(price_per_m2=_BASE_PPM2, building_cadastral_number=None) for _ in range(3)
    ]
    base_median = round(_BASE_PPM2 * _AREA)
    est = _run_estimate_qi(
        analogs=analogs_no_cadnum,
        dadata_cadnum=f"{_TARGET_QUARTER}:350",
        qi_lookup_result=(3.5, 20),  # index>2.0 AND n<50 → bimodal guard
    )
    assert est.median_price_rub == base_median


def test_bimodal_guard_allows_high_index_large_n() -> None:
    """Bimodal guard НЕ срабатывает при price_index>2.0 если n_deals>=50.

    Коррекция применяется, но raw factor=2.5 зажат #859-clamp до max_factor=1.8.
    Медиана меняется (guard не блокирует), но масштабируется на 1.8, не 2.5.
    """
    analogs_no_cadnum = [
        _make_listing_qi(price_per_m2=_BASE_PPM2, building_cadastral_number=None) for _ in range(3)
    ]
    base_median = round(_BASE_PPM2 * _AREA)
    est = _run_estimate_qi(
        analogs=analogs_no_cadnum,
        dadata_cadnum=f"{_TARGET_QUARTER}:350",
        qi_lookup_result=(2.5, 60),  # index>2.0 но n=60>=50 → bimodal guard не срабатывает
    )
    # Коррекция применена: медиана != base_median (bimodal guard не заблокировал).
    # factor=2.5 > max_factor=1.8 → зажат до 1.8 (#859).
    assert est.median_price_rub != base_median
    assert est.median_price_rub == round(base_median * 1.8)


# ─────────────────────────────────────────────────────────────────────────────
# Guard-1a: anchor_tier не None → correction не применяется
# ─────────────────────────────────────────────────────────────────────────────


def test_guard1_anchor_tier_prevents_correction() -> None:
    """Guard-1a: когда same-building anchor сработал (anchor_tier='A'),
    квартальный индекс не применяется (double-count guard).

    Стабим _compute_same_building_anchor, чтобы вернул непустой anchor dict
    и _fetch_anchor_comps вернул comps → anchor_tier будет 'A'.
    """
    from app.services.estimator import estimate_quality

    db = MagicMock()
    payload = _make_payload_qi()
    dadata_obj = _make_fake_dadata(f"{_TARGET_QUARTER}:350")

    fake_comps = [
        _make_listing_qi(price_per_m2=_BASE_PPM2 * 1.5, building_cadastral_number=None)
        for _ in range(3)
    ]
    fake_anchor = {
        "anchor_ppm2": _BASE_PPM2 * 1.5,
        "anchor_sold_ppm2": _BASE_PPM2 * 1.4,
        "fsd": 0.05,
        "confidence": "high",
        "n": 3,
        "cv": 0.05,
        "comp_min_ppm2": _BASE_PPM2 * 1.3,
        "comp_max_ppm2": _BASE_PPM2 * 1.7,
        "used_uplift": False,
        "haircut": 0.05,
        # display-consistency fix: contract now requires "comps" — the final
        # post-MAD-clip survivors (see _compute_same_building_anchor docstring).
        "comps": fake_comps,
    }

    analogs_no_cadnum = [
        _make_listing_qi(price_per_m2=_BASE_PPM2, building_cadastral_number=None) for _ in range(3)
    ]

    async def _run():
        with (
            patch(
                "app.services.estimator.geocode",
                new=AsyncMock(return_value=_make_fake_geo_qi()),
            ),
            patch(
                "app.services.estimator.dadata_clean_address",
                new=AsyncMock(return_value=dadata_obj),
            ),
            patch("app.services.estimator.match_house_readonly", return_value=None),
            patch("app.services.estimator.get_house_metadata", new=AsyncMock(return_value=None)),
            patch(
                "app.services.estimator._fetch_analogs",
                return_value=(list(analogs_no_cadnum), False, "W"),
            ),
            patch("app.services.estimator._fetch_deals", return_value=[]),
            patch("app.services.estimator._fetch_dkp_corridor", return_value=None),
            patch(
                "app.services.estimator._get_or_fetch_imv_cached",
                new=AsyncMock(return_value=None),
            ),
            patch(
                "app.services.estimator._get_or_fetch_yandex_valuation_cached",
                new=AsyncMock(return_value=None),
            ),
            patch(
                "app.services.estimator.estimate_via_cian_valuation",
                new=AsyncMock(return_value=None),
            ),
            patch(
                "app.services.estimator._get_asking_sold_ratio",
                return_value=(None, None),
            ),
            patch("app.services.estimator._fetch_house_imv_anchor", return_value=None),
            # same-building anchor FIRES → anchor_tier = 'A'
            patch(
                "app.services.estimator._fetch_anchor_comps",
                return_value=(fake_comps, "A"),
            ),
            patch(
                "app.services.estimator._compute_same_building_anchor",
                return_value=fake_anchor,
            ),
            patch(
                "app.services.estimator._lookup_quarter_index",
                return_value=(1.5, 30),  # would apply if not guarded
            ),
        ):
            return await estimate_quality(payload, db)

    est = anyio.run(_run)

    # Медиана от anchor = anchor_ppm2 * repair_coef(=1.0 нет ремонта) * area
    anchor_median = round(_BASE_PPM2 * 1.5 * _AREA)
    assert est.median_price_rub == anchor_median
    # explanation не содержит упоминания квартала (guard-1 сработал)
    assert (
        est.confidence_explanation is None
        or "квартал" not in (est.confidence_explanation or "").lower()
    )


# ─────────────────────────────────────────────────────────────────────────────
# Guard-1b: IMV-blended → correction не применяется
# ─────────────────────────────────────────────────────────────────────────────


def test_guard1b_imv_blend_prevents_correction() -> None:
    """Guard-1b: IMV-blend повышал медиану → квартальный индекс не применяется."""
    from app.services.estimator import estimate_quality

    db = MagicMock()
    payload = _make_payload_qi()
    dadata_obj = _make_fake_dadata(f"{_TARGET_QUARTER}:350")

    analogs_no_cadnum = [
        _make_listing_qi(price_per_m2=_BASE_PPM2, building_cadastral_number=None) for _ in range(3)
    ]

    # IMV anchor сильно выше медианы → blend сработает
    imv_anchor = {
        "recommended_price": 30_000_000,  # ≫ base_median 6М × 1.15
        "lower_price": 25_000_000,
        "higher_price": 35_000_000,
        "market_count": 500,
        "rooms": 1,
        "area_m2": _AREA,
    }

    async def _run():
        with (
            patch(
                "app.services.estimator.geocode",
                new=AsyncMock(return_value=_make_fake_geo_qi()),
            ),
            patch(
                "app.services.estimator.dadata_clean_address",
                new=AsyncMock(return_value=dadata_obj),
            ),
            patch("app.services.estimator.match_house_readonly", return_value=None),
            patch("app.services.estimator.get_house_metadata", new=AsyncMock(return_value=None)),
            patch(
                "app.services.estimator._fetch_analogs",
                return_value=(list(analogs_no_cadnum), False, "W"),
            ),
            patch("app.services.estimator._fetch_deals", return_value=[]),
            patch("app.services.estimator._fetch_dkp_corridor", return_value=None),
            patch(
                "app.services.estimator._get_or_fetch_imv_cached",
                new=AsyncMock(return_value=None),
            ),
            patch(
                "app.services.estimator._get_or_fetch_yandex_valuation_cached",
                new=AsyncMock(return_value=None),
            ),
            patch(
                "app.services.estimator.estimate_via_cian_valuation",
                new=AsyncMock(return_value=None),
            ),
            patch(
                "app.services.estimator._get_asking_sold_ratio",
                return_value=(None, None),
            ),
            # IMV anchor fires (returns non-None) → blend will trigger
            patch(
                "app.services.estimator._fetch_house_imv_anchor",
                return_value=imv_anchor,
            ),
            patch(
                "app.services.estimator._lookup_quarter_index",
                return_value=(1.5, 30),  # would apply if not guarded
            ),
        ):
            return await estimate_quality(payload, db)

    est = anyio.run(_run)

    # IMV blend: base 6М, anchor 30М, w=0.5 → 18М
    blended_median = round(6_000_000 * 0.5 + 30_000_000 * 0.5)
    assert est.median_price_rub == blended_median
    # explanation не должна содержать квартального дисклоужера
    assert "квартал" not in (est.confidence_explanation or "").lower()


def test_guard1b_imv_anchor_below_blend_threshold_prevents_correction() -> None:
    """Guard-1b: IMV anchor присутствует но ниже blend-порога (blended=False).

    До фикса #764: imv_blended=False → квартальный индекс применялся поверх
    IMV-расширенного range_high (double-influence). После фикса: imv_anchor_present=True
    → quarter index не применяется вне зависимости от blended.
    """
    from app.services.estimator import estimate_quality

    db = MagicMock()
    payload = _make_payload_qi()
    dadata_obj = _make_fake_dadata(f"{_TARGET_QUARTER}:350")

    analogs_no_cadnum = [
        _make_listing_qi(price_per_m2=_BASE_PPM2, building_cadastral_number=None) for _ in range(3)
    ]

    # IMV anchor НИЖЕ blend-порога: base_median = 6_000_000, threshold=1.15 → порог 6.9М.
    # anchor=6_500_000 < 6.9М → blended=False, но range_high IMV-расширен.
    imv_anchor_below_threshold = {
        "recommended_price": 6_500_000,
        "lower_price": 5_800_000,
        "higher_price": 7_200_000,
        "market_count": 100,
        "rooms": 1,
        "area_m2": _AREA,
    }

    async def _run():
        with (
            patch(
                "app.services.estimator.geocode",
                new=AsyncMock(return_value=_make_fake_geo_qi()),
            ),
            patch(
                "app.services.estimator.dadata_clean_address",
                new=AsyncMock(return_value=dadata_obj),
            ),
            patch("app.services.estimator.match_house_readonly", return_value=None),
            patch("app.services.estimator.get_house_metadata", new=AsyncMock(return_value=None)),
            patch(
                "app.services.estimator._fetch_analogs",
                return_value=(list(analogs_no_cadnum), False, "W"),
            ),
            patch("app.services.estimator._fetch_deals", return_value=[]),
            patch("app.services.estimator._fetch_dkp_corridor", return_value=None),
            patch(
                "app.services.estimator._get_or_fetch_imv_cached",
                new=AsyncMock(return_value=None),
            ),
            patch(
                "app.services.estimator._get_or_fetch_yandex_valuation_cached",
                new=AsyncMock(return_value=None),
            ),
            patch(
                "app.services.estimator.estimate_via_cian_valuation",
                new=AsyncMock(return_value=None),
            ),
            patch(
                "app.services.estimator._get_asking_sold_ratio",
                return_value=(None, None),
            ),
            # IMV anchor returns below-threshold value → blended=False but anchor_present=True
            patch(
                "app.services.estimator._fetch_house_imv_anchor",
                return_value=imv_anchor_below_threshold,
            ),
            patch(
                "app.services.estimator._lookup_quarter_index",
                return_value=(1.5, 30),  # would apply factor=1.5 if not guarded
            ),
        ):
            return await estimate_quality(payload, db)

    est = anyio.run(_run)

    # Медиана не должна быть умножена на 1.5 (квартальный индекс заблокирован).
    base_median = round(_BASE_PPM2 * _AREA)  # 6_000_000
    assert est.median_price_rub == base_median
    # explanation не содержит квартального дисклоужера
    assert "квартал" not in (est.confidence_explanation or "").lower()


# ─────────────────────────────────────────────────────────────────────────────
# #859 — sanity-clamp на factor = target_index / avg_analog_index
# ─────────────────────────────────────────────────────────────────────────────


def test_apply_quarter_index_clamp_extreme_high_raw_factor() -> None:
    """Экстремально низкий avg_analog_index → raw factor >> max → зажат до max_factor.

    target_index=1.0, avg_analog_index=0.3 → raw=3.33, clamped→1.8.
    Выходы масштабируются на 1.8, не на 3.33.
    """
    max_f = 1.8
    ppm2, median, low, high, factor = _apply_quarter_index(
        base_median_ppm2=100_000.0,
        base_median_price=5_000_000,
        base_range_low=4_000_000,
        base_range_high=6_000_000,
        target_index=1.0,
        avg_analog_index=0.3,
        min_factor=0.6,
        max_factor=max_f,
    )
    assert abs(factor - max_f) < 1e-9, f"Expected factor={max_f}, got {factor}"
    assert abs(ppm2 - 100_000.0 * max_f) < 1.0
    assert median == round(5_000_000 * max_f)
    assert low == round(4_000_000 * max_f)
    assert high == round(6_000_000 * max_f)
    # Убеждаемся, что raw factor действительно был бы за пределами clamp
    raw = 1.0 / 0.3
    assert raw > max_f


def test_apply_quarter_index_clamp_extreme_low_raw_factor() -> None:
    """Экстремально высокий avg_analog_index → raw factor << min → зажат до min_factor.

    target_index=0.5, avg_analog_index=2.0 → raw=0.25, clamped→0.6.
    Выходы масштабируются на 0.6, не на 0.25.
    """
    min_f = 0.6
    ppm2, median, low, high, factor = _apply_quarter_index(
        base_median_ppm2=100_000.0,
        base_median_price=5_000_000,
        base_range_low=4_000_000,
        base_range_high=6_000_000,
        target_index=0.5,
        avg_analog_index=2.0,
        min_factor=min_f,
        max_factor=1.8,
    )
    assert abs(factor - min_f) < 1e-9, f"Expected factor={min_f}, got {factor}"
    assert abs(ppm2 - 100_000.0 * min_f) < 1.0
    assert median == round(5_000_000 * min_f)
    assert low == round(4_000_000 * min_f)
    assert high == round(6_000_000 * min_f)
    # Убеждаемся, что raw factor действительно был бы за пределами clamp
    raw = 0.5 / 2.0
    assert raw < min_f


def test_apply_quarter_index_clamp_normal_factor_unchanged() -> None:
    """Нормальный factor внутри [0.6, 1.8] → clamp не меняет значение (регрессия).

    target_index=1.3, avg_analog_index=1.1 → raw=1.182, внутри [0.6,1.8] → без изменений.
    """
    raw_expected = 1.3 / 1.1
    ppm2, median, _low, _high, factor = _apply_quarter_index(
        base_median_ppm2=200_000.0,
        base_median_price=10_000_000,
        base_range_low=8_000_000,
        base_range_high=12_000_000,
        target_index=1.3,
        avg_analog_index=1.1,
        min_factor=0.6,
        max_factor=1.8,
    )
    assert abs(factor - raw_expected) < 1e-9, f"Expected {raw_expected}, got {factor}"
    assert abs(ppm2 - 200_000.0 * raw_expected) < 1.0
    assert median == round(10_000_000 * raw_expected)


def test_apply_quarter_index_clamp_boundary_at_max_exact() -> None:
    """factor точно на верхней границе (=1.8) → clamp не применяется."""
    # target=1.8, avg=1.0 → raw=1.8 ровно = max_factor
    _ppm2, median, _low, _high, factor = _apply_quarter_index(
        base_median_ppm2=100_000.0,
        base_median_price=5_000_000,
        base_range_low=4_000_000,
        base_range_high=6_000_000,
        target_index=1.8,
        avg_analog_index=1.0,
        min_factor=0.6,
        max_factor=1.8,
    )
    assert abs(factor - 1.8) < 1e-9
    assert median == round(5_000_000 * 1.8)


def test_apply_quarter_index_clamp_boundary_at_min_exact() -> None:
    """factor точно на нижней границе (=0.6) → clamp не применяется."""
    # target=0.6, avg=1.0 → raw=0.6 ровно = min_factor
    _ppm2, median, _low, _high, factor = _apply_quarter_index(
        base_median_ppm2=100_000.0,
        base_median_price=5_000_000,
        base_range_low=4_000_000,
        base_range_high=6_000_000,
        target_index=0.6,
        avg_analog_index=1.0,
        min_factor=0.6,
        max_factor=1.8,
    )
    assert abs(factor - 0.6) < 1e-9
    assert median == round(5_000_000 * 0.6)


if __name__ == "__main__":  # pragma: no cover
    raise SystemExit(pytest.main([__file__, "-q"]))