from src.models.lgbm_features import build_runtime_feature_map, build_training_samples


def test_build_runtime_feature_map_derives_history_and_model_summary():
    history_data = {
        "ankara": {
            "2026-03-20": {"actual_high": 10.0},
            "2026-03-21": {"actual_high": 11.0},
            "2026-03-22": {"actual_high": 13.0},
            "2026-03-23": {"actual_high": 12.0},
        }
    }

    feature_map, meta = build_runtime_feature_map(
        city_name="ankara",
        current_forecasts={
            "Open-Meteo": 12.4,
            "ECMWF": 12.1,
            "GFS": 11.9,
            "GEM": 12.8,
        },
        deb_prediction=12.3,
        current_temp=11.0,
        max_so_far=11.4,
        humidity=62.0,
        wind_speed_kt=8.0,
        visibility_mi=6.0,
        local_hour=10,
        local_date="2026-03-24",
        peak_status="before",
        history_data=history_data,
    )

    assert meta["reason"] == "ok"
    assert meta["history_count"] == 4
    assert feature_map["actual_high_lag_1"] == 12.0
    assert feature_map["actual_high_lag_2"] == 13.0
    assert feature_map["actual_high_trend_3"] == 1.0
    assert feature_map["model_median"] == 12.4
    assert round(feature_map["model_spread"], 3) == 0.9
    assert feature_map["peak_status_code"] == 0.0


def test_build_runtime_feature_map_returns_none_without_history():
    feature_map, meta = build_runtime_feature_map(
        city_name="unknown-city",
        current_forecasts={"Open-Meteo": 12.4},
        deb_prediction=12.3,
        current_temp=11.0,
        max_so_far=11.4,
        humidity=62.0,
        wind_speed_kt=8.0,
        visibility_mi=6.0,
        local_hour=10,
        local_date="2026-03-24",
        peak_status="before",
        history_data={},
    )

    assert feature_map is None
    assert meta["reason"] == "no_history"


def test_build_training_samples_prefers_truth_history_for_target():
    history_data = {
        "ankara": {
            "2026-03-20": {"actual_high": 10.0},
            "2026-03-21": {"actual_high": 11.0},
            "2026-03-22": {"actual_high": 13.0},
            "2026-03-23": {
                "actual_high": 12.0,
                "deb_prediction": 12.3,
                "forecasts": {"Open-Meteo": 12.4, "ECMWF": 12.1},
            },
        }
    }
    snapshot_index = {
        ("ankara", "2026-03-23"): {
            "city": "ankara",
            "date": "2026-03-23",
            "timestamp": "2026-03-23T10:00:00+03:00",
            "raw_mu": 12.2,
            "deb_prediction": 12.3,
            "max_so_far": 11.8,
            "peak_status": "before",
            "multi_model": {"Open-Meteo": 12.4, "ECMWF": 12.1},
            "observation": {"current_temp": 11.5, "humidity": 60.0, "wind_speed_kt": 8.0, "local_hour": 10},
        }
    }

    samples = build_training_samples(history_data=history_data, snapshot_index=snapshot_index)
    assert len(samples) == 1
    assert samples[0]["sample_source"] == "snapshot"