from app.analysis.levels import Side
from app.analysis.manual_lines import ManualLine, ManualLineStore
from app.analysis.confluence import cluster_levels
from app.analysis.levels import Level, LevelKind
from app.bars.models import Timeframe


def sample_line():
    return ManualLine("ml_test", Timeframe.H4, Side.RESISTANCE, 100, 5000, -0.01, 200, 300, number=1)


def test_json_persistence_round_trip(tmp_path):
    path = tmp_path / "manual_lines.json"
    store = ManualLineStore(path)
    store.add(sample_line())

    loaded = ManualLineStore(path)
    assert list(loaded.lines.values()) == [sample_line()]

    loaded.update("ml_test", {"note": "major swing"})
    assert ManualLineStore(path).lines["ml_test"].note == "major swing"
    loaded.delete("ml_test")
    assert ManualLineStore(path).lines == {}


def test_four_hour_line_uses_absolute_time_on_one_minute_chart():
    level = sample_line().to_level()
    instant = 160
    assert level.tf is Timeframe.H4
    assert level.price_at(instant) == 4999.4
    assert level.weight == 8


def test_manual_line_raises_existing_ma_cluster_score():
    ma = Level(
        "ma", LevelKind.MA, Timeframe.D1, Side.RESISTANCE, 12, 1, "1d SMA20",
        100, 5000, 0, None, 0, 100, 100, False, False, 20,
    )
    before = cluster_levels([ma], 160, 4998, 2)[0]
    after = cluster_levels([ma, sample_line().to_level()], 160, 4998, 2)[0]
    assert before.score == 12
    assert after.score == 20