from photoflow.core.models import Asset
from app.clustering import CandidateCluster
from app.coverage import coverage_members


def _a(i, taken):
    return Asset(immich_id=i, taken_at=taken)


def test_coverage_candidate_inside_seeded_window():
    members = [_a("a", "2019-06-01T10:00:00"), _a("b", "2019-06-01T12:00:00"),
               _a("c", "2019-06-02T10:00:00")]
    intruder = _a("x", "2019-06-01T13:00:00")          # in window, untagged
    outside = _a("y", "2019-07-01T10:00:00")           # out of window
    by_id = {m.immich_id: m for m in members + [intruder, outside]}
    cand = CandidateCluster(member_ids=["a", "b", "c"], start_at="2019-06-01T10:00:00",
                            end_at="2019-06-02T10:00:00", suggested_name="Italy 2019",
                            confidence=0.95, kind_guess="trip", seed_tag="Italy 2019")
    out = coverage_members(cand, by_id)
    flagged = {m.immich_id for m in out if m.flagged_coverage}
    assert flagged == {"x"}                            # only the in-window intruder
    assert all(not m.included for m in out if m.flagged_coverage)


def test_outlier_member_far_from_bulk():
    members = [_a("a", "2019-06-01T10:00:00"), _a("a2", "2019-06-01T11:00:00"),
               _a("a3", "2019-06-01T12:00:00"),
               _a("z", "2019-09-01T10:00:00")]          # tagged but months away
    by_id = {m.immich_id: m for m in members}
    cand = CandidateCluster(member_ids=["a", "a2", "a3", "z"],
                            start_at="2019-06-01T10:00:00", end_at="2019-09-01T10:00:00",
                            suggested_name="Italy 2019", confidence=0.95,
                            kind_guess="trip", seed_tag="Italy 2019")
    out = coverage_members(cand, by_id)
    outliers = {m.immich_id for m in out if m.is_outlier}
    assert outliers == {"z"}


def test_non_seeded_cluster_has_no_coverage_or_outliers():
    members = [_a("a", "2019-06-01T10:00:00"), _a("b", "2019-06-01T12:00:00")]
    intruder = _a("x", "2019-06-01T11:00:00")
    by_id = {m.immich_id: m for m in members + [intruder]}
    cand = CandidateCluster(member_ids=["a", "b"], start_at="2019-06-01T10:00:00",
                            end_at="2019-06-01T12:00:00", suggested_name="Trip",
                            confidence=0.4, kind_guess="everyday", seed_tag=None)
    out = coverage_members(cand, by_id)
    assert {m.immich_id for m in out} == {"a", "b"}
    assert not any(m.flagged_coverage or m.is_outlier for m in out)