"""Behavioural tests for the place deriver.

A frequent place is a spatial cluster of photo metadata (and similar
location-bearing evidence) visited repeatedly over time.
"""
from __future__ import annotations

from datetime import timedelta

from mnema.derive.derivers.places import PlaceDeriver

# A fixed anchor in San Francisco; jitter of ~0.0002 degrees is ~20 metres.
LAT, LON = 37.7764, -122.4242
JITTER = [
    (0.0000, 0.0000),
    (0.0001, -0.0001),
    (-0.0002, 0.0001),
    (0.0002, 0.0002),
    (-0.0001, -0.0002),
    (0.0001, 0.0001),
    (-0.0002, -0.0001),
    (0.0002, -0.0002),
    (0.0000, 0.0002),
    (-0.0001, 0.0001),
    (0.0001, -0.0002),
    (0.0002, 0.0000),
]


def _cluster_photos(kit, count, place_name=None):
    photos = []
    for i in range(count):
        dlat, dlon = JITTER[i % len(JITTER)]
        photos.append(
            kit.make_photo(
                kit.T0 + timedelta(days=2 * i, hours=i % 5),
                LAT + dlat,
                LON + dlon,
                place_name=place_name,
            )
        )
    return photos


def _places_run(kit, evidence):
    engine = kit.new_engine([PlaceDeriver()])
    claims = kit.run_claims(engine, evidence)
    return engine, kit.by_predicate(claims, "place")


def test_repeated_photo_location_yields_place_claim(kit):
    photos = _cluster_photos(kit, 8, place_name="Mission Coffee Club")
    _, places = _places_run(kit, photos)
    assert places, "eight photos within ~30m over three weeks must yield a place claim"
    claim = kit.best(places)
    assert 0.0 < claim.confidence <= 1.0
    photo_ids = {p.evidence_id for p in photos}
    cited = set(claim.inputs)
    assert cited and cited <= photo_ids
    assert len(cited) >= 4, "a frequent place should cite several visits"


def test_place_name_propagates_into_claim(kit):
    photos = _cluster_photos(kit, 8, place_name="Mission Coffee Club")
    _, places = _places_run(kit, photos)
    claim = kit.best(places)
    assert "mission coffee" in kit.vdump(claim), (
        "when evidence carries a place name, the derived claim should surface it"
    )


def test_scattered_photos_yield_no_place(kit):
    spots = [
        (51.5072, -0.1276),   # London
        (35.6764, 139.6500),  # Tokyo
        (-33.8688, 151.2093), # Sydney
        (40.7128, -74.0060),  # New York
        (55.7558, 37.6173),   # Moscow
        (-23.5505, -46.6333), # Sao Paulo
    ]
    photos = [
        kit.make_photo(kit.T0 + timedelta(days=i * 3), lat, lon)
        for i, (lat, lon) in enumerate(spots)
    ]
    _, places = _places_run(kit, photos)
    assert places == [], "one photo per location worldwide must not yield a frequent place"


def test_more_visits_do_not_lower_confidence(kit):
    _, few = _places_run(kit, _cluster_photos(kit, 4))
    _, many = _places_run(kit, _cluster_photos(kit, 12))
    assert few and many
    c_few = kit.best(few).confidence
    c_many = kit.best(many).confidence
    assert c_many >= c_few, (
        f"confidence must be monotone in visit count: {c_many} (12) < {c_few} (4)"
    )


def test_place_claim_is_explainable(kit):
    photos = _cluster_photos(kit, 8, place_name="Mission Coffee Club")
    engine, places = _places_run(kit, photos)
    claim = kit.best(places)
    text = kit.explanation_text(engine, claim)
    assert text, "every claim must have a retrievable explanation"