homemaker-layout/tests/test_fitness.py

"""Unit tests for fitness.py quality terms and helpers (oracle-free)."""

from pathlib import Path

import pytest

from _helpers import with_usage
from homemaker_layout import dom, geometry
from homemaker_layout.dom import Node
from homemaker_layout.fitness import (
    CONF_DEFAULTS,
    COST_DEFAULTS,
    FAIL_THRESHOLD,
    Fitness,
    _leaf_grade,
    classify_fail_tier,
    load_config,
    gaussian,
    tier_counts,
)


def _leaf(type_: str, size: float = 4.0) -> Node:
    """Undivided level-root leaf with a square plot of side `size`."""
    geometry.clear_cache()
    return Node(
        node=[[0.0, 0.0], [size, 0.0], [size, size], [0.0, size]],
        type=type_,
    )


# --------------------------------------------------------------------------- #
# gaussian
# --------------------------------------------------------------------------- #


def test_gaussian_peak_returns_a():
    assert gaussian(5.0, 1.0, 5.0, 1.0) == pytest.approx(1.0)


def test_gaussian_peak_scales_by_a():
    assert gaussian(3.0, 2.5, 3.0, 1.0) == pytest.approx(2.5)


def test_gaussian_one_sigma_uses_truncated_e():
    # Urb uses e=2.718281828, not math.e; at one sigma the factor is e^-0.5
    e = 2.718281828
    expected = e ** -0.5
    assert gaussian(6.0, 1.0, 5.0, 1.0) == pytest.approx(expected, rel=1e-9)


def test_gaussian_symmetry():
    assert gaussian(4.0, 1.0, 5.0, 1.0) == pytest.approx(gaussian(6.0, 1.0, 5.0, 1.0))


# --------------------------------------------------------------------------- #
# Fitness.conf / cost
# --------------------------------------------------------------------------- #


def test_conf_falls_back_to_defaults():
    assert Fitness().conf("value_inside") == CONF_DEFAULTS["value_inside"]


def test_conf_override_wins():
    assert Fitness(conf={"value_inside": 999.0}).conf("value_inside") == 999.0


def test_conf_unknown_key_returns_none():
    assert Fitness().conf("no_such_key") is None


def test_cost_falls_back_to_defaults():
    assert Fitness().cost("inside") == COST_DEFAULTS["inside"]


def test_cost_override_wins():
    assert Fitness(cost={"inside": 42.0}).cost("inside") == 42.0


def test_cost_unknown_key_returns_zero():
    assert Fitness().cost("no_such_key") == 0.0


# --------------------------------------------------------------------------- #
# get_space_params lookup chain
# --------------------------------------------------------------------------- #


def test_get_space_params_circulation_size():
    assert Fitness().get_space_params("C", "size") == CONF_DEFAULTS["size_circulation"]


def test_get_space_params_outside_width():
    assert Fitness().get_space_params("O", "width") == CONF_DEFAULTS["width_outside"]


def test_get_space_params_sahn_proportion():
    assert Fitness().get_space_params("S", "proportion") == CONF_DEFAULTS["proportion_outside"]


def test_get_space_params_inside_falls_back_to_inside_defaults():
    assert Fitness().get_space_params("k1", "proportion") == CONF_DEFAULTS["proportion_inside"]
    assert Fitness().get_space_params("k1", "size") == CONF_DEFAULTS["size_inside"]


def test_get_space_params_named_space_overrides_default():
    f = Fitness(conf={"spaces": with_usage({"k1": {"size": [20.0, 4.0]}})})
    assert f.get_space_params("k1", "size") == [20.0, 4.0]


# --------------------------------------------------------------------------- #
# quality_proportion
# --------------------------------------------------------------------------- #


def test_quality_proportion_square_inside_returns_one():
    # aspect=1.0 < proportion_inside[0]=1.5 → 1.0
    assert Fitness().quality_proportion(_leaf("k1")) == pytest.approx(1.0)


def test_quality_proportion_square_outside_returns_one():
    # aspect=1.0 < proportion_outside[0]=1.5 → 1.0
    assert Fitness().quality_proportion(_leaf("O")) == pytest.approx(1.0)


def test_quality_proportion_square_circulation_returns_one():
    assert Fitness().quality_proportion(_leaf("C")) == pytest.approx(1.0)


# --------------------------------------------------------------------------- #
# quality_size
# --------------------------------------------------------------------------- #


def test_quality_size_outside_always_one():
    assert Fitness().quality_size(_leaf("O")) == 1.0


def test_quality_size_sahn_always_one():
    assert Fitness().quality_size(_leaf("S")) == 1.0


def test_quality_size_inside_at_peak():
    # size_inside=[16.0,3.5]; leaf is 4×4=16 m² → gaussian at peak → 1.0
    leaf = _leaf("k1", size=4.0)
    assert geometry.area(leaf) == pytest.approx(16.0)
    assert Fitness().quality_size(leaf) == pytest.approx(1.0)


def test_quality_size_circulation_at_peak():
    # size_circulation=[0.0,14.0]; peak at 0, gaussian(area,1,0,14) → always <1 for area>0
    # Just verify it returns a value in [0,1]
    f = Fitness().quality_size(_leaf("C", size=4.0))
    assert 0.0 < f <= 1.0


# --------------------------------------------------------------------------- #
# quality_width
# --------------------------------------------------------------------------- #


def test_quality_width_wide_inside_returns_one():
    # width_inside=[4.0,1.0]; 10m side > 4.0 → 1.0
    assert Fitness().quality_width(_leaf("k1", size=10.0)) == pytest.approx(1.0)


def test_quality_width_wide_circulation_returns_one():
    # width_circulation=[2.4,0.2]; 10m > 2.4 → 1.0
    assert Fitness().quality_width(_leaf("C", size=10.0)) == pytest.approx(1.0)


def test_quality_width_wide_outside_ground_uses_gaussian():
    # outside at level 0 falls through to gaussian; 10m > width_outside[0]=3.0 → 1.0
    assert Fitness().quality_width(_leaf("O", size=10.0)) == pytest.approx(1.0)


# --------------------------------------------------------------------------- #
# quality_perpendicular
# --------------------------------------------------------------------------- #


def test_quality_perpendicular_rectangle_near_one():
    # All four corners of the square are pi/2; perpendicular formula gives ≈1
    leaf = _leaf("k1", size=4.0)
    result = Fitness().quality_perpendicular(leaf)
    assert result == pytest.approx(1.0, abs=1e-6)


# --------------------------------------------------------------------------- #
# value_rate
# --------------------------------------------------------------------------- #


def test_value_rate_outside_ground():
    leaf = _leaf("O")
    assert dom.level_of(leaf) == 0
    assert Fitness().value_rate(leaf) == pytest.approx(CONF_DEFAULTS["value_outside"])


def test_value_rate_circulation():
    assert Fitness().value_rate(_leaf("C")) == pytest.approx(CONF_DEFAULTS["value_circulation"])


def test_value_rate_inside():
    assert Fitness().value_rate(_leaf("k1")) == pytest.approx(CONF_DEFAULTS["value_inside"])


# --------------------------------------------------------------------------- #
# leaf_cost
# --------------------------------------------------------------------------- #


def test_leaf_cost_outside_bare():
    # not covered, not supported → outside rate × area
    leaf = _leaf("O", size=4.0)  # area = 16.0
    assert Fitness().leaf_cost(leaf) == pytest.approx(COST_DEFAULTS["outside"] * 16.0)


def test_leaf_cost_inside():
    leaf = _leaf("k1", size=4.0)
    assert Fitness().leaf_cost(leaf) == pytest.approx(COST_DEFAULTS["inside"] * 16.0)


# --------------------------------------------------------------------------- #
# Share-aware edge-too-long cap (hph §13.7)
# --------------------------------------------------------------------------- #


def _shared_leaf(type_: str = "k1", k: int = 3) -> Node:
    leaf = _leaf(type_)
    leaf.share = k
    leaf.share_type = type_
    return leaf


def test_edge_cap_flat_by_default():
    # no leaf_sharing → flat 8 m regardless of any share stamp
    fit = Fitness()
    assert fit._edge_cap(_shared_leaf(k=3)) == pytest.approx(8.0)


def test_edge_cap_flat_when_lever_off_even_with_sharing():
    # leaf_sharing on but the hph lever explicitly off → still flat (control arm).
    # Post-§13.8 the lever defaults ON under sharing, so the control must pin it.
    fit = Fitness(conf={"leaf_sharing": True, "share_edge_cap": False})
    assert fit._edge_cap(_shared_leaf(k=3)) == pytest.approx(8.0)


def test_edge_cap_scales_by_share_when_lever_on():
    fit = Fitness(conf={"leaf_sharing": True, "share_edge_cap": True})
    assert fit._edge_cap(_shared_leaf(k=3)) == pytest.approx(24.0)


def test_edge_cap_defaults_on_under_leaf_sharing():
    # §13.8 default flip: leaf_sharing on, lever unset → cap scales by share
    fit = Fitness(conf={"leaf_sharing": True})
    assert fit._edge_cap(_shared_leaf(k=3)) == pytest.approx(24.0)


def test_edge_cap_unshared_leaf_keeps_flat_cap():
    # a non-shared leaf (the narrow-sliver pathology) is never relaxed
    fit = Fitness(conf={"leaf_sharing": True, "share_edge_cap": True})
    assert fit._edge_cap(_leaf("k1")) == pytest.approx(8.0)


def test_edge_cap_stale_share_type_ignored():
    # retyped leaf whose stamp no longer matches type → share invalid → flat
    fit = Fitness(conf={"leaf_sharing": True, "share_edge_cap": True})
    leaf = _shared_leaf("k1", k=3)
    leaf.type = "b1"  # retyped; share_type still "k1"
    assert fit._edge_cap(leaf) == pytest.approx(8.0)


def test_edge_cap_uses_largest_share_among_adjoining_leaves():
    # an interior wall takes the max share of the two leaves it separates
    fit = Fitness(conf={"leaf_sharing": True, "share_edge_cap": True})
    cap = fit._edge_cap(_leaf("k1"), _shared_leaf("b1", k=2))
    assert cap == pytest.approx(16.0)


# --------------------------------------------------------------------------- #
# Stair helpers
# --------------------------------------------------------------------------- #


def test_risers_number_exact_division():
    # 2.0 / 0.25 = 8.0 exactly → returns 8
    assert Fitness._risers_number(2.0, 0.25) == 8


def test_risers_number_rounds_up():
    # 3.0 / 0.19 ≈ 15.789 → rounds up to 16
    assert Fitness._risers_number(3.0, 0.19) == 16


def test_ideal_going_clamps_to_minimum():
    # riser=0.25 → going=0.125 < 0.22 → clamp
    assert Fitness._ideal_going(0.25) == 0.22


def test_ideal_going_above_minimum():
    # riser=0.15 → going=0.325 > 0.22; result should be in valid range
    result = Fitness._ideal_going(0.15)
    assert result >= 0.22
    assert result <= 0.625


# --------------------------------------------------------------------------- #
# Graded high-fail objective (§11.4)
# --------------------------------------------------------------------------- #


def test_leaf_grade_no_failing_factors_is_zero():
    # All factors above FAIL_THRESHOLD → no proximity credit.
    assert _leaf_grade({"size": 0.9, "width": 1.0, "access": 1.0}) == 0.0


def test_leaf_grade_credits_only_failing_factors():
    # Only size fails (0.05 < 0.1); credit = 0.05 / 0.1 = 0.5.
    g = _leaf_grade({"size": 0.05, "width": 0.5, "proportion": 1.0})
    assert g == pytest.approx(0.05 / FAIL_THRESHOLD)


def test_leaf_grade_monotone_in_proximity():
    # A failing factor closer to the threshold scores higher (better).
    deep = _leaf_grade({"size": 0.01})
    shallow = _leaf_grade({"size": 0.09})
    assert shallow > deep


def test_leaf_grade_sums_over_failing_factors():
    g = _leaf_grade({"size": 0.04, "width": 0.06, "access": 1.0})
    assert g == pytest.approx((0.04 + 0.06) / FAIL_THRESHOLD)


def test_leaf_grade_ignores_non_graded_keys():
    # daylight is pinned and never a graded factor even if below threshold.
    assert _leaf_grade({"daylight": 0.0}) == 0.0


# --------------------------------------------------------------------------- #
# load_config overrides (homemaker-py-x3b)
# --------------------------------------------------------------------------- #


def test_load_config_overrides_merge_last(tmp_path):
    # The CLI/driver injects run-level knobs (leaf_sharing) without editing any
    # on-disk patterns.config, so §13.3 example programmes stay reproducible.
    import yaml

    from homemaker_layout.fitness import load_config

    (tmp_path / "patterns.config").write_text(
        yaml.safe_dump({"spaces": with_usage({"b": {"size": [12.0, 1.0]}})}))

    conf, _ = load_config(tmp_path)
    assert "leaf_sharing" not in conf  # absent on disk

    conf2, _ = load_config(tmp_path, overrides={"leaf_sharing": True})
    assert conf2["leaf_sharing"] is True
    assert conf2["spaces"]["b"] == with_usage({"b": {"size": [12.0, 1.0]}})["b"]

    # None / empty overrides are a no-op (default-OFF parity).
    assert "leaf_sharing" not in load_config(tmp_path, overrides=None)[0]
    assert "leaf_sharing" not in load_config(tmp_path, overrides={})[0]


def test_programme_parses_per_code_share(tmp_path):
    # homemaker-py-x3b: SpaceReq carries the optional per-code 'share' grain and a
    # has_share flag distinguishing an explicit share:1 (opt out) from the default.
    import yaml

    from homemaker_layout.programme import load_programme

    p = tmp_path / "patterns.config"
    p.write_text(yaml.safe_dump({"spaces": with_usage({
        "b": {"size": [12.0, 1.0], "share": 3},
        "k": {"size": [20.0, 1.0]},            # no share key
    })}))
    reqs = load_programme(str(p))
    assert reqs["b"].share == 3 and reqs["b"].has_share is True
    assert reqs["k"].share == 1 and reqs["k"].has_share is False


# --------------------------------------------------------------------------- #
# Hard/soft fail tiering (homemaker-py-2g7.3)
# --------------------------------------------------------------------------- #

@pytest.mark.parametrize("fail_str", [
    "missing required space: la1",
    "missing required space: la1 (critical)",
    "too many spaces: k (found 3, expected 2)",
    "missing ef1: would need size check",
    "missing ef1: would need width check",
    "missing ef1: would need proportion check",
    "missing m: would need adjacency to c",
    "missing r: would need to be on level 1",
    "missing t1: would need connection to c below",
    "0/lr (cr1) not adjacent to c",
    "li1 on wrong level (level 0, expected 1)",
    "t1 not connected to c below",
    "level 0 not connected",
    "0 inaccessible usable space",
    "level 0 no outside space",
    "0/lr unsupported covered outside",
    "0/lr covered outside above ground",
    "too few stairs (0, min 1)",
    "too many stairs (2, max 1)",
    "storey limit",
    "storey minimum",
    "no outside public access",
])
def test_classify_fail_tier_hard(fail_str):
    assert classify_fail_tier(fail_str) == "hard"


@pytest.mark.parametrize("fail_str", [
    "0/lr perpendicular",
    "0/lr proportion",
    "0/lr size",
    "0/lr width",
    "0/lr crinkliness",
    "0/lr access",
    "0/lr lrr edge too long",
    "lr outside edge too long",
    "staircase volume",
])
def test_classify_fail_tier_soft(fail_str):
    assert classify_fail_tier(fail_str) == "soft"


def test_classify_fail_tier_missing_cascade_is_hard_not_soft():
    # "missing X: would need size check" contains the SOFT " size" substring,
    # but is a consequence of a HARD missing-space fail, not a shape defect —
    # the HARD markers must be checked first (fitness.py ordering).
    assert classify_fail_tier("missing m#2: would need size check") == "hard"


def test_classify_fail_tier_unknown_raises():
    with pytest.raises(ValueError):
        classify_fail_tier("some brand new fail string nobody tiered yet")


def test_tier_counts_splits_hard_and_soft():
    fails = ("level 0 not connected", "0/lr proportion", "0/lr crinkliness",
              "missing required space: k1")
    assert tier_counts(fails) == (2, 2)


def test_tier_counts_empty():
    assert tier_counts(()) == (0, 0)


# Layouts chosen for BREADTH of failure kinds, not for being good designs --
# between them these emit size/width/proportion/crinkliness/access/adjacency,
# missing-space cascades, connectivity and volume fails.
_CORPUS_LAYOUTS = [
    ("harbor-house", "evolved-3M-nols-3.dom"),
    ("harbor-house", "generated.dom"),
    ("maple-court", "generated.dom"),
]


def test_classify_fail_tier_covers_every_fail_the_evaluator_emits():
    """Every fail string the evaluator can produce must classify into a tier.

    Fails are GENERATED here by scoring corpus layouts. The previous version
    globbed `examples/**/*.fails` and asserted it had checked something -- but
    those are generated artefacts that `homemaker-fitness` writes beside a
    `.dom`, absent from a clean checkout. So it passed only on a machine that
    had already run the scorer, and in a fresh clone failed with `assert 0 > 0`:
    it was asserting on the state of the developer's working tree, not on the
    code (`homemaker-py-1ue`).
    """
    import copy

    from homemaker_layout import dom as dom_mod

    repo_root = Path(__file__).resolve().parent.parent
    checked = kinds = 0
    seen: set[str] = set()
    for prog, name in _CORPUS_LAYOUTS:
        path = repo_root / "examples" / prog / name
        if not path.is_file():
            continue
        conf, cost = load_config(repo_root / "examples" / prog)
        _, fails = Fitness(conf, cost).score_with_fails(
            copy.deepcopy(dom_mod.load(str(path))))
        for fail in fails:
            classify_fail_tier(fail)      # raises on an unclassified string
            checked += 1
            seen.add(fail.split()[-1])
    kinds = len(seen)
    assert checked > 0, "no corpus layout could be scored -- fixtures missing?"
    assert kinds >= 8, f"only {kinds} distinct fail kinds exercised; too narrow"


def test_classify_fail_tier_rejects_an_unknown_fail_string():
    """The guard above is only worth anything if an unclassifiable string
    actually raises."""
    with pytest.raises(ValueError, match="unclassified fail string"):
        classify_fail_tier("0/lr something nobody has ever emitted")


def test_classify_fail_tier_checks_any_native_fails_artefacts_present():
    """If a working tree happens to carry .fails artefacts, check them too --
    but never require them to exist."""
    import glob

    repo_root = Path(__file__).resolve().parent.parent
    for path in glob.glob(str(repo_root / "examples" / "**" / "*.fails"),
                          recursive=True):
        with open(path) as f:
            first = f.readline()
            if first.startswith("---"):
                continue      # legacy Perl-oracle YAML, not this evaluator
            lines = [first.rstrip("\n")] + [ln.rstrip("\n") for ln in f]
        for line in lines:
            if line:
                classify_fail_tier(line)


# --------------------------------------------------------------------------- #
# homemaker-py-ssz / DESIGN.md §38.1 — crinkliness_mode (EXPERIMENTAL)
# --------------------------------------------------------------------------- #
class _StubCrink(Fitness):
    """Fitness with ``crinkliness`` stubbed, so the modes can be tested without
    building a real tree/graph (the value under test is the branch, not the
    geometry)."""

    _stub = 0.0

    def crinkliness(self, leaf, G, groups):  # noqa: D102 - test stub
        return self._stub


def _stub_fit(mode=None, stub=0.0, type_="t1"):
    conf = dict(CONF_DEFAULTS)
    if mode is not None:
        conf["crinkliness_mode"] = mode
    f = _StubCrink(conf, dict(COST_DEFAULTS))
    f._stub = stub
    return f, _leaf(type_)


def test_crinkliness_mode_defaults_to_urb_and_reproduces_hard_zero():
    """Default must be byte-identical to stock Urb: buried leaf -> exactly 0.0."""
    f, leaf = _stub_fit()
    assert f._crinkliness_mode == "urb"
    assert f.quality_uncrinkliness(leaf, None, {}) == 0.0


def test_crinkliness_floor_restores_gradient_but_keeps_the_failure():
    """The floor must stay BELOW FAIL_THRESHOLD: it restores a value gradient
    without silently deleting a whole fail category."""
    f, leaf = _stub_fit("floor")
    q = f.quality_uncrinkliness(leaf, None, {})
    assert q > 0.0, "buried leaf should no longer be worth exactly nothing"
    assert q < FAIL_THRESHOLD, "buried leaf must still emit its crinkliness fail"


def test_crinkliness_compact_ok_clips_on_the_compact_side_only():
    """Being more compact than target is not a defect; being over-exposed is."""
    target = CONF_DEFAULTS["uncrinkliness"][0]
    # 1/crink > target  =>  more compact than target  =>  clipped to 1.0
    f, leaf = _stub_fit("compact_ok", stub=1.0 / (target * 2))
    assert f.quality_uncrinkliness(leaf, None, {}) == 1.0
    # 1/crink < target  =>  over-exposed  =>  still decays
    f, leaf = _stub_fit("compact_ok", stub=1.0 / (target / 2))
    assert f.quality_uncrinkliness(leaf, None, {}) < 1.0


def test_crinkliness_exempt_circulation_only_exempts_circulation():
    f, circ = _stub_fit("exempt_circulation", type_="C")
    assert f.quality_uncrinkliness(circ, None, {}) == 1.0
    f, room = _stub_fit("exempt_circulation", type_="t1")
    assert f.quality_uncrinkliness(room, None, {}) == 0.0


def test_crinkliness_compact_ok_scores_the_buried_limit_as_compact():
    """Regression (§38.8): a zero-exposure leaf IS the compact limit.

    The first `compact_ok` returned the floor here, i.e. it announced that
    being compact is not a defect and then punished the most compact case of
    all hardest -- which is why it measured inert on buried leaves.
    """
    f, leaf = _stub_fit("compact_ok", stub=0.0)
    assert f.quality_uncrinkliness(leaf, None, {}) == 1.0


# --------------------------------------------------------------------------- #
# homemaker-py-ssz / DESIGN.md §38.10 — per-space crinkliness (the SHIPPING fix)
#
# The compact side of the crinkliness gaussian IS the daylight requirement, so
# a space declares it in its own `crinkliness:` target, like `size:` or
# `width:`. There is no separate daylight attribute -- see §38.9 for why
# keying it off `usage:` (an ACCESS class) was wrong.
# --------------------------------------------------------------------------- #
def _declared_fit(stub, space=None, conf_extra=None, code="x1"):
    """Stub Fitness with a one-space programme, optionally declaring
    `crinkliness:`, so `crinkliness_params` resolves off real config."""
    conf = dict(CONF_DEFAULTS)
    conf["spaces"] = {code: dict({"usage": "living", "size": [4.0, 1.0]},
                                 **(space or {}))}
    conf.update(conf_extra or {})
    f = _StubCrink(conf, dict(COST_DEFAULTS))
    f._stub = stub
    return f, _leaf(code)


def test_declared_crinkliness_absent_keeps_stock_behaviour():
    """No `crinkliness:` key -> the global target, unchanged: buried = 0.0.

    This is what makes the mechanism backward compatible -- shipping it
    changes no score until a config actually declares something.
    """
    f, leaf = _declared_fit(0.0)
    assert f.crinkliness_params(leaf) == tuple(CONF_DEFAULTS["uncrinkliness"])
    assert f.quality_uncrinkliness(leaf, None, {}) == 0.0


def test_declared_crinkliness_none_lets_a_space_be_buried():
    """`crinkliness: none` says this space needs no window. Fully buried --
    the compact limit -- is then not a defect."""
    f, leaf = _declared_fit(0.0, {"crinkliness": None})
    assert f.crinkliness_params(leaf) is None
    assert f.quality_uncrinkliness(leaf, None, {}) == 1.0


def test_declared_crinkliness_none_accepts_the_literal_string():
    """`crinkliness: none` reads the same as a YAML null, so the corpus can
    spell it the way it spells `usage: none`."""
    f, leaf = _declared_fit(0.0, {"crinkliness": "none"})
    assert f.crinkliness_params(leaf) is None
    assert f.quality_uncrinkliness(leaf, None, {}) == 1.0


def test_declared_crinkliness_none_still_penalises_over_exposure():
    """Needing no window is not exemption from envelope cost. The factor is
    clipped on the compact side only, never switched off -- a crinkly store
    still costs wall."""
    target = CONF_DEFAULTS["uncrinkliness"][0]
    f, leaf = _declared_fit(1.0 / (target / 2), {"crinkliness": None})
    assert f.quality_uncrinkliness(leaf, None, {}) < 1.0


def test_declared_crinkliness_pair_is_used_verbatim():
    """A space may instead ask for its own target, as it does for size."""
    f, leaf = _declared_fit(0.0, {"crinkliness": [2.0, 0.5]})
    assert f.crinkliness_params(leaf) == (2.0, 0.5)
    assert f.quality_uncrinkliness(leaf, None, {}) == 0.0  # still wants light


def test_circulation_target_is_separately_declarable():
    """A generic corridor takes `uncrinkliness_circulation`, and that key can
    say `none` -- an internal corridor with no windows is ordinary
    architecture, not a failure (this was 63% of the phantom fails, §38.10)."""
    f, _ = _declared_fit(0.0, conf_extra={"uncrinkliness_circulation": None})
    assert f.crinkliness_params(_leaf("C")) is None
    assert f.quality_uncrinkliness(_leaf("C"), None, {}) == 1.0
    # a room is untouched by the circulation key
    f2, room = _declared_fit(0.0, conf_extra={"uncrinkliness_circulation": None})
    assert f2.quality_uncrinkliness(room, None, {}) == 0.0


def test_circulation_keeps_its_pair_when_declared():
    f, _ = _declared_fit(0.0, conf_extra={"uncrinkliness_circulation": [1.0, 0.3]})
    assert f.crinkliness_params(_leaf("C")) == (1.0, 0.3)


def test_crinkliness_mode_unknown_raises():
    with pytest.raises(ValueError, match="crinkliness_mode"):
        _stub_fit("nonsense")


# --------------------------------------------------------------------------- #
# homemaker-py-2v1 / DESIGN.md §39.8 — connectivity_weight (EXPERIMENTAL, NULL)
# --------------------------------------------------------------------------- #
def test_connectivity_weight_defaults_to_flat_rule():
    """Default must reproduce the flat 0.5^n penalty exactly."""
    assert Fitness(conf={})._connectivity_weight == 1.0


def test_connectivity_weight_auto_is_derived_from_the_value_gap():
    """Not a magic number: the smallest w making 0.5^w < value_circulation /
    value_inside, so it tracks the rates if either is retuned."""
    from homemaker_layout.fitness import connectivity_weight_for
    assert connectivity_weight_for(300.0, 50.0) == 3.0     # 0.5^3 < 1/6 < 0.5^2
    assert connectivity_weight_for(100.0, 100.0) == 1.0    # no gap, no extra weight
    assert connectivity_weight_for(400.0, 50.0) == 3.0     # 1/8 -> exactly 3
    assert Fitness(conf={"connectivity_weight": "auto"})._connectivity_weight == 3.0


def test_is_connectivity_fail_matches_both_strings():
    from homemaker_layout.fitness import is_connectivity_fail
    assert is_connectivity_fail("level 0 not connected")
    assert is_connectivity_fail("1 inaccessible usable space")
    assert not is_connectivity_fail("0/llr crinkliness")
    assert not is_connectivity_fail("missing required space: b1")