"""Bounded adapter regressions; fixtures are self-contained, with no corpus/audit files read. The 21 source boxes below are the complete retained >2 cm error examples in the 2026-09-27 adapter evidence (11 Structured3D, 8 HSSD200, 2 MultiScan). """ import copy import csv import io import itertools import json import math from types import SimpleNamespace from unittest.mock import patch import numpy as np import pytest from fastfill.adapters import hssd200, interiorgs, multiscan, structured3d from fastfill.adapters.unified import convert_room from fastfill.build import prep AUDITED_BOXES = [('Structured3D', 'structured3d_00160_room_584/50', {'category': 'unknown', 'instance_id': 50, 'position': {'x': 1.516548, 'y': 0.92628, 'z': 0.4325}, 'raw_basis': [[-0.9999999999999962, 8.742277644230737e-08, 0.0], [3.8213709261743826e-15, 4.3711388286737763e-08, -0.9999999999999991], [-8.742277644230729e-08, -0.9999999999999953, -4.3711388175715626e-08]], 'raw_coeffs': [208.00000000000077, 32.50000365650003, 598.0000000000028]}), ('Structured3D', 'structured3d_00393_room_584/67', {'category': 'unknown', 'instance_id': 67, 'position': {'x': 1.305684, 'y': 0.087636, 'z': 0.4325}, 'raw_basis': [[-0.9999999999999962, 8.742278110047815e-08, 0.0], [3.821371129789495e-15, 4.3711388286737763e-08, -0.9999999999999991], [-8.742278110047807e-08, -0.9999999999999953, -4.3711388175715626e-08]], 'raw_coeffs': [209.00000000000077, 32.50000365650003, 548.0000000000027]}), ('Structured3D', 'structured3d_01159_room_232/100', {'category': 'table', 'instance_id': 100, 'position': {'x': 0.44347, 'y': -2.189658, 'z': 0.3155}, 'raw_basis': [[4.371139006309477e-08, 3.821370999999997e-15, -0.9999999999999991], [8.742277999999968e-08, -0.999999999999996, 2.2499312661442353e-22], [-0.9999999999999953, -8.742277999999959e-08, -4.3711389952072466e-08]], 'raw_coeffs': [35.00000000000003, 18.75000000000007, 12.452050000000058]}), ('Structured3D', 'structured3d_02687_room_670/53', {'category': 'unknown', 'instance_id': 53, 'position': {'x': -0.730234, 'y': -1.066933, 'z': 0.3145}, 'raw_basis': [[1.0, 0.0, 0.0], [0.0, -4.371138828673793e-08, -0.9999999999999991], [-0.0, 0.9999999999999991, -4.3711388175715626e-08]], 'raw_coeffs': [223.5, 32.50000365650003, 336.00000000000034]}), ('Structured3D', 'structured3d_02687_room_670/54', {'category': 'unknown', 'instance_id': 54, 'position': {'x': -0.330234, 'y': -1.066933, 'z': 0.3145}, 'raw_basis': [[1.0, 0.0, 0.0], [0.0, -4.371138828673793e-08, -0.9999999999999991], [-0.0, 0.9999999999999991, -4.3711388175715626e-08]], 'raw_coeffs': [173.5, 32.50000365650003, 336.00000000000034]}), ('Structured3D', 'structured3d_02687_room_670/55', {'category': 'unknown', 'instance_id': 55, 'position': {'x': 0.019766, 'y': -1.066933, 'z': 0.3145}, 'raw_basis': [[1.0, 0.0, 0.0], [0.0, -4.371138828673793e-08, -0.9999999999999991], [-0.0, 0.9999999999999991, -4.3711388175715626e-08]], 'raw_coeffs': [173.5, 32.50000365650003, 336.00000000000034]}), ('Structured3D', 'structured3d_03087_room_332351/56', {'category': 'bed', 'instance_id': 56, 'position': {'x': 1.063394, 'y': 1.34462, 'z': 0.3805}, 'raw_basis': [[1.9984014443252818e-15, 4.371138999999996e-08, -0.9999999999999991], [0.9999999999999991, -4.37113899041451e-08, 0.0], [-4.3711389793122756e-08, -0.9999999999999981, -4.371139e-08]], 'raw_coeffs': [90.66900000000008, 12.37120000000001, 15.869400000000033]}), ('Structured3D', 'structured3d_03155_room_309/16', {'category': 'table', 'instance_id': 16, 'position': {'x': -0.60826, 'y': 4.415584, 'z': 0.2747}, 'raw_basis': [[-3.3306690738754696e-15, -4.371138999999996e-08, -0.9999999999999991], [-0.9999999999999972, 7.549789999487077e-08, -1.1102230246251565e-16], [7.549789999487071e-08, 0.9999999999999962, -4.3711390000000065e-08]], 'raw_coeffs': [35.00000000000003, 18.750000000000053, 12.452050000000046]}), ('Structured3D', 'structured3d_03356_room_584/129', {'category': 'table', 'instance_id': 129, 'position': {'x': 2.124656, 'y': -1.657159, 'z': 0.4325}, 'raw_basis': [[-4.371139117331779e-08, 0.9999999999999992, 0.0], [4.3711388286737896e-08, 1.9106855776612683e-15, -0.9999999999999991], [-0.9999999999999983, -4.3711390840250886e-08, -4.3711388175715626e-08]], 'raw_coeffs': [209.0000000000002, 32.50000365650003, 273.0000000000005]}), ('Structured3D', 'structured3d_03356_room_584/133', {'category': 'unknown', 'instance_id': 133, 'position': {'x': 1.409656, 'y': -0.555107, 'z': 0.4325}, 'raw_basis': [[-4.371139117331779e-08, -0.9999999999999992, 0.0], [-4.3711388286737896e-08, 1.9106855776612683e-15, -0.9999999999999991], [0.9999999999999983, -4.3711390840250886e-08, -4.3711388175715626e-08]], 'raw_coeffs': [209.0000000000002, 32.50000365650003, 438.00000000000097]}), ('Structured3D', 'structured3d_03356_room_584/139', {'category': 'unknown', 'instance_id': 139, 'position': {'x': 1.409656, 'y': -1.657159, 'z': 0.4325}, 'raw_basis': [[-4.371139117331779e-08, 0.9999999999999992, 0.0], [4.3711388286737896e-08, 1.9106855776612683e-15, -0.9999999999999991], [-0.9999999999999983, -4.3711390840250886e-08, -4.3711388175715626e-08]], 'raw_coeffs': [209.0000000000002, 32.50000365650003, 438.00000000000097]}), ('HSSD200', 'HSSD200:102816627:3/102816627:267', {'category': 'book', 'scene_id': '102816627', 'instance_id': '267', 'obb_center': '[3.546474, 0.121647, -1.923595]', 'obb_half_extents': '[0.047279, 0.12895, 0.102077]', 'obb_rotation_wxyz': '[0.65328163, 0.6532815, -0.27059783, -0.27059788]'}), ('HSSD200', 'HSSD200:102816627:3/102816627:309', {'category': 'book', 'scene_id': '102816627', 'instance_id': '309', 'obb_center': '[3.546474, 1.921797, -1.923595]', 'obb_half_extents': '[0.047279, 0.12895, 0.102077]', 'obb_rotation_wxyz': '[0.65328163, 0.6532815, -0.27059783, -0.27059788]'}), ('HSSD200', 'HSSD200:103997781_171030978:3/103997781_171030978:185', {'category': 'book', 'scene_id': '103997781_171030978', 'instance_id': '185', 'obb_center': '[-2.296859, 0.115267, -4.154386]', 'obb_half_extents': '[0.044784, 0.12895, 0.09669]', 'obb_rotation_wxyz': '[0.65407459, 0.65248737, -0.27139045, -0.26980341]'}), ('HSSD200', 'HSSD200:104348082_171512994:0/104348082_171512994:150', {'category': 'book', 'scene_id': '104348082_171512994', 'instance_id': '150', 'obb_center': '[-9.489737, 0.149516, -1.599131]', 'obb_half_extents': '[0.0562, 0.104913, 0.121338]', 'obb_rotation_wxyz': '[0.60044965, 0.31731935, 0.21637841, -0.70139078]'}), ('HSSD200', 'HSSD200:104862501_172226556:5/104862501_172226556:165', {'category': 'book', 'scene_id': '104862501_172226556', 'instance_id': '165', 'obb_center': '[-4.624166, 0.121647, 4.894016]', 'obb_half_extents': '[0.047279, 0.12895, 0.102077]', 'obb_rotation_wxyz': '[0.65328142, 0.2705982, 0.27059834, -0.65328136]'}), ('HSSD200', 'HSSD200:104862501_172226556:5/104862501_172226556:207', {'category': 'book', 'scene_id': '104862501_172226556', 'instance_id': '207', 'obb_center': '[-3.159476, 0.121647, -0.588035]', 'obb_half_extents': '[0.047279, 0.12895, 0.102077]', 'obb_rotation_wxyz': '[0.65328163, 0.6532815, -0.27059783, -0.27059788]'}), ('HSSD200', 'HSSD200:106879005_174887124:4/106879005_174887124:98', {'category': 'roof', 'scene_id': '106879005_174887124', 'instance_id': '98', 'obb_center': '[-5.67073, 3.956208, -6.830123]', 'obb_half_extents': '[6.5, 0.55117, 2.749985]', 'obb_rotation_wxyz': '[0.97029571, -0.24192195, 0.0, 0.0]'}), ('HSSD200', 'HSSD200:107734158_175999998:14/107734158_175999998:448', {'category': 'book', 'scene_id': '107734158_175999998', 'instance_id': '448', 'obb_center': '[-9.930676, 0.157266, -2.633861]', 'obb_half_extents': '[0.060269, 0.12895, 0.130123]', 'obb_rotation_wxyz': '[-0.21313372, -0.70393206, 0.59736535, -0.31970036]'}), ('MultiScan', 'MultiScan::scene_00029_01/o43', {'category': 'bag', 'object_id': '43', 'obb_center': '[-2.216006052445697, -3.198990954172932, -2.0838447429477776]', 'obb_axes': '[-0.9391466459853527, 0.34151555401180256, -0.03702301584790649, 0.2533428178007576, ' '0.6157978529307632, -0.7460632821648807, -0.23199352146824048, -0.7100423442963621, ' '-0.6648450009610445]', 'obb_half_extents': '[0.2190989368345001, 0.2549238904394131, 0.1397719718865565]', 'front': '[0.23199352146824054, 0.7100423442963623, 0.6648450009610446]', 'is_architectural': 'False', 'is_opening': 'False'}), ('MultiScan', 'MultiScan::scene_00109_04/o31', {'category': 'backpack', 'object_id': '31', 'obb_center': '[0.6333183612225775, 1.7997251504673377, -0.9412570338535274]', 'obb_axes': '[-0.9961946980917455, -0.022557566113149824, -0.0841859828293692, -0.08715574274765812, ' '0.25783416049629937, 0.9622501868990583, -2.7755575615628914e-17, 0.9659258262890683, ' '-0.2588190451025206]', 'obb_half_extents': '[0.19922853225692852, 0.20651165445598438, 0.11010368672622178]', 'front': '[2.7755575615628914e-17, -0.9659258262890683, 0.2588190451025206]', 'is_architectural': 'False', 'is_opening': 'False'})] def rotation(yaw, roll=0, pitch=0): c, s = math.cos(yaw), math.sin(yaw) a, b = math.cos(roll), math.sin(roll) d, e = math.cos(pitch), math.sin(pitch) return np.array([[c, -s, 0], [s, c, 0], [0, 0, 1]]) @ np.array( [[1, 0, 0], [0, a, -b], [0, b, a]]) @ np.array([[d, 0, e], [0, 1, 0], [-e, 0, d]]) def quaternion_matrix(q): # Independent vector/quaternion formula, applied to the three basis vectors. w, v = q[0], np.asarray(q[1:]) return np.column_stack([e + 2 * np.cross(v, w * e + np.cross(v, e)) for e in np.eye(3)]) def corners(R, size, center): return np.asarray(list(itertools.product((-0.5, 0.5), repeat=3))) * size @ R.T + center def pose(f): return (np.array([f['furniture_size'][k] for k in ('width', 'length', 'height')]), np.array([f['furniture_position'][k] for k in 'xyz']), math.radians(f['furniture_rotation']['z'])) def assert_envelope(f, points, center_z): size, pos, yaw = pose(f) local = (points - pos) @ rotation(yaw) expected_lo = -size / 2 if center_z else np.array([-size[0] / 2, -size[1] / 2, 0]) np.testing.assert_allclose(local.min(0), expected_lo, atol=1e-8) np.testing.assert_allclose(local.max(0), expected_lo + size, atol=1e-8) @pytest.mark.parametrize('source,uid,raw', AUDITED_BOXES, ids=[r[1] for r in AUDITED_BOXES]) def test_all_audited_retained_boxes_enclose_rotated_corners(source, uid, raw): before = copy.deepcopy(raw) if source == 'Structured3D': f = structured3d._furniture(raw) R, size = np.asarray(raw['raw_basis']).T, 2 * np.abs(raw['raw_coeffs']) / 1000 center = np.array([raw['position'][k] for k in 'xyz']) elif source == 'HSSD200': f = hssd200._furniture(raw, 0) R = hssd200.T @ quaternion_matrix(json.loads(raw['obb_rotation_wxyz'])) size = 2 * np.asarray(json.loads(raw['obb_half_extents'])) center = hssd200.T @ np.asarray(json.loads(raw['obb_center'])) else: f = multiscan.box(raw) R = np.asarray(json.loads(raw['obb_axes'])).reshape(3, 3).T size = 2 * np.asarray(json.loads(raw['obb_half_extents'])) center = np.asarray(json.loads(raw['obb_center'])) assert_envelope(f, corners(R, size, center), source != 'MultiScan') assert raw == before def source_row(source, R, size, center, category='table', identity='1'): """Encode one semantic-front X / up Z box in each source's actual axis convention.""" if source == 'Structured3D': return {'category': category, 'instance_id': identity, 'position': dict(zip('xyz', center)), 'raw_basis': [R[:, 1].tolist(), (-R[:, 0]).tolist(), R[:, 2].tolist()], 'raw_coeffs': (np.asarray(size)[[1, 0, 2]] * 500).tolist()} C = R[:, [1, 2, 0]] # asset +Z front, +Y up row = {'category': category, 'obb_half_extents': json.dumps((np.asarray(size)[[1, 2, 0]] / 2).tolist())} if source == 'HSSD200': M = hssd200.T.T @ C w = math.sqrt(1 + np.trace(M)) / 2 q = [w, (M[2, 1] - M[1, 2]) / (4 * w), (M[0, 2] - M[2, 0]) / (4 * w), (M[1, 0] - M[0, 1]) / (4 * w)] return {**row, 'scene_id': 'synthetic', 'instance_id': identity, 'obb_center': json.dumps((hssd200.T.T @ center).tolist()), 'obb_rotation_wxyz': json.dumps(q)} return {**row, 'object_id': identity, 'obb_center': json.dumps(list(center)), 'obb_axes': json.dumps(C.T.flatten().tolist()), 'front': json.dumps(R[:, 0].tolist()), 'is_architectural': 'False', 'is_opening': 'False'} def furniture(source, row, floor=0): if source == 'Structured3D': return structured3d._furniture(row) if source == 'HSSD200': return hssd200._furniture(row, floor) return multiscan.box(row) @pytest.mark.parametrize('source', ['Structured3D', 'HSSD200', 'MultiScan']) @pytest.mark.parametrize('yaw', [-1.2, 0.7, 2.1]) def test_tilt_preserves_horizontal_front_and_exact_center(source, yaw): R, size, center = rotation(yaw, 0.4), np.array([1.4, 0.8, 0.5]), np.array([10., 20., 2.]) f = furniture(source, source_row(source, R, size, center)) assert_envelope(f, corners(R, size, center), source != 'MultiScan') assert math.cos(pose(f)[2] - yaw) == pytest.approx(1) assert f['furniture_rotation']['x'] != 0 assert f.get('front_known') is not False @pytest.mark.parametrize('source', ['Structured3D', 'HSSD200', 'MultiScan']) def test_upright_known_front_unchanged(source): R, size, center = rotation(0.7), np.array([1.4, 0.8, 0.5]), np.array([10., 20., 2.]) f = furniture(source, source_row(source, R, size, center)) assert_envelope(f, corners(R, size, center), source != 'MultiScan') np.testing.assert_allclose(pose(f)[0], size) assert pose(f)[2] == pytest.approx(0.7) assert f['furniture_rotation']['x'] == 0 @pytest.mark.parametrize('source', ['Structured3D', 'MultiScan']) def test_vertical_front_has_geometry_but_no_claimed_heading(source): R = rotation(0.7, pitch=math.pi / 2) size, center = np.array([1.4, 0.8, 0.5]), np.array([10., 20., 2.]) f = furniture(source, source_row(source, R, size, center)) assert_envelope(f, corners(R, size, center), source != 'MultiScan') assert f.get('front_known') is False or f.get('front_vertical') is True ARGS = SimpleNamespace(boundary_types=['polygon', 'hull'], source_anchors={}, anchors=['floor', 'object'], min_objects=1, max_vertices=0, oob_tol=.1, hidden_max=.3, reject_flagged=[]) def test_hssd_floor_origin_and_support_use_true_envelope(): R, size, floor = rotation(.7, .4), np.array([1.4, .8, .5]), 7.25 height = np.ptp(corners(R, size, np.zeros(3))[:, 2]) table = hssd200._furniture(source_row('HSSD200', R, size, np.array([12., 22., floor + height / 2])), floor) book = hssd200._furniture(source_row('HSSD200', rotation(.7), np.array([.2, .2, .1]), np.array([12., 22., floor + height + .05]), 'book', '2'), floor) room = {'room_id': 'r', 'room_boundary': [[10, 20], [15, 20], [15, 25], [10, 25]], 'room_height': 3, 'furniture': [table, book]} ir = convert_room(room, source='HSSD200', uid='r', group='g', boundary_type='polygon', center_z=True, meta={'front_known': True}) assert ir['objects'][0]['pos'] == pytest.approx([2, 2, 0]) built, why = prep(ir, ARGS) assert why is None child = next(o for o in built['objects'] if o['id'] == 'synthetic:2') assert child['anchor'] == 'object' and child['parent'] == 'synthetic:1' assert child['pos'][2] == round(height, 2) def test_structured_false_floor_obstacle_is_removed_after_preparation(): raw = AUDITED_BOXES[0][2] # structured3d_00160_room_584 / instance 50 chair = source_row('Structured3D', rotation(0), np.array([.6, .6, 1.]), np.array([6., 6., .5]), 'chair', 'control') record = {'sample_id': 'bounded', 'provenance': {'source_house_id': 'test', 'split': 'train'}, 'room_origin_house_m': [0, 0, 0], 'room_context': {'room_id': 'r', 'room_type': 'office', 'ceiling_height_m': 3, 'floor_polygon': [[0, 0], [10, 0], [10, 10], [0, 10]]}, 'layout': {'floor_layout': {'objects': [raw, chair]}}} ir = structured3d.convert(record) false_obstacle = ir['objects'][0] assert false_obstacle['pos'][2] == pytest.approx(.4, abs=1e-6) assert false_obstacle['size'][2] == pytest.approx(.065, abs=1e-6) assert false_obstacle['front_known'] is False built, why = prep(ir, ARGS) assert why is None assert [o['id'] for o in built['objects']] == ['control'] assert not built['fixed'] def csv_stream(rows): stream = io.StringIO() writer = csv.DictWriter(stream, fieldnames=list(rows[0])) writer.writeheader() writer.writerows(rows) stream.seek(0) return stream def test_hssd_load_keeps_tilt_envelope_floor_and_front_metadata(): floor = 7.25 R, size = rotation(.7, .4), np.array([1.4, .8, .5]) height = np.ptp(corners(R, size, np.zeros(3))[:, 2]) center = np.array([12., 22., floor + height / 2]) raw = source_row('HSSD200', R, size, center) row = {**raw, 'instance_kind': 'rigid', 'bbox_source': 'mesh', 'region_id': '0', 'region_source': 'inside', 'is_architectural': 'False', 'aabb_max': json.dumps((corners(R, size, center) @ hssd200.T).max(0).tolist())} region = {'scene_id': 'synthetic', 'region_id': '0', 'room_type': 'office', 'region_name': 'test', 'poly_loop_xz': '[[10,-20],[15,-20],[15,-25],[10,-25]]', 'floor_height': floor, 'ceiling_height': floor + 3, 'extrusion_height': 3} files = {'objects.csv': [row], 'regions.csv': [region], 'asset_catalog.csv': [{'template_name': 'unused', 'local_bbox_min': ''}]} with patch('builtins.open', side_effect=lambda path: csv_stream(files[path.rsplit('/', 1)[-1]])): ir, = hssd200.load('unused') obj, = ir['objects'] assert obj['pos'] == pytest.approx([2, 2, 0]) assert obj['yaw'] == pytest.approx(.7) assert obj['size'][2] == pytest.approx(height) assert obj['tilted'] and 'rot_wxyz_yup' in obj assert ir['meta']['floor_height'] == floor def test_multiscan_load_uses_source_floor_and_propagates_unknown_front(): floor, R, size = -3.25, rotation(.7, pitch=math.pi / 2), np.array([.8, .6, .4]) row = {**source_row('MultiScan', R, size, np.array([12., 22., floor + .4])), 'scan_id': 'scene_9_0', 'aabb_min': json.dumps([11, 21, floor])} files = {'objects.csv': [row], 'relations.csv': [{'scan_id': 'scene_9_0', 'subject_id': '1', 'relation': 'rests_on_floor'}], 'scans.csv': [{'scan_id': 'scene_9_0', 'scene_id': 'scene_9', 'room_type': 'office', 'device': 'test'}], 'regions.csv': [{'scan_id': 'scene_9_0', 'floor_height': floor + .2, 'ceiling_height': floor + 3, 'height_reliable': 'True', 'poly_source': 'floor', 'wall_segments': '[]', 'poly_loop': '[[10,20],[15,20],[15,25],[10,25]]'}]} with patch('builtins.open', side_effect=lambda path: csv_stream(files[path.rsplit('/', 1)[-1]])): ir, = multiscan.load('unused') assert ir['height'] == 3 assert ir['meta']['floor_z'] == floor assert ir['objects'][0]['pos'] == pytest.approx([2, 2, 0]) assert ir['objects'][0].get('front_known') is False def interior_box(identity, xy, category='chair'): pts = [[xy[0] + x, xy[1] + y, z] for z in (0., 1.) for x, y in ((.2, -.2), (-.2, -.2), (-.2, .2), (.2, .2))] return {'furniture_category': category, 'furniture_instance_id': identity, 'furniture_position': {'x': 999, 'y': 999, 'z': 999}, 'source_fields': {'bounding_box': [dict(zip('xyz', p)) for p in pts]}} def interior_room(identity, ring, furn=()): return {'room_id': identity, 'room_boundary': ring, 'room_height': 3, 'furniture': list(furn)} def load_interior(scene): with patch.object(interiorgs, 'iter_records', return_value=iter([scene])): return list(interiorgs.load('unused')) def test_interior_recovers_only_unique_bbox_centers_without_mutating_assignments(): # Repeated closing/zero-length edges triggered the upstream ray-cast defect. left = [[10, 20], [12, 20], [12, 22], [10, 22], [10, 22], [10, 20]] right = [[12, 20], [14, 20], [14, 22], [12, 22]] original = interior_box('already', [11, 21]) candidates = [interior_box('left', [11.5, 21]), interior_box('right', [13, 21]), interior_box('shared', [12, 21]), interior_box('outside', [100, 100]), interior_box('already', [13, 21]), {**interior_box('invalid', [11, 21]), 'source_fields': {'bounding_box': []}}] scene = {'scene_id': 'arbitrary-house', 'rooms': [interior_room('west', left, [original]), interior_room('east', right)], 'unassigned_objects': candidates} before = copy.deepcopy(scene) rooms = load_interior(scene) assert [[o['id'] for o in r['objects']] for r in rooms] == [['already', 'left'], ['right']] assert rooms[0]['objects'][1]['pos'] == pytest.approx([1.5, 1, 0]) recovery = rooms[0]['meta']['membership_recovery'] assert recovery['scene_recovered'] == 2 assert recovery['scene_unresolved'] == {'ambiguous': ['shared'], 'outside': ['outside'], 'invalid_bbox': ['invalid']} assert recovery['scene_already_assigned'] == ['already'] assert scene == before assert all(prep(room, ARGS)[1] is None for room in rooms) def test_interior_does_not_pick_first_overlapping_room_or_nearest_room(): ring = [[0, 0], [4, 0], [4, 4], [0, 4]] scene = {'scene_id': 'overlap', 'rooms': [interior_room('a', ring), interior_room('b', ring)], 'unassigned_objects': [interior_box('both', [1, 1]), interior_box('neither', [5, 5])]} for r in load_interior(scene): assert not r['objects'] assert r['meta']['membership_recovery']['scene_unresolved'] == { 'ambiguous': ['both'], 'outside': ['neither']} @pytest.mark.parametrize('bad', [None, [], [[0, 0], [1, 1], [1, 0], [0, 1]]]) def test_interior_invalid_boundary_prevents_unproven_unique_assignment(bad): scene = {'scene_id': 'bad-ring', 'rooms': [interior_room('valid', [[0, 0], [4, 0], [4, 4], [0, 4]]), interior_room('invalid', bad)], 'unassigned_objects': [interior_box('uncertain', [1, 1])]} for r in load_interior(scene): assert not r['objects'] assert r['meta']['membership_recovery']['scene_unresolved'] == {'invalid_boundary': ['uncertain']} def test_interior_duplicate_unassigned_ids_stay_unresolved(): scene = {'scene_id': 'duplicate', 'rooms': [interior_room('a', [[0, 0], [4, 0], [4, 4], [0, 4]])], 'unassigned_objects': [interior_box('repeat', [1, 1]), interior_box('repeat', [2, 2])]} r, = load_interior(scene) assert not r['objects'] assert r['meta']['membership_recovery']['scene_unresolved'] == {'duplicate_id': ['repeat', 'repeat']} def test_interior_assigned_only_scene_is_unchanged(): room = interior_room('a', [[10, 20], [14, 20], [14, 24], [10, 24]], [interior_box('kept', [12, 22])]) scene = {'scene_id': 'stable', 'rooms': [room]} ir, = load_interior(scene) assert ir == load_interior({**scene, 'unassigned_objects': []})[0] assert 'membership_recovery' not in ir['meta'] assert ir['objects'][0]['pos'] == pytest.approx([2, 2, 0]) assert len(ir['objects']) == 1