import numpy as np
import pytest
import open3d as o3d
from scipy.spatial.transform import Rotation
from aruco.icp_registration import (
    ICPConfig,
    ICPResult,
    ICPMetrics,
    extract_near_floor_band,
    compute_overlap_xz,
    apply_gravity_constraint,
    pairwise_icp,
    build_pose_graph,
    refine_with_icp,
)
from aruco.ground_plane import FloorPlane


def test_extract_near_floor_band_basic():
    points = np.array(
        [[0, -0.1, 0], [0, 0.1, 0], [0, 0.2, 0], [0, 0.4, 0]], dtype=np.float64
    )

    floor_y = 0.0
    band_height = 0.3
    floor_normal = np.array([0, 1, 0], dtype=np.float64)

    result = extract_near_floor_band(points, floor_y, band_height, floor_normal)
    assert len(result) == 2
    assert np.all(result[:, 1] >= 0)
    assert np.all(result[:, 1] <= 0.3)


def test_extract_near_floor_band_empty():
    points = np.zeros((0, 3))
    result = extract_near_floor_band(points, 0.0, 0.3, np.array([0, 1, 0]))
    assert len(result) == 0


def test_extract_near_floor_band_all_in():
    points = np.random.uniform(0, 0.2, (100, 3))
    points[:, 1] = np.random.uniform(0.05, 0.25, 100)
    result = extract_near_floor_band(points, 0.0, 0.3, np.array([0, 1, 0]))
    assert len(result) == 100


def test_compute_overlap_xz_full():
    points_a = np.array([[0, 0, 0], [1, 0, 1]])
    points_b = np.array([[0, 0, 0], [1, 0, 1]])
    area = compute_overlap_xz(points_a, points_b)
    assert abs(area - 1.0) < 1e-6


def test_compute_overlap_xz_no():
    points_a = np.array([[0, 0, 0], [1, 0, 1]])
    points_b = np.array([[2, 0, 2], [3, 0, 3]])
    area = compute_overlap_xz(points_a, points_b)
    assert area == 0.0


def test_compute_overlap_xz_partial():
    points_a = np.array([[0, 0, 0], [1, 0, 1]])
    points_b = np.array([[0.5, 0, 0.5], [1.5, 0, 1.5]])
    area = compute_overlap_xz(points_a, points_b)
    assert abs(area - 0.25) < 1e-6


def test_compute_overlap_xz_with_margin():
    points_a = np.array([[0, 0, 0], [1, 0, 1]])
    points_b = np.array([[1.2, 0, 0], [2.2, 0, 1]])
    area_no_margin = compute_overlap_xz(points_a, points_b)
    area_with_margin = compute_overlap_xz(points_a, points_b, margin=0.5)
    assert area_no_margin == 0.0
    assert area_with_margin > 0.0


def test_apply_gravity_constraint_identity():
    T = np.eye(4)
    result = apply_gravity_constraint(T, T)
    np.testing.assert_allclose(result, T, atol=1e-6)


def test_apply_gravity_constraint_preserves_yaw():
    T_orig = np.eye(4)
    R_icp = Rotation.from_euler("xyz", [0, 10, 0], degrees=True).as_matrix()
    T_icp = np.eye(4)
    T_icp[:3, :3] = R_icp

    result = apply_gravity_constraint(T_icp, T_orig, penalty_weight=10.0)

    res_euler = Rotation.from_matrix(result[:3, :3]).as_euler("xyz", degrees=True)
    assert abs(res_euler[1] - 10.0) < 1e-6
    assert abs(res_euler[0]) < 1e-6
    assert abs(res_euler[2]) < 1e-6


def test_apply_gravity_constraint_regularizes_pitch_roll():
    T_orig = np.eye(4)
    R_icp = Rotation.from_euler("xyz", [10, 0, 10], degrees=True).as_matrix()
    T_icp = np.eye(4)
    T_icp[:3, :3] = R_icp

    result = apply_gravity_constraint(T_icp, T_orig, penalty_weight=9.0)

    res_euler = Rotation.from_matrix(result[:3, :3]).as_euler("xyz", degrees=True)
    assert abs(res_euler[0] - 1.0) < 1e-2
    assert abs(res_euler[2] - 1.0) < 1e-2


def create_box_pcd(size=1.0, num_points=500, seed=42):
    rng = np.random.default_rng(seed)
    points = rng.uniform(0, size, (num_points, 3))
    pcd = o3d.geometry.PointCloud()
    pcd.points = o3d.utility.Vector3dVector(points)
    return pcd


def test_pairwise_icp_identity():
    pcd = create_box_pcd()
    config = ICPConfig(min_fitness=0.1)
    result = pairwise_icp(pcd, pcd, config, np.eye(4))

    assert result.converged
    assert result.fitness > 0.9
    np.testing.assert_allclose(result.transformation, np.eye(4), atol=1e-3)


def test_pairwise_icp_known_transform():
    source = create_box_pcd()
    T_true = np.eye(4)
    T_true[:3, :3] = Rotation.from_euler("y", 5, degrees=True).as_matrix()
    T_true[:3, 3] = [0.05, 0, 0.02]

    target = o3d.geometry.PointCloud()
    target.points = o3d.utility.Vector3dVector(
        (np.asarray(source.points) @ T_true[:3, :3].T) + T_true[:3, 3]
    )

    config = ICPConfig(min_fitness=0.5, voxel_size=0.01)
    result = pairwise_icp(source, target, config, np.eye(4))

    assert result.converged
    np.testing.assert_allclose(result.transformation, T_true, atol=1e-2)


def test_pairwise_icp_known_transform_gicp():
    source = create_box_pcd()
    T_true = np.eye(4)
    T_true[:3, :3] = Rotation.from_euler("y", 5, degrees=True).as_matrix()
    T_true[:3, 3] = [0.05, 0, 0.02]

    target = o3d.geometry.PointCloud()
    target.points = o3d.utility.Vector3dVector(
        (np.asarray(source.points) @ T_true[:3, :3].T) + T_true[:3, 3]
    )

    # GICP usually needs normals, which pairwise_icp estimates internally
    config = ICPConfig(min_fitness=0.5, voxel_size=0.01, method="gicp")
    result = pairwise_icp(source, target, config, np.eye(4))

    assert result.converged
    np.testing.assert_allclose(result.transformation, T_true, atol=1e-2)


def test_pairwise_icp_insufficient_points():
    source = o3d.geometry.PointCloud()
    source.points = o3d.utility.Vector3dVector(np.random.rand(5, 3))
    target = o3d.geometry.PointCloud()
    target.points = o3d.utility.Vector3dVector(np.random.rand(5, 3))

    config = ICPConfig(min_fitness=0.9)
    result = pairwise_icp(source, target, config, np.eye(4))
    assert not result.converged


def test_build_pose_graph_basic():
    serials = ["cam1", "cam2"]
    extrinsics = {"cam1": np.eye(4), "cam2": np.eye(4)}

    res = ICPResult(
        transformation=np.eye(4),
        fitness=1.0,
        inlier_rmse=0.0,
        information_matrix=np.eye(6),
        converged=True,
    )
    pair_results = {("cam1", "cam2"): res}

    graph = build_pose_graph(serials, extrinsics, pair_results, "cam1")
    assert len(graph.nodes) == 2
    assert len(graph.edges) == 1


def test_build_pose_graph_disconnected():
    serials = ["cam1", "cam2", "cam3"]
    extrinsics = {"cam1": np.eye(4), "cam2": np.eye(4), "cam3": np.eye(4)}

    res = ICPResult(
        transformation=np.eye(4),
        fitness=1.0,
        inlier_rmse=0.0,
        information_matrix=np.eye(6),
        converged=True,
    )
    pair_results = {("cam1", "cam2"): res}

    graph = build_pose_graph(serials, extrinsics, pair_results, "cam1")
    assert len(graph.nodes) == 2
    assert len(graph.edges) == 1


def test_refine_with_icp_synthetic_offset():
    import aruco.icp_registration
    import aruco.ground_plane

    box_points = create_box_pcd(size=0.5).points
    box_points = np.asarray(box_points)
    box_points[:, 1] -= 1.0
    box_points[:, 2] += 2.0

    def mock_unproject(depth, K, stride=1, **kwargs):
        if depth[0, 0] == 1.0:
            return box_points
        else:
            return box_points - np.array([1.0, 0, 0])

    orig_unproject = aruco.ground_plane.unproject_depth_to_points
    aruco.ground_plane.unproject_depth_to_points = mock_unproject

    try:
        camera_data = {
            "cam1": {"depth": np.ones((10, 10)), "K": np.eye(3)},
            "cam2": {"depth": np.zeros((10, 10)), "K": np.eye(3)},
        }
        T_w1 = np.eye(4)
        T_w2_est = np.eye(4)
        T_w2_est[0, 3] = 1.05

        extrinsics = {"cam1": T_w1, "cam2": T_w2_est}

        floor_planes = {
            "cam1": FloorPlane(normal=np.array([0, 1, 0]), d=1.0),
            "cam2": FloorPlane(normal=np.array([0, 1, 0]), d=1.0),
        }

        config = ICPConfig(
            min_overlap_area=0.01,
            min_fitness=0.1,
            voxel_size=0.05,
            max_iterations=[20, 10, 5],
            max_translation_m=3.0,
        )

        new_extrinsics, metrics = refine_with_icp(
            camera_data, extrinsics, floor_planes, config
        )

        assert metrics.success
        assert metrics.num_cameras_optimized == 2
        assert abs(new_extrinsics["cam2"][0, 3] - T_w2_est[0, 3]) > 0.01

    finally:
        aruco.ground_plane.unproject_depth_to_points = orig_unproject


def test_refine_with_icp_no_overlap():
    import aruco.icp_registration
    import aruco.ground_plane

    def mock_unproject(depth, K, stride=1, **kwargs):
        if depth[0, 0] == 1.0:
            return np.random.rand(200, 3) + [0, -1, 0]
        else:
            return np.random.rand(200, 3) + [10, -1, 0]

    orig_unproject = aruco.ground_plane.unproject_depth_to_points
    aruco.ground_plane.unproject_depth_to_points = mock_unproject

    try:
        camera_data = {
            "cam1": {"depth": np.ones((10, 10)), "K": np.eye(3)},
            "cam2": {"depth": np.zeros((10, 10)), "K": np.eye(3)},
        }
        extrinsics = {"cam1": np.eye(4), "cam2": np.eye(4)}
        floor_planes = {
            "cam1": FloorPlane(normal=np.array([0, 1, 0]), d=1.0),
            "cam2": FloorPlane(normal=np.array([0, 1, 0]), d=1.0),
        }

        config = ICPConfig(min_overlap_area=1.0)
        new_extrinsics, metrics = refine_with_icp(
            camera_data, extrinsics, floor_planes, config
        )

        assert not metrics.success
        assert "No converged ICP pairs" in metrics.message

    finally:
        aruco.ground_plane.unproject_depth_to_points = orig_unproject


def test_refine_with_icp_single_camera():
    camera_data = {"cam1": {"depth": np.ones((10, 10)), "K": np.eye(3)}}
    extrinsics = {"cam1": np.eye(4)}
    floor_planes = {"cam1": FloorPlane(normal=np.array([0, 1, 0]), d=1.0)}

    config = ICPConfig()
    new_extrinsics, metrics = refine_with_icp(
        camera_data, extrinsics, floor_planes, config
    )

    assert not metrics.success