"""Shared helpers for the SW-IR and code-generation sides of the translator.

These small utilities are used by both ``ir`` (SolidWorks plugin JSON to
backend IR) and ``codegen`` (backend IR to build123d source).  Anything used
by exactly one side lives in that side's module instead.
"""

from __future__ import annotations

import math
from typing import Any, Optional

#: SolidWorks numeric end-condition codes, shared by IR conversion and codegen.
SW_END_CONDITIONS = {
    0: "Blind",
    1: "ThroughAll",
    2: "ThroughAllBoth",
    3: "UpToVertex",
    4: "UpToSurface",
    5: "OffsetFromSurface",
    6: "ThroughAllAndBlind",
    7: "UpToBody",
    8: "MidPlane",
    9: "ThroughNext",
}

#: Generous through-cut length used when a termination reference is missing.
THROUGH_CUT_AMOUNT_MM = 200


def _tuple3(values: Any) -> tuple[float, float, float]:
    values = list(values or [0, 0, 0])
    values = (values + [0, 0, 0])[:3]
    return tuple(values)


def _point_m_to_mm(point: Any) -> tuple[float, float, float]:
    values = list(point or [0, 0, 0])
    values = (values + [0, 0, 0])[:3]
    return tuple(float(value) * 1000 for value in values)


def _scale_point(point: Any) -> list[float]:
    values = [0 if value is None else float(value) for value in (point or [0, 0])]
    return [_scale_length(value) for value in values[:2]]


def _scale_length(value: Any) -> float:
    value = 0 if value is None else float(value)
    return value * 1000 if abs(value) <= 10 else value


def _to_degrees(value: Any) -> float:
    value = 0 if value is None else float(value)
    return value * 180 / 3.141592653589793 if abs(value) <= 6.283185307179586 else value


def _unit3(vector: list[Any]) -> list[float]:
    raw = [float(vector[i]) for i in range(3)]
    length = math.sqrt(sum(v * v for v in raw))
    if length <= 0:
        return [0.0, 0.0, 0.0]
    return [v / length for v in raw]


def _points_bbox(points: list[list[float]]) -> Optional[list[float]]:
    if not points:
        return None
    return [
        min(point[0] for point in points),
        min(point[1] for point in points),
        min(point[2] for point in points),
        max(point[0] for point in points),
        max(point[1] for point in points),
        max(point[2] for point in points),
    ]


def _point_key(point: Any, places: int = 5) -> tuple[float, float] | None:
    if not isinstance(point, list) or len(point) < 2:
        return None
    return (round(float(point[0]), places), round(float(point[1]), places))


def _rounded_point_key(point: list[Any], digits: int = 5) -> tuple[float, float, float]:
    z = point[2] if len(point) > 2 else 0
    return (round(float(point[0]), digits), round(float(point[1]), digits), round(float(z), digits))


def _dedupe_points(points: list[list[float]]) -> list[list[float]]:
    result = []
    seen = set()
    for point in points:
        key = _rounded_point_key(point)
        if key in seen:
            continue
        seen.add(key)
        result.append(point)
    return result


def _is_near_origin(point: list[float], tolerance: float = 1e-6) -> bool:
    return math.sqrt(sum(float(component) * float(component) for component in point[:3])) <= tolerance


def _similar_bbox_size(a: list[float], b: list[float], tolerance: float = 0.05) -> bool:
    return all(abs(float(a[i]) - float(b[i])) <= tolerance for i in range(3))


def _translated_bbox(bbox: list[float], offset: list[float]) -> list[float]:
    return [
        bbox[0] + offset[0],
        bbox[1] + offset[1],
        bbox[2] + offset[2],
        bbox[3] + offset[0],
        bbox[4] + offset[1],
        bbox[5] + offset[2],
    ]


def _bbox_overflow_score(candidate: list[float], source: list[float]) -> float:
    score = 0.0
    for axis in range(3):
        score += max(source[axis] - candidate[axis], 0)
        score += max(candidate[axis + 3] - source[axis + 3], 0)
    return score


def _bbox_center_distance_score(candidate: list[float], source: list[float]) -> float:
    score = 0.0
    for axis in range(3):
        source_center = (source[axis] + source[axis + 3]) / 2
        candidate_center = (candidate[axis] + candidate[axis + 3]) / 2
        axis_size = max(source[axis + 3] - source[axis], 1.0)
        score += abs(candidate_center - source_center) / axis_size
    return score


def _bbox_area_2d(bbox: Optional[list[float]]) -> float:
    if not isinstance(bbox, list) or len(bbox) < 4:
        return 0.0
    return max(0.0, float(bbox[2]) - float(bbox[0])) * max(0.0, float(bbox[3]) - float(bbox[1]))


def _bbox_contains_2d(outer: Optional[list[float]], inner: Optional[list[float]], tolerance: float = 1e-6) -> bool:
    if not isinstance(outer, list) or not isinstance(inner, list) or len(outer) < 4 or len(inner) < 4:
        return False
    return (
        float(outer[0]) <= float(inner[0]) + tolerance
        and float(outer[1]) <= float(inner[1]) + tolerance
        and float(outer[2]) >= float(inner[2]) - tolerance
        and float(outer[3]) >= float(inner[3]) - tolerance
    )


def _bbox_overlap_ratio_2d(a: Optional[list[float]], b: Optional[list[float]]) -> float:
    if not isinstance(a, list) or not isinstance(b, list) or len(a) < 4 or len(b) < 4:
        return 0.0
    ix0 = max(float(a[0]), float(b[0]))
    iy0 = max(float(a[1]), float(b[1]))
    ix1 = min(float(a[2]), float(b[2]))
    iy1 = min(float(a[3]), float(b[3]))
    intersection = max(0.0, ix1 - ix0) * max(0.0, iy1 - iy0)
    smaller = min(_bbox_area_2d(a), _bbox_area_2d(b))
    if smaller <= 1e-9:
        return 0.0
    return intersection / smaller


def _loop_bbox(entities: list[dict[str, Any]]) -> Optional[list[float]]:
    points = []
    for ent in entities:
        if not isinstance(ent, dict):
            continue
        if ent.get("type") == "circle":
            center = ent.get("center")
            radius = ent.get("radius_mm")
            if isinstance(center, list) and len(center) >= 2 and radius is not None:
                radius_value = abs(float(radius))
                points.append([float(center[0]) - radius_value, float(center[1]) - radius_value])
                points.append([float(center[0]) + radius_value, float(center[1]) + radius_value])
                continue
        for key in ("start", "end", "center"):
            point = ent.get(key)
            if isinstance(point, list) and len(point) >= 2:
                points.append(point)
    if not points:
        return None
    return [
        min(float(point[0]) for point in points),
        min(float(point[1]) for point in points),
        max(float(point[0]) for point in points),
        max(float(point[1]) for point in points),
    ]