182 lines
7.8 KiB
Python
182 lines
7.8 KiB
Python
"""Dress-up executors (fillet / chamfer / shell).
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These mutate an existing body through edge/face selectors resolved from the
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current B-rep snapshot.
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"""
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from __future__ import annotations
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import math
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from typing import TYPE_CHECKING, Any
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from ..registry import atomic_executor
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from ..topology import FeaturePlanNode, FeatureResult, RuntimeDiagnostic, TopologyDelta
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from .common import _replace_shell_target, _selector_edges, _shell_target
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if TYPE_CHECKING: # pragma: no cover - import for type checkers only
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from ..session import ExecutionSession
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def _single_member_dressup_members(
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node: FeaturePlanNode,
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session: "ExecutionSession",
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body: Any,
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selected_edges: list[Any],
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) -> dict[str, Any] | None:
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"""Preserve unchanged body members after one exact-member dress-up.
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The adapter only reports Compound history when every selected edge maps to
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one source solid. Keep the same proof at the body-graph layer: all other
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members must appear unchanged in the result and exactly one result solid
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must remain for the changed member. Otherwise aggregate replay remains
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valid, but no member-lifecycle transfer is asserted.
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"""
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if not selected_edges or len(session.body_members) < 2:
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return None
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source_members: dict[str, Any] = {}
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for member_id, member in session.body_members.items():
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solids = session.adapter.body_solids(member)
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if len(solids) != 1:
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return None
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source_members[member_id] = solids[0]
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selected_members = {
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member_id
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for edge in selected_edges
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for member_id, member in source_members.items()
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if any(edge.is_same(candidate) for candidate in member.edges())
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}
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if len(selected_members) != 1:
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return None
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changed_member_id = next(iter(selected_members))
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result_solids = session.adapter.body_solids(body)
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unchanged: dict[str, Any] = {}
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matched_result_indexes: set[int] = set()
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for member_id, member in source_members.items():
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if member_id == changed_member_id:
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continue
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matches = [
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index for index, result in enumerate(result_solids)
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if session.topology._same_topology_value(member, result)
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]
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if len(matches) != 1 or matches[0] in matched_result_indexes:
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return None
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matched_result_indexes.add(matches[0])
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unchanged[member_id] = result_solids[matches[0]]
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changed = [
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result for index, result in enumerate(result_solids)
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if index not in matched_result_indexes
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]
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if len(changed) != 1:
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return None
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return {**unchanged, node.feature_id: changed[0]}
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def _execute_fillet(node: FeaturePlanNode, session: "ExecutionSession") -> FeatureResult:
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# 圆角特征（fillet）执行入口：对选中边按半径做圆角，平滑尖角与棱边。
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# 1. 校验：圆角作用于已有主体，必须先有主体。
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if session.body is None:
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raise ValueError("fillet has no body")
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# 2. 解析圆角半径并校验必须大于 0。
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radius = float(node.params.get("radius_mm") or 0)
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if radius <= 0:
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raise ValueError("fillet radius_mm must be > 0")
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# 3. 解析目标边（支持 tangent_propagation 相切传播），并执行圆角。
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edges = _selector_edges(node, session, tangent_propagation=bool(node.params.get("tangent_propagation")))
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body, topology_delta = session.adapter.fillet_with_topology_delta(
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session.body, radius, edges,
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)
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# 4. 登记新主体并返回结果。
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session.register_body(
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node.feature_id, body, replay_node=node, topology_delta=topology_delta,
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body_members=_single_member_dressup_members(node, session, body, edges),
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)
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return session.result(node)
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@atomic_executor("fillet")
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def _fillet_executor(node: FeaturePlanNode, session: "ExecutionSession", sketch: dict[str, Any] | None) -> FeatureResult:
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del sketch
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return _execute_fillet(node, session)
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def _execute_chamfer(node: FeaturePlanNode, session: "ExecutionSession") -> FeatureResult:
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# 倒角特征（chamfer）执行入口：对选中边按距离做倒角（可带第二距离形成不对称倒角）。
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# 1. 校验：倒角作用于已有主体，必须先有主体。
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if session.body is None:
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raise ValueError("chamfer has no body")
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# 2. 解析主距离并校验必须大于 0。
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distance = float(node.params.get("distance_mm") or 0)
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if distance <= 0:
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raise ValueError("chamfer distance_mm must be > 0")
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# 3. 解析第二距离与角度（importer 对 SolidWorks Distance-Angle 倒角产出
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# angle_rad，单位为弧度）。第二距离 = 主距离 * tan(angle)；angle=45° 时
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# tan=1，退化为等距倒角（与历史行为一致，零回归）。
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# 注意：build123d 的 length/length2 侧向分配依赖面的枚举顺序，对非 45°
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# 倒角仅保证量级正确，距离所在侧可能反转。
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distance_2 = node.params.get("distance_2_mm")
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angle_rad = node.params.get("angle_rad")
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if distance_2 is None and angle_rad is not None:
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distance_2 = distance * math.tan(float(angle_rad))
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# 4. 解析目标边（支持相切传播），执行倒角。
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edges = _selector_edges(node, session, tangent_propagation=bool(node.params.get("tangent_propagation")))
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diagnostics: list[RuntimeDiagnostic] = []
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topology_delta: TopologyDelta | None = None
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try:
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body, topology_delta = session.adapter.chamfer_with_topology_delta(session.body, distance, distance_2, edges)
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except ValueError as error:
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# 显式 surfaceEntities 可以在后续实体上留下曲面分区边界。若标准
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# OCC 倒角因环域宽度不足而拒绝，只允许在该 shell 给出同轴边界证据
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# 时按原始距离构造受限倒角；没有证明时仍保留原始内核失败。
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if distance_2 is not None or not session.surface_members:
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raise
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try:
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body = session.adapter.surface_limited_chamfer(
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session.body, distance, edges, list(session.surface_members.values()),
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)
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except ValueError:
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raise error
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diagnostics.append(RuntimeDiagnostic(
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"chamfer_surface_limited",
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"Chamfer was limited by an explicit coaxial surface boundary",
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feature_id=node.feature_id,
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detail={"distance_mm": distance, "surface_count": len(session.surface_members)},
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))
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# 5. 登记新主体并返回结果。
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session.register_body(
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node.feature_id, body, replay_node=node, topology_delta=topology_delta,
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body_members=_single_member_dressup_members(node, session, body, edges),
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)
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return session.result(node, diagnostics=diagnostics)
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@atomic_executor("chamfer")
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def _chamfer_executor(node: FeaturePlanNode, session: "ExecutionSession", sketch: dict[str, Any] | None) -> FeatureResult:
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del sketch
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return _execute_chamfer(node, session)
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def _execute_shell(node: FeaturePlanNode, session: "ExecutionSession") -> FeatureResult:
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# 抽壳特征：移除 selector 所指面，并按 CADFS thickness 向实体内部偏置。
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if session.body is None:
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raise ValueError("shell has no body")
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thickness = float(node.params.get("thickness_mm") or 0)
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if thickness <= 0:
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raise ValueError("shell thickness_mm must be > 0")
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target, faces = _shell_target(node, session)
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result, topology_delta = session.adapter.shell_with_topology_delta(
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target, faces, thickness, inward=bool(node.params.get("inward", True)),
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)
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session.register_body(
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node.feature_id, _replace_shell_target(session, target, result), replay_node=node,
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topology_delta=topology_delta,
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)
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return session.result(node)
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@atomic_executor("shell")
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def _shell_executor(node: FeaturePlanNode, session: "ExecutionSession", sketch: dict[str, Any] | None) -> FeatureResult:
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del sketch
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return _execute_shell(node, session)
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