feat: 完善 STEP 一级参数化编辑识别与关系式建模

step_editor/recognition_priority.py

@@ -38,6 +38,17 @@ USER_PRIORITY_BUCKETS: tuple[tuple[int, str, str], ...] = (
     (90, "只读/诊断", "暂未稳定归类为可修改特征。"),
 )
 
+EXTERNAL_RELATION_SCORE_WEIGHTS: dict[str, int] = {
+    "coaxial": 8,
+    "tangent": 5,
+    "coplanar": 4,
+    "parallel": 3,
+    "perpendicular": 3,
+    "parallel_axis": 3,
+}
+EXTERNAL_RELATION_SCORE_LIMIT = 18
+EXTERNAL_FEATURE_HINT_SCORE_LIMIT = 12
+
 
 def _text(value: object) -> str:
     return str(value or "").strip()
@@ -50,6 +61,69 @@ def _float_or_none(value: object) -> float | None:
         return None
 
 
+def _int_or_zero(value: object) -> int:
+    try:
+        return int(value)
+    except (TypeError, ValueError):
+        return 0
+
+
+def _text_values(value: object) -> tuple[str, ...]:
+    if value is None or value == "":
+        return ()
+    if isinstance(value, str):
+        return (value.strip(),) if value.strip() else ()
+    if isinstance(value, (list, tuple, set)):
+        return tuple(str(item).strip() for item in value if str(item).strip())
+    return ()
+
+
+def _relation_types_from_summary(value: object) -> tuple[str, ...]:
+    text = _text(value)
+    if not text:
+        return ()
+    result: list[str] = []
+    for chunk in text.replace(";", ",").split(","):
+        relation_type = chunk.split(":", 1)[0].strip()
+        if relation_type:
+            result.append(relation_type)
+    return tuple(result)
+
+
+def external_relation_score_bonus(info: Mapping[str, object]) -> int:
+    relation_types = _text_values(info.get("external_recognition_relation_types")) or _text_values(
+        info.get("asitus_geometric_relation_types")
+    )
+    if not relation_types:
+        relation_types = _relation_types_from_summary(
+            info.get("external_recognition_relation_summary")
+            or info.get("asitus_geometric_relation_summary")
+        )
+    relation_count = _int_or_zero(
+        info.get("external_recognition_relation_count")
+        or info.get("asitus_geometric_relation_count")
+    )
+    score = 0
+    for relation_type in relation_types:
+        score += EXTERNAL_RELATION_SCORE_WEIGHTS.get(relation_type, 1)
+    if relation_count and not relation_types:
+        score = min(relation_count * 2, EXTERNAL_RELATION_SCORE_LIMIT)
+    score = max(0, min(score, EXTERNAL_RELATION_SCORE_LIMIT))
+    hint_score = min(_int_or_zero(info.get("analysis_situs_feature_hint_score")), EXTERNAL_FEATURE_HINT_SCORE_LIMIT)
+    return max(0, min(score + hint_score, EXTERNAL_RELATION_SCORE_LIMIT + EXTERNAL_FEATURE_HINT_SCORE_LIMIT))
+
+
+def _confidence_sort_rank(value: object) -> int:
+    return {
+        "high": 0,
+        "medium": 1,
+        "low": 2,
+        "pending": 3,
+        "unchecked": 3,
+        "none": 4,
+    }.get(_text(value), 5)
+
+
 def _is_effectively_full_cylinder(info: Mapping[str, object]) -> bool:
     if bool(info.get("is_full_cylinder")):
         return True
@@ -146,7 +220,7 @@ def feature_recognition_priority_reason(info: Mapping[str, object]) -> str:
     return reason
 
 
-def feature_recognition_sort_key(info: Mapping[str, object]) -> tuple[int, int, int, int]:
+def feature_recognition_sort_key(info: Mapping[str, object]) -> tuple[int, int, int, int, int, int]:
     status_order = {"ready": 0, "candidate": 0, "caution": 1, "blocked": 2}
     risk_order = {"low": 0, "medium": 1, "high": 2, "blocked": 3}
     target_id = info.get("target_id", info.get("face_id", info.get("edge_id", -1)))
@@ -158,5 +232,7 @@ def feature_recognition_sort_key(info: Mapping[str, object]) -> tuple[int, int,
         feature_recognition_priority(info),
         status_order.get(_text(info.get("status")), 9),
         risk_order.get(_text(info.get("risk")), 9),
+        _confidence_sort_rank(info.get("confidence") or info.get("recognition_confidence")),
+        -external_relation_score_bonus(info),
         numeric_target,
     )