122 lines
5.0 KiB
Python
122 lines
5.0 KiB
Python
from __future__ import annotations
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from .models import CompareIssue, GradeReport, LessonStep, SkillStep, StepCompareResult
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CORE_ARGUMENTS = {
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"extrude_boss_mm": ["depth_mm", "end_condition_code", "through_all"],
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"extrude_cut_mm": ["depth_mm", "end_condition_code", "through_all"],
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"shell_remove_face_at_point_mm": ["thickness_mm"],
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"draw_circle_diameter_mm": ["diameter_mm", "center_model_mm", "cx_mm", "cy_mm"],
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"fillet_edges_radius_mm": ["radius_mm"],
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"chamfer_edges_angle_distance_mm": ["distance_mm", "angle_deg"],
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"linear_pattern_feature_mm": ["count1", "spacing1_mm"],
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"circular_pattern_feature": ["count", "angle_deg"],
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}
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class FeatureGrader:
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def compare_step(self, expected: LessonStep, observed: SkillStep | None) -> StepCompareResult:
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if observed is None:
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return StepCompareResult(
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ok=False,
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score=0,
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expected_step=expected,
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feedback_text=f"没有检测到本步骤的操作。请执行：{expected.title}。",
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issues=[
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CompareIssue(
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code="missing_operation",
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message=f"Expected {expected.expected_skill}, but no user feature was observed.",
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expected={"skill": expected.expected_skill},
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)
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],
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)
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issues: list[CompareIssue] = []
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if expected.expected_skill != observed.skill:
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issues.append(
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CompareIssue(
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code="wrong_feature_method",
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message=f"方法错误：标准答案要求 {expected.expected_skill}，学生实际使用 {observed.skill}。",
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expected={"skill": expected.expected_skill, "title": expected.title},
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actual={"skill": observed.skill, "name": observed.name, "source_feature": observed.source_feature},
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)
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)
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issues.extend(compare_core_arguments(expected.expected_skill, expected.expected_arguments, observed.arguments))
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ok = not issues
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return StepCompareResult(
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ok=ok,
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score=100.0 if ok else max(0.0, 60.0 - 20.0 * len(issues)),
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expected_step=expected,
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observed_step=observed,
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issues=issues,
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feedback_text=success_feedback(expected) if ok else failure_feedback(expected, issues),
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)
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def grade_sequence(self, expected: list[LessonStep], observed: list[SkillStep]) -> GradeReport:
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issues: list[CompareIssue] = []
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passed = 0
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total = len(expected)
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for index, step in enumerate(expected):
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obs = observed[index] if index < len(observed) else None
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result = self.compare_step(step, obs)
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if result.ok:
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passed += 1
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issues.extend(result.issues)
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score = 100.0 if total == 0 else round((passed / total) * 100.0, 2)
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return GradeReport(
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ok=score >= 90.0 and not any(issue.severity == "error" for issue in issues),
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score=score,
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passed_steps=passed,
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total_steps=total,
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issues=issues,
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summary=f"Passed {passed}/{total} feature-method steps.",
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)
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def compare_core_arguments(skill: str, expected: dict[str, object], actual: dict[str, object]) -> list[CompareIssue]:
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result: list[CompareIssue] = []
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for key in CORE_ARGUMENTS.get(skill, []):
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if key not in expected:
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continue
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if key not in actual:
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result.append(
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CompareIssue(
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code="missing_parameter",
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message=f"参数缺失：{key}。",
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expected={key: expected.get(key)},
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actual={},
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)
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)
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continue
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if not values_close(expected.get(key), actual.get(key)):
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result.append(
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CompareIssue(
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code="wrong_parameter",
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message=f"参数错误：{key} 标准值为 {expected.get(key)}，实际值为 {actual.get(key)}。",
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expected={key: expected.get(key)},
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actual={key: actual.get(key)},
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)
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)
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return result
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def values_close(expected: object, actual: object, tolerance: float = 0.05) -> bool:
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if isinstance(expected, (int, float)) and isinstance(actual, (int, float)):
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return abs(float(expected) - float(actual)) <= tolerance
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if isinstance(expected, list) and isinstance(actual, list) and len(expected) == len(actual):
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return all(values_close(e, a, tolerance) for e, a in zip(expected, actual))
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return str(expected) == str(actual)
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def success_feedback(expected: LessonStep) -> str:
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return f"正确。你使用了本步骤要求的 {expected.title}，可以进入下一步。"
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def failure_feedback(expected: LessonStep, issues: list[CompareIssue]) -> str:
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first = issues[0].message if issues else "操作不符合标准答案。"
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return f"{first} 本步骤要求：{expected.voice_text}"
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