98 lines
3.8 KiB
Python
98 lines
3.8 KiB
Python
# -*- coding: utf-8 -*-
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"""Ti-2 配方优化问题建模 自检脚本（Issue #78）。
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不依赖 unittest，直接加载模板资产并做能力点断言，便于 CI / 部署期一键核对。
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"""
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import os
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import sys
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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from problem import ConstraintKind, OptimizationProblem, load_problem # noqa: E402
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from solver import SolverConfig, solve # noqa: E402
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from cross_process import CrossProcessModel, CrossProcessModelConfig, CrossProcessSample # noqa: E402
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from advisor import generate_advice # noqa: E402
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CONFIG = os.path.join(os.path.dirname(os.path.abspath(__file__)),
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"config", "recipe_optim.template.yaml")
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def main() -> int:
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failures = []
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# 1) 模板能加载
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p = load_problem(CONFIG)
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if not isinstance(p, OptimizationProblem):
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failures.append("load_problem 未返回 OptimizationProblem")
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# 2) 4 类约束齐全
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kinds = {c.kind for c in p.constraints}
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expected = {ConstraintKind.BOX, ConstraintKind.LINEAR,
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ConstraintKind.RATIO, ConstraintKind.FORBIDDEN}
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if kinds != expected:
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failures.append(f"约束种类不齐: {kinds} != {expected}")
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# 3) 静态校验通过
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errs = p.validate()
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if errs:
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failures.append(f"validate 未通过: {errs}")
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# 4) 可行性判定：合法取值可行、禁止组合不可行
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ok = p.is_feasible({"clf_temp": 850, "cl2_ratio": 1.0,
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"feed_rate": 450, "catalyst": "A"})
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bad = p.is_feasible({"clf_temp": 950, "cl2_ratio": 1.0,
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"feed_rate": 450, "catalyst": "A"})
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if not ok:
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failures.append("合法取值被判为不可行")
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if bad:
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failures.append("越界取值(950℃)未被识别为不可行")
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# 5) 序列化往返无损
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rt = OptimizationProblem.from_dict(p.to_dict())
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if [v.name for v in rt.variables] != [v.name for v in p.variables]:
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failures.append("序列化往返丢失变量")
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# 6) 求解器（#79）端到端：加载模板后能求出可行解
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sol = solve(p, SolverConfig(grid_steps=7, max_combinations=200000))
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if not sol.feasible:
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failures.append(f"求解器未求出可行解: {sol.message}")
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if sol.strategy != "grid":
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failures.append(f"求解策略非 grid: {sol.strategy}")
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# 7) 跨工序关联模型（#80）端到端：合成线性数据训练 + R² 评估
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cfg = CrossProcessModelConfig(
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upstream_features=["up"], downstream_targets=["down"],
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alpha=0.0, min_samples=8)
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samples = [CrossProcessSample(upstream={"up": float(i)},
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downstream={"down": 2.0 * float(i) + 1.0})
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for i in range(12)]
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cm = CrossProcessModel(cfg).fit(samples)
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report = cm.evaluate(samples)
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if not cm.fitted:
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failures.append("跨工序模型未训练成功")
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if not (report.get("r2_down", 0.0) > 0.99):
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failures.append(f"跨工序模型 R² 过低: {report}")
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# 8) 优化建议生成（#81）端到端：可解释、可溯源建议
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advice = generate_advice(p, sol, cross_process_weights={
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"Ti_purity": {"clf_temp": 0.8, "cl2_ratio": 1.2}})
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if not advice.feasible:
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failures.append("建议生成器标记不可行")
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if len(advice.items) != len(p.variables):
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failures.append("建议条目数与变量数不一致")
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if not all(it.evidence for it in advice.items):
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failures.append("存在无依据的建议条目（违反可溯源要求）")
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if not advice.trace:
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failures.append("溯源链路为空")
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if failures:
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print("❌ recipe-optim 自检失败:")
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for f in failures:
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print(" -", f)
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return 1
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print("✅ recipe-optim 自检通过（8 能力点）")
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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