feat: 完成 issue #81 [Ti-2] 优化建议生成与可解释性（整合求解结果+跨工序权重+约束依据，输出可溯源建议报告）
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# -*- coding: utf-8 -*-
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"""Ti-2 优化建议生成与可解释性 单元测试（Issue #81）。
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覆盖：
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- 单条建议方向/幅度计算；
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- generate_advice：变量级建议、跨工序佐证、风险与达标提示、不可行降级、摘要；
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- 序列化；
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- 端到端（#78→#79→#81 链路 + 跨工序权重注入）。
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"""
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import os
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import sys
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import unittest
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sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
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import _bootstrap # noqa: E402
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from recipe_optim.problem import ( # noqa: E402
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ConstraintKind,
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ConstraintSpec,
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DecisionVariable,
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DomainKind,
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ObjectiveSpec,
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ObjectiveTerm,
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OptimizationProblem,
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Sense,
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load_problem,
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)
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from recipe_optim.solver import Solution, SolverConfig, solve # noqa: E402
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from recipe_optim.advisor import ( # noqa: E402
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AdviceConfig,
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AdviceItem,
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AdviceReport,
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AdvisorError,
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generate_advice,
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)
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def _problem() -> OptimizationProblem:
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return OptimizationProblem(
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variables=[
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DecisionVariable("clf_temp", DomainKind.BOUNDS, "反应温度", "℃",
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bounds=(800.0, 920.0), initial=860.0),
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DecisionVariable("cl2_ratio", DomainKind.BOUNDS, "氯气配比", "ratio",
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bounds=(0.8, 1.4), initial=1.0),
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],
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objective=ObjectiveSpec(Sense.MAXIMIZE, target="Ti_purity", target_value=10.0,
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terms=[ObjectiveTerm("clf_temp", 0.01),
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ObjectiveTerm("cl2_ratio", 2.0)]),
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constraints=[ConstraintSpec(ConstraintKind.BOX, variable="clf_temp",
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bounds=(820.0, 900.0), reason="温度安全区间")],
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)
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class TestDirectionDelta(unittest.TestCase):
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def test_up(self):
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from recipe_optim.advisor import _direction_and_delta
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self.assertEqual(_direction_and_delta(1.0, 1.5), ("↑", 0.5))
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def test_down(self):
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from recipe_optim.advisor import _direction_and_delta
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self.assertEqual(_direction_and_delta(2.0, 1.0), ("↓", -1.0))
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def test_equal(self):
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from recipe_optim.advisor import _direction_and_delta
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self.assertEqual(_direction_and_delta(1.0, 1.0), ("→", 0.0))
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def test_non_numeric(self):
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from recipe_optim.advisor import _direction_and_delta
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d, delta = _direction_and_delta("A", "B")
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self.assertEqual(d, "≠")
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self.assertEqual(delta, 0.0)
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class TestGenerateAdvice(unittest.TestCase):
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def test_variable_level_advice(self):
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p = _problem()
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sol = solve(p, SolverConfig(grid_steps=11))
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report = generate_advice(p, sol, current={"clf_temp": 860.0, "cl2_ratio": 1.0})
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self.assertTrue(report.feasible)
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self.assertEqual(len(report.items), 2)
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# 应当有变化项（求解器会爬到温度/配比上界附近）
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changes = [it for it in report.items if it.direction in ("↑", "↓")]
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self.assertGreater(len(changes), 0)
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# 含工艺含义
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meanings = {it.meaning for it in report.items}
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self.assertIn("反应温度", meanings)
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def test_target_met_summary(self):
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p = _problem()
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sol = solve(p, SolverConfig(grid_steps=11))
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report = generate_advice(p, sol)
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self.assertIn("Ti_purity", report.summary)
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def test_cross_process_evidence_appended(self):
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p = _problem()
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sol = solve(p, SolverConfig(grid_steps=11))
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weights = {"sponge_titanium_grade": {"clf_temp": 0.5, "cl2_ratio": -0.3}}
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report = generate_advice(p, sol, cross_process_weights=weights)
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joined = " ".join(it.evidence for it in report.items)
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self.assertIn("跨工序关联", joined)
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self.assertTrue(any("sponge_titanium_grade" in t for t in report.trace))
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def test_warnings_on_infeasible(self):
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p = _problem()
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# 构造一个不可行 Solution
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sol = Solution(feasible=False, target_met=False,
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violated=[ConstraintSpec(ConstraintKind.BOX, variable="clf_temp",
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bounds=(820.0, 900.0), reason="温度安全区间")],
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message="无可行解（约束过紧）")
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report = generate_advice(p, sol)
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self.assertFalse(report.feasible)
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self.assertTrue(any("可行" in w for w in report.warnings))
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self.assertIn("温度安全区间", " ".join(report.warnings))
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def test_keep_unchanged_item(self):
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p = OptimizationProblem(
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variables=[DecisionVariable("x", DomainKind.BOUNDS, "X", "",
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bounds=(0.0, 10.0), initial=5.0)],
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objective=ObjectiveSpec(Sense.MAXIMIZE, terms=[ObjectiveTerm("x", 0.0)]),
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constraints=[ConstraintSpec(ConstraintKind.BOX, variable="x", bounds=(5.0, 5.0))],
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)
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sol = solve(p, SolverConfig(grid_steps=3))
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report = generate_advice(p, sol, current={"x": 5.0})
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self.assertEqual(len(report.items), 1)
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self.assertEqual(report.items[0].direction, "→")
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def test_serialization(self):
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p = _problem()
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sol = solve(p, SolverConfig(grid_steps=5))
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report = generate_advice(p, sol)
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d = report.to_dict()
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self.assertIn("items", d)
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self.assertIn("summary", d)
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self.assertTrue(d["feasible"])
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# item dict 完整
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if d["items"]:
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self.assertIn("reason_text", d["items"][0])
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class TestEndToEndFromTemplate(unittest.TestCase):
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def test_template_chain(self):
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cfg_path = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))),
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"config", "recipe_optim.template.yaml")
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p = load_problem(cfg_path)
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sol = solve(p, SolverConfig(grid_steps=7, max_combinations=200000))
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report = generate_advice(p, sol, cross_process_weights={
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"Ti_purity": {"clf_temp": 0.8, "cl2_ratio": 1.2, "feed_rate": 0.1}})
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self.assertTrue(report.feasible)
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self.assertEqual(len(report.items), len(p.variables))
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# 每条建议都有依据
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for it in report.items:
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self.assertTrue(it.evidence)
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# 溯源链路非空
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self.assertGreater(len(report.trace), 0)
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if __name__ == "__main__":
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unittest.main()
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