iAOP/templates/ti-cl4/recipe-optim/tests/test_advisor.py

# -*- coding: utf-8 -*-
"""Ti-2 优化建议生成与可解释性 单元测试（Issue #81）。

覆盖：
- 单条建议方向/幅度计算；
- 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；
- 序列化；
- 端到端（#78→#79→#81 链路 + 跨工序权重注入）。
"""
import os
import sys
import unittest

sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
import _bootstrap  # noqa: E402

from recipe_optim.problem import (  # noqa: E402
    ConstraintKind,
    ConstraintSpec,
    DecisionVariable,
    DomainKind,
    ObjectiveSpec,
    ObjectiveTerm,
    OptimizationProblem,
    Sense,
    load_problem,
)
from recipe_optim.solver import Solution, SolverConfig, solve  # noqa: E402
from recipe_optim.advisor import (  # noqa: E402
    AdviceConfig,
    AdviceItem,
    AdviceReport,
    AdvisorError,
    generate_advice,
)


def _problem() -> OptimizationProblem:
    return OptimizationProblem(
        variables=[
            DecisionVariable("clf_temp", DomainKind.BOUNDS, "反应温度", "℃",
                             bounds=(800.0, 920.0), initial=860.0),
            DecisionVariable("cl2_ratio", DomainKind.BOUNDS, "氯气配比", "ratio",
                             bounds=(0.8, 1.4), initial=1.0),
        ],
        objective=ObjectiveSpec(Sense.MAXIMIZE, target="Ti_purity", target_value=10.0,
                                terms=[ObjectiveTerm("clf_temp", 0.01),
                                       ObjectiveTerm("cl2_ratio", 2.0)]),
        constraints=[ConstraintSpec(ConstraintKind.BOX, variable="clf_temp",
                                    bounds=(820.0, 900.0), reason="温度安全区间")],
    )


class TestDirectionDelta(unittest.TestCase):
    def test_up(self):
        from recipe_optim.advisor import _direction_and_delta
        self.assertEqual(_direction_and_delta(1.0, 1.5), ("↑", 0.5))

    def test_down(self):
        from recipe_optim.advisor import _direction_and_delta
        self.assertEqual(_direction_and_delta(2.0, 1.0), ("↓", -1.0))

    def test_equal(self):
        from recipe_optim.advisor import _direction_and_delta
        self.assertEqual(_direction_and_delta(1.0, 1.0), ("→", 0.0))

    def test_non_numeric(self):
        from recipe_optim.advisor import _direction_and_delta
        d, delta = _direction_and_delta("A", "B")
        self.assertEqual(d, "≠")
        self.assertEqual(delta, 0.0)


class TestGenerateAdvice(unittest.TestCase):
    def test_variable_level_advice(self):
        p = _problem()
        sol = solve(p, SolverConfig(grid_steps=11))
        report = generate_advice(p, sol, current={"clf_temp": 860.0, "cl2_ratio": 1.0})
        self.assertTrue(report.feasible)
        self.assertEqual(len(report.items), 2)
        # 应当有变化项（求解器会爬到温度/配比上界附近）
        changes = [it for it in report.items if it.direction in ("↑", "↓")]
        self.assertGreater(len(changes), 0)
        # 含工艺含义
        meanings = {it.meaning for it in report.items}
        self.assertIn("反应温度", meanings)

    def test_target_met_summary(self):
        p = _problem()
        sol = solve(p, SolverConfig(grid_steps=11))
        report = generate_advice(p, sol)
        self.assertIn("Ti_purity", report.summary)

    def test_cross_process_evidence_appended(self):
        p = _problem()
        sol = solve(p, SolverConfig(grid_steps=11))
        weights = {"sponge_titanium_grade": {"clf_temp": 0.5, "cl2_ratio": -0.3}}
        report = generate_advice(p, sol, cross_process_weights=weights)
        joined = " ".join(it.evidence for it in report.items)
        self.assertIn("跨工序关联", joined)
        self.assertTrue(any("sponge_titanium_grade" in t for t in report.trace))

    def test_warnings_on_infeasible(self):
        p = _problem()
        # 构造一个不可行 Solution
        sol = Solution(feasible=False, target_met=False,
                       violated=[ConstraintSpec(ConstraintKind.BOX, variable="clf_temp",
                                                bounds=(820.0, 900.0), reason="温度安全区间")],
                       message="无可行解（约束过紧）")
        report = generate_advice(p, sol)
        self.assertFalse(report.feasible)
        self.assertTrue(any("可行" in w for w in report.warnings))
        self.assertIn("温度安全区间", " ".join(report.warnings))

    def test_keep_unchanged_item(self):
        p = OptimizationProblem(
            variables=[DecisionVariable("x", DomainKind.BOUNDS, "X", "",
                                        bounds=(0.0, 10.0), initial=5.0)],
            objective=ObjectiveSpec(Sense.MAXIMIZE, terms=[ObjectiveTerm("x", 0.0)]),
            constraints=[ConstraintSpec(ConstraintKind.BOX, variable="x", bounds=(5.0, 5.0))],
        )
        sol = solve(p, SolverConfig(grid_steps=3))
        report = generate_advice(p, sol, current={"x": 5.0})
        self.assertEqual(len(report.items), 1)
        self.assertEqual(report.items[0].direction, "→")

    def test_serialization(self):
        p = _problem()
        sol = solve(p, SolverConfig(grid_steps=5))
        report = generate_advice(p, sol)
        d = report.to_dict()
        self.assertIn("items", d)
        self.assertIn("summary", d)
        self.assertTrue(d["feasible"])
        # item dict 完整
        if d["items"]:
            self.assertIn("reason_text", d["items"][0])


class TestEndToEndFromTemplate(unittest.TestCase):
    def test_template_chain(self):
        cfg_path = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))),
                                "config", "recipe_optim.template.yaml")
        p = load_problem(cfg_path)
        sol = solve(p, SolverConfig(grid_steps=7, max_combinations=200000))
        report = generate_advice(p, sol, cross_process_weights={
            "Ti_purity": {"clf_temp": 0.8, "cl2_ratio": 1.2, "feed_rate": 0.1}})
        self.assertTrue(report.feasible)
        self.assertEqual(len(report.items), len(p.variables))
        # 每条建议都有依据
        for it in report.items:
            self.assertTrue(it.evidence)
        # 溯源链路非空
        self.assertGreater(len(report.trace), 0)


if __name__ == "__main__":
    unittest.main()