feat: 完成 issue #78 [Ti-2] 配方优化问题建模（决策变量/目标/约束声明式规格+求解器无关+零依赖YAML加载）
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# -*- coding: utf-8 -*-
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"""Ti-2 配方优化问题建模 单元测试（Issue #78）。
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覆盖：
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- 决策变量域（bounds/choices/integer/越界/夹紧）；
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- 目标函数（线性求值、min/max、target 记录）；
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- 约束（box/linear/ratio/forbidden 可行性判定 + 未知变量静态校验）；
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- OptimizationProblem（聚合校验、可行性、违反约束枚举、序列化往返）；
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- load_problem YAML 子集加载（模板资产）。
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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 挂载 recipe_optim 包
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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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ProblemError,
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Sense,
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load_problem,
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)
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CONFIG_PATH = os.path.join(
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os.path.dirname(os.path.dirname(os.path.abspath(__file__))),
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"config", "recipe_optim.template.yaml",
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)
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def _ti_problem() -> OptimizationProblem:
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"""构造一份与 config 同构的内存问题（用于无需 YAML 的断言）。"""
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return OptimizationProblem(
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variables=[
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DecisionVariable("clf_temp", DomainKind.BOUNDS, "温度", "℃",
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bounds=(800, 920), initial=860),
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DecisionVariable("cl2_ratio", DomainKind.BOUNDS, "配比", "ratio",
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bounds=(0.8, 1.4), initial=1.0),
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DecisionVariable("catalyst", DomainKind.CHOICES, "催化剂", "",
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choices=["A", "B", "C"]),
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],
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objective=ObjectiveSpec(
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sense=Sense.MAXIMIZE,
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target="Ti_purity",
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target_value=99.5,
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terms=[ObjectiveTerm("clf_temp", 0.01), ObjectiveTerm("cl2_ratio", 2.0)],
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),
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constraints=[
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ConstraintSpec(ConstraintKind.BOX, variable="clf_temp", bounds=(820, 900),
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reason="温度安全区间"),
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ConstraintSpec(ConstraintKind.LINEAR, coefficients={"clf_temp": 1.0},
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op="<=", rhs=900),
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ConstraintSpec(ConstraintKind.FORBIDDEN, combination={"catalyst": "C"}),
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],
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)
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class TestDecisionVariable(unittest.TestCase):
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def test_bounds_valid_and_contains(self):
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v = DecisionVariable("t", DomainKind.BOUNDS, bounds=(0.0, 10.0))
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self.assertTrue(v.contains(5))
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self.assertTrue(v.contains(0))
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self.assertTrue(v.contains(10))
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self.assertFalse(v.contains(-0.1))
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self.assertFalse(v.contains(10.1))
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self.assertFalse(v.contains("x"))
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def test_bounds_reversed_rejected(self):
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with self.assertRaises(ProblemError):
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DecisionVariable("t", DomainKind.BOUNDS, bounds=(10.0, 0.0))
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def test_choices_domain(self):
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v = DecisionVariable("cat", DomainKind.CHOICES, choices=["A", "B"])
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self.assertTrue(v.contains("A"))
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self.assertFalse(v.contains("Z"))
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def test_integer_bounds_noninteger_rejected(self):
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with self.assertRaises(ProblemError):
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DecisionVariable("n", DomainKind.BOUNDS, bounds=(1.5, 5.0), integer=True)
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def test_integer_contains_and_clamp(self):
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v = DecisionVariable("n", DomainKind.BOUNDS, bounds=(0.0, 10.0), integer=True)
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self.assertFalse(v.contains(1.5))
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self.assertTrue(v.contains(3))
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# clamp 把越界夹回 + 取整
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self.assertEqual(v.clamp(12.4), 10.0)
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self.assertEqual(v.clamp(-3), 0.0)
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self.assertEqual(v.clamp(4.7), 5.0)
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def test_continuous_clamp(self):
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v = DecisionVariable("t", DomainKind.BOUNDS, bounds=(0.0, 10.0))
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self.assertEqual(v.clamp(15), 10)
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self.assertEqual(v.clamp(-2), 0)
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def test_empty_name_rejected(self):
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with self.assertRaises(ProblemError):
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DecisionVariable(" ", DomainKind.BOUNDS, bounds=(0, 1))
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def test_missing_domain_payload_rejected(self):
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with self.assertRaises(ProblemError):
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DecisionVariable("t", DomainKind.BOUNDS)
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with self.assertRaises(ProblemError):
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DecisionVariable("t", DomainKind.CHOICES, choices=[])
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def test_roundtrip(self):
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v = DecisionVariable("t", DomainKind.BOUNDS, "温度", "℃",
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bounds=(1.0, 2.0), initial=1.5)
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v2 = DecisionVariable.from_dict(v.to_dict())
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self.assertEqual(v2.bounds, v.bounds)
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self.assertEqual(v2.initial, v.initial)
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class TestObjective(unittest.TestCase):
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def test_evaluate_maximize(self):
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obj = ObjectiveSpec(Sense.MAXIMIZE, terms=[ObjectiveTerm("a", 2.0),
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ObjectiveTerm("b", -1.0)])
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self.assertEqual(obj.evaluate({"a": 3, "b": 1}), 5.0)
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# 未知变量按 0
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self.assertEqual(obj.evaluate({"a": 3}), 6.0)
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def test_minimize_label(self):
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self.assertEqual(Sense.MINIMIZE.label, "最小化")
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self.assertEqual(Sense.MAXIMIZE.label, "最大化")
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def test_unknown_sense_rejected(self):
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with self.assertRaises(ProblemError):
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ObjectiveSpec.from_dict({"sense": "extreme"})
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def test_roundtrip_with_target(self):
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obj = ObjectiveSpec(Sense.MAXIMIZE, target="Ti_purity", target_value=99.5,
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terms=[ObjectiveTerm("a", 0.5)])
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obj2 = ObjectiveSpec.from_dict(obj.to_dict())
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self.assertEqual(obj2.target, "Ti_purity")
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self.assertEqual(obj2.target_value, 99.5)
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self.assertEqual(obj2.terms[0].coefficient, 0.5)
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class TestConstraint(unittest.TestCase):
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def test_box_satisfied(self):
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c = ConstraintSpec(ConstraintKind.BOX, variable="t", bounds=(0, 10))
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self.assertTrue(c.satisfied_by({"t": 5}))
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self.assertFalse(c.satisfied_by({"t": 11}))
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# 未知取值不判
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self.assertTrue(c.satisfied_by({}))
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def test_linear_ops(self):
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c = ConstraintSpec(ConstraintKind.LINEAR, coefficients={"a": 1, "b": 1},
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op="<=", rhs=10)
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self.assertTrue(c.satisfied_by({"a": 4, "b": 6}))
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self.assertFalse(c.satisfied_by({"a": 6, "b": 6}))
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# 部分未知视为未约束
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self.assertTrue(c.satisfied_by({"a": 4}))
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def test_ratio_constraint(self):
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c = ConstraintSpec(ConstraintKind.RATIO, numerator="x", denominator="y",
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op=">=", value=0.5)
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self.assertTrue(c.satisfied_by({"x": 1, "y": 2}))
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self.assertFalse(c.satisfied_by({"x": 1, "y": 4}))
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# 分母为 0 视为未约束
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self.assertTrue(c.satisfied_by({"x": 1, "y": 0}))
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def test_forbidden_combination(self):
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c = ConstraintSpec(ConstraintKind.FORBIDDEN, combination={"cat": "C"})
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self.assertFalse(c.satisfied_by({"cat": "C"}))
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self.assertTrue(c.satisfied_by({"cat": "A"}))
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# 多键需全部命中才算触发
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c2 = ConstraintSpec(ConstraintKind.FORBIDDEN,
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combination={"cat": "C", "t": 900})
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self.assertTrue(c2.satisfied_by({"cat": "C", "t": 100}))
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self.assertFalse(c2.satisfied_by({"cat": "C", "t": 900}))
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def test_linear_bad_op_rejected(self):
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with self.assertRaises(ProblemError):
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ConstraintSpec(ConstraintKind.LINEAR, coefficients={"a": 1}, op="~=")
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with self.assertRaises(ProblemError):
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ConstraintSpec(ConstraintKind.LINEAR, op="<=")
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def test_errors_against_unknown_var(self):
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c = ConstraintSpec(ConstraintKind.BOX, variable="missing", bounds=(0, 1))
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self.assertTrue(c.errors_against({"t": object()}))
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def test_roundtrip(self):
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c = ConstraintSpec(ConstraintKind.LINEAR, reason="x",
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coefficients={"a": 1.0}, op=">=", rhs=5)
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c2 = ConstraintSpec.from_dict(c.to_dict())
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self.assertEqual(c2.op, ">=")
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self.assertEqual(c2.rhs, 5)
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class TestOptimizationProblem(unittest.TestCase):
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def test_validate_ok(self):
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self.assertEqual(_ti_problem().validate(), [])
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def test_validate_duplicate_variable(self):
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p = _ti_problem()
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p.variables.append(DecisionVariable("clf_temp", DomainKind.BOUNDS,
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bounds=(0, 1)))
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errs = p.validate()
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self.assertTrue(any("重复定义" in e for e in errs))
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def test_validate_unknown_var_in_objective(self):
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p = _ti_problem()
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p.objective.terms.append(ObjectiveTerm("nope"))
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errs = p.validate()
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self.assertTrue(any("nope" in e for e in errs))
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def test_validate_unknown_var_in_constraint(self):
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p = _ti_problem()
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p.constraints.append(ConstraintSpec(ConstraintKind.BOX, variable="ghost",
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bounds=(0, 1)))
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errs = p.validate()
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self.assertTrue(any("ghost" in e for e in errs))
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def test_is_feasible_and_violated(self):
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p = _ti_problem()
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# 合法取值
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self.assertTrue(p.is_feasible({"clf_temp": 850, "cl2_ratio": 1.0,
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"catalyst": "A"}))
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# 越出 box 收紧（820~900）
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self.assertFalse(p.is_feasible({"clf_temp": 910, "cl2_ratio": 1.0,
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"catalyst": "A"}))
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# forbidden 组合
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self.assertFalse(p.is_feasible({"clf_temp": 850, "cl2_ratio": 1.0,
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"catalyst": "C"}))
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viol = p.violated_constraints({"clf_temp": 950, "cl2_ratio": 1.0,
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"catalyst": "A"})
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self.assertGreater(len(viol), 0)
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def test_roundtrip(self):
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p = _ti_problem()
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p2 = OptimizationProblem.from_dict(p.to_dict())
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self.assertEqual([v.name for v in p2.variables],
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[v.name for v in p.variables])
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self.assertEqual(p2.objective.sense, p.objective.sense)
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self.assertEqual(len(p2.constraints), len(p.constraints))
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class TestLoadProblemYaml(unittest.TestCase):
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def test_load_template(self):
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self.assertTrue(os.path.exists(CONFIG_PATH), f"缺少模板 {CONFIG_PATH}")
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p = load_problem(CONFIG_PATH)
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names = [v.name for v in p.variables]
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self.assertEqual(names, ["clf_temp", "cl2_ratio", "feed_rate", "catalyst"])
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# 校验通过
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self.assertEqual(p.validate(), [])
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# 目标与约束就位
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self.assertEqual(p.objective.target, "Ti_purity")
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self.assertEqual(p.objective.target_value, 99.5)
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kinds = {c.kind for c in p.constraints}
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self.assertEqual(kinds, {ConstraintKind.BOX, ConstraintKind.LINEAR,
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ConstraintKind.RATIO, ConstraintKind.FORBIDDEN})
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# 合法初值可行
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self.assertTrue(p.is_feasible({"clf_temp": 850, "cl2_ratio": 1.0,
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"feed_rate": 450, "catalyst": "A"}))
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def test_load_choices_parsed(self):
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p = load_problem(CONFIG_PATH)
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cat = p.variable_map["catalyst"]
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self.assertEqual(cat.kind, DomainKind.CHOICES)
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self.assertEqual(cat.choices, ["A", "B", "C"])
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def test_integer_flag_parsed(self):
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# feed_rate integer: false
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p = load_problem(CONFIG_PATH)
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self.assertFalse(p.variable_map["feed_rate"].integer)
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class TestScalarParser(unittest.TestCase):
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"""直接覆盖 _parse_scalar 的边界（内联列表/映射/数字/字符串/布尔）。"""
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def test_scalars(self):
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from recipe_optim.problem import _parse_scalar
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self.assertEqual(_parse_scalar("1"), 1)
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self.assertEqual(_parse_scalar("1.5"), 1.5)
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self.assertIs(_parse_scalar("true"), True)
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self.assertIs(_parse_scalar("False"), False)
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self.assertEqual(_parse_scalar("99.5"), 99.5)
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self.assertEqual(_parse_scalar('"A"'), "A")
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self.assertEqual(_parse_scalar("[1, 2, 3]"), [1, 2, 3])
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self.assertEqual(_parse_scalar("[A, B]"), ["A", "B"])
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self.assertEqual(_parse_scalar("{a: 1, b: 2}"), {"a": 1, "b": 2})
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if __name__ == "__main__":
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unittest.main()
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