28686250335

Committed 03 Jul 2026 10:35PM UTC coverage: 79.634% (-7.5%) from 87.112%

Build # 28686250335

Build Type

Pull #13

github

Committed by

web-flow

Commit Message

Merge a13ea2d3d into f08badaa8

Pull Request Pull Request #13: Feat/multi objective

Coverage Stats

307 of 771 new or added lines in 13 files covered. (39.82%)

3 existing lines in 1 file now uncovered.

3957 of 4969 relevant lines covered (79.63%)

1.59 hits per line

Source File
Press 'n' to go to next uncovered line, 'b' for previous

98.63

/src/smt_optim/benchmarks/multiobj/constrained.py




import numpy as np
import smt.design_space as ds

from smt_optim.benchmarks.base import BenchmarkProblem


class BNH(BenchmarkProblem):

    def __init__(self):
        super().__init__()

        self.name: str = "BNH"

        self.num_dim: int = 2
        self.num_obj: int = 2
        self.num_cstr: int = 2
        self.num_fidelity = 1

        self.tags = [
            "multi-obj",
        ]

        self.bounds = np.array([
            [0, 5],
            [0, 3],
        ])

        self.objective = [
            self.f1, self.f2,
        ]

        self.constraints = [
            self.g1,
            self.g2,
        ]

    def f1(self, x):
        return 4*x[0]**2 + 4*x[1]**2

    def f2(self, x):
        return (x[0] - 5)**2 + (x[1] - 5)**2

    def g1(self, x):
        return (x[0] - 5)**2 + x[1]**2 - 25

    def g2(self, x):
        return -(x[0] - 8)**2 - (x[1] + 3)**2 + 7.7


class TNK(BenchmarkProblem):

    def __init__(self):
        super().__init__()

        self.name: str = "TNK"

        self.num_dim: int = 2
        self.num_obj: int = 2
        self.num_cstr: int = 2
        self.num_fidelity = 1

        self.tags = [
            "multi-obj",
        ]

        self.bounds = np.array([
            [0, np.pi],
            [0, np.pi],
        ])

        self.objective = [
            self.f1, self.f2,
        ]

        self.constraints = [
            self.g1,
            self.g2,
        ]

    def f1(self, x):
        return x[0]

    def f2(self, x):
        return x[1]

    def g1(self, x):
        return -x[0]**2 - x[1]**2 + 1 + 0.1 * np.cos(16*np.arctan(x[0]/x[1]))

    def g2(self, x):
        return (x[0] - 0.5)**2 + (x[1] - 0.5)**2 - 0.5


class OSY(BenchmarkProblem):

    def __init__(self):
        super().__init__()

        self.name: str = "OSY"

        self.num_dim: int = 6
        self.num_obj: int = 2
        self.num_cstr: int = 6
        self.num_fidelity = 1

        self.tags = [
            "multi-obj",
        ]

        self.bounds = np.array([
            [0., 10.],
            [0., 10.],
            [0., 5.],
            [0., 6.],
            [0., 5.],
            [0., 10.],
        ])

        self.objective = [
            self.f1, self.f2,
        ]

        self.constraints = [
            self.g1,
            self.g2,
            self.g3,
            self.g4,
            self.g5,
            self.g6,
        ]

    def f1(self, x):
        return -(25*(x[0] - 2)**2 + (x[1] - 2)**2 + (x[2] - 1)**2 + (x[3] - 4)**2 + (x[4] - 1)**2)

    def f2(self, x):
        return np.sum(x**2)

    def g1(self, x):
        return -x[0] - x[1] + 2

    def g2(self, x):
        return -6 + x[0] + x[1]

    def g3(self, x):
        return -2 + x[1] - x[0]

    def g4(self, x):
        return -2 + x[0] - 3*x[1]

    def g5(self, x):
        return -4 + (x[2] - 3)**2 + x[3]

    def g6(self, x):
        return -(x[4] - 3)**2 - x[5] + 4


if __name__ == "__main__":
    pass

1
2
3
4	import numpy as np	2✔
5	import smt.design_space as ds	2✔
6
7	from smt_optim.benchmarks.base import BenchmarkProblem	2✔
8
9
10	class BNH(BenchmarkProblem):	2✔
11
12	def __init__(self):	2✔
13	super().__init__()	2✔
14
15	self.name: str = "BNH"	2✔
16
17	self.num_dim: int = 2	2✔
18	self.num_obj: int = 2	2✔
19	self.num_cstr: int = 2	2✔
20	self.num_fidelity = 1	2✔
21
22	self.tags = [	2✔
23	"multi-obj",
24	]
25
26	self.bounds = np.array([	2✔
27	[0, 5],
28	[0, 3],
29	])
30
31	self.objective = [	2✔
32	self.f1, self.f2,
33	]
34
35	self.constraints = [	2✔
36	self.g1,
37	self.g2,
38	]
39
40	def f1(self, x):	2✔
41	return 4x[0]2 + 4x[1]**2	2✔
42
43	def f2(self, x):	2✔
44	return (x[0] - 5)2 + (x[1] - 5)2	2✔
45
46	def g1(self, x):	2✔
47	return (x[0] - 5)2 + x[1]2 - 25	2✔
48
49	def g2(self, x):	2✔
50	return -(x[0] - 8)2 - (x[1] + 3)2 + 7.7	2✔
51
52
53	class TNK(BenchmarkProblem):	2✔
54
55	def __init__(self):	2✔
56	super().__init__()	2✔
57
58	self.name: str = "TNK"	2✔
59
60	self.num_dim: int = 2	2✔
61	self.num_obj: int = 2	2✔
62	self.num_cstr: int = 2	2✔
63	self.num_fidelity = 1	2✔
64
65	self.tags = [	2✔
66	"multi-obj",
67	]
68
69	self.bounds = np.array([	2✔
70	[0, np.pi],
71	[0, np.pi],
72	])
73
74	self.objective = [	2✔
75	self.f1, self.f2,
76	]
77
78	self.constraints = [	2✔
79	self.g1,
80	self.g2,
81	]
82
83	def f1(self, x):	2✔
84	return x[0]	2✔
85
86	def f2(self, x):	2✔
87	return x[1]	2✔
88
89	def g1(self, x):	2✔
90	return -x[0]2 - x[1]2 + 1 + 0.1 * np.cos(16*np.arctan(x[0]/x[1]))	2✔
91
92	def g2(self, x):	2✔
93	return (x[0] - 0.5)2 + (x[1] - 0.5)2 - 0.5	2✔
94
95
96	class OSY(BenchmarkProblem):	2✔
97
98	def __init__(self):	2✔
99	super().__init__()	2✔
100
101	self.name: str = "OSY"	2✔
102
103	self.num_dim: int = 6	2✔
104	self.num_obj: int = 2	2✔
105	self.num_cstr: int = 6	2✔
106	self.num_fidelity = 1	2✔
107
108	self.tags = [	2✔
109	"multi-obj",
110	]
111
112	self.bounds = np.array([	2✔
113	[0., 10.],
114	[0., 10.],
115	[0., 5.],
116	[0., 6.],
117	[0., 5.],
118	[0., 10.],
119	])
120
121	self.objective = [	2✔
122	self.f1, self.f2,
123	]
124
125	self.constraints = [	2✔
126	self.g1,
127	self.g2,
128	self.g3,
129	self.g4,
130	self.g5,
131	self.g6,
132	]
133
134	def f1(self, x):	2✔
135	return -(25(x[0] - 2)2 + (x[1] - 2)2 + (x[2] - 1)2 + (x[3] - 4)2 + (x[4] - 1)*2)	2✔
136
137	def f2(self, x):	2✔
138	return np.sum(x**2)	2✔
139
140	def g1(self, x):	2✔
141	return -x[0] - x[1] + 2	2✔
142
143	def g2(self, x):	2✔
144	return -6 + x[0] + x[1]	2✔
145
146	def g3(self, x):	2✔
147	return -2 + x[1] - x[0]	2✔
148
149	def g4(self, x):	2✔
150	return -2 + x[0] - 3*x[1]	2✔
151
152	def g5(self, x):	2✔
153	return -4 + (x[2] - 3)**2 + x[3]	2✔
154
155	def g6(self, x):	2✔
156	return -(x[4] - 3)**2 - x[5] + 4	2✔
157
158
159	if __name__ == "__main__":	2✔
NEW 160	pass	×

SMTorg / smt-optim / 28686250335

Source File Press 'n' to go to next uncovered line, 'b' for previous

Source File
Press 'n' to go to next uncovered line, 'b' for previous