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activate tests
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‎test/runtests.jl‎

Lines changed: 111 additions & 111 deletions
Original file line numberDiff line numberDiff line change
@@ -5,125 +5,125 @@ using LinearAlgebra, Printf, SparseArrays, Test
55
using ADNLPModels,
66
LinearOperators, NLPModels, NLPModelsModifiers, NLPModelsTest, QPSReader, QuadraticModels
77

8-
# @testset "test utils" begin
9-
# A = rand(10, 10)
10-
# @test nnz(A) == 100
11-
# @test nnz(Diagonal(A)) == 10
12-
# @test nnz(Symmetric(A)) == 55
13-
# v1, v2 = rand(10), rand(9)
14-
# @test nnz(SymTridiagonal(v1, v2)) == 19
15-
# end
8+
@testset "test utils" begin
9+
A = rand(10, 10)
10+
@test nnz(A) == 100
11+
@test nnz(Diagonal(A)) == 10
12+
@test nnz(Symmetric(A)) == 55
13+
v1, v2 = rand(10), rand(9)
14+
@test nnz(SymTridiagonal(v1, v2)) == 19
15+
end
1616

17-
# # Definition of quadratic problems
18-
# qp_problems_Matrix = ["bndqp", "eqconqp"]
19-
# qp_problems_COO = ["uncqp", "ineqconqp"]
20-
# for qp in [qp_problems_Matrix; qp_problems_COO]
21-
# include(joinpath("problems", "$qp.jl"))
22-
# end
17+
# Definition of quadratic problems
18+
qp_problems_Matrix = ["bndqp", "eqconqp"]
19+
qp_problems_COO = ["uncqp", "ineqconqp"]
20+
for qp in [qp_problems_Matrix; qp_problems_COO]
21+
include(joinpath("problems", "$qp.jl"))
22+
end
2323

24-
# include("test_consistency.jl")
24+
include("test_consistency.jl")
2525

26-
# function testSM(sm) # test function for a specific problem
27-
# @test (sm.meta.ncon == 2 && sm.meta.nvar == 5)
28-
# @test sm.meta.lcon == sm.meta.ucon
29-
# lvar_sm_true = [0.0; 0.0; 0.0; -4.0; -3.0]
30-
# uvar_sm_true = [Inf; Inf; Inf; Inf; -2.0]
31-
# H_sm_true = sparse(
32-
# [
33-
# 6.0 0.0 0.0 0.0 0.0
34-
# 2.0 5.0 0.0 0.0 0.0
35-
# 1.0 2.0 4.0 0.0 0.0
36-
# 0.0 0.0 0.0 0.0 0.0
37-
# 0.0 0.0 0.0 0.0 0.0
38-
# ],
39-
# )
40-
# A_sm_true = sparse([
41-
# 1.0 0.0 1.0 0.0 -1.0
42-
# 0.0 2.0 1.0 -1.0 0.0
43-
# ])
26+
function testSM(sm) # test function for a specific problem
27+
@test (sm.meta.ncon == 2 && sm.meta.nvar == 5)
28+
@test sm.meta.lcon == sm.meta.ucon
29+
lvar_sm_true = [0.0; 0.0; 0.0; -4.0; -3.0]
30+
uvar_sm_true = [Inf; Inf; Inf; Inf; -2.0]
31+
H_sm_true = sparse(
32+
[
33+
6.0 0.0 0.0 0.0 0.0
34+
2.0 5.0 0.0 0.0 0.0
35+
1.0 2.0 4.0 0.0 0.0
36+
0.0 0.0 0.0 0.0 0.0
37+
0.0 0.0 0.0 0.0 0.0
38+
],
39+
)
40+
A_sm_true = sparse([
41+
1.0 0.0 1.0 0.0 -1.0
42+
0.0 2.0 1.0 -1.0 0.0
43+
])
4444

45-
# @test all(lvar_sm_true .== sm.meta.lvar)
46-
# @test all(uvar_sm_true .== sm.meta.uvar)
47-
# @test all(sparse(sm.data.Arows, sm.data.Acols, sm.data.Avals, 2, 5) .== A_sm_true)
48-
# @test all(sparse(sm.data.Hrows, sm.data.Hcols, sm.data.Hvals, 5, 5) .== H_sm_true)
49-
# end
45+
@test all(lvar_sm_true .== sm.meta.lvar)
46+
@test all(uvar_sm_true .== sm.meta.uvar)
47+
@test all(sparse(sm.data.Arows, sm.data.Acols, sm.data.Avals, 2, 5) .== A_sm_true)
48+
@test all(sparse(sm.data.Hrows, sm.data.Hcols, sm.data.Hvals, 5, 5) .== H_sm_true)
49+
end
5050

51-
# @testset "SlackModel" begin
52-
# H = [
53-
# 6.0 2.0 1.0
54-
# 2.0 5.0 2.0
55-
# 1.0 2.0 4.0
56-
# ]
57-
# c = [-8.0; -3; -3]
58-
# A = [
59-
# 1.0 0.0 1.0
60-
# 0.0 2.0 1.0
61-
# ]
62-
# b = [0.0; 3]
63-
# l = [0.0; 0; 0]
64-
# u = [Inf; Inf; Inf]
65-
# T = eltype(c)
66-
# qp = QuadraticModel(
67-
# c,
68-
# sparse(H),
69-
# A = A,
70-
# lcon = [-3.0; -4.0],
71-
# ucon = [-2.0; Inf],
72-
# lvar = l,
73-
# uvar = u,
74-
# c0 = 0.0,
75-
# name = "QM1",
76-
# )
77-
# sm = SlackModel(qp)
78-
# testSM(sm)
51+
@testset "SlackModel" begin
52+
H = [
53+
6.0 2.0 1.0
54+
2.0 5.0 2.0
55+
1.0 2.0 4.0
56+
]
57+
c = [-8.0; -3; -3]
58+
A = [
59+
1.0 0.0 1.0
60+
0.0 2.0 1.0
61+
]
62+
b = [0.0; 3]
63+
l = [0.0; 0; 0]
64+
u = [Inf; Inf; Inf]
65+
T = eltype(c)
66+
qp = QuadraticModel(
67+
c,
68+
sparse(H),
69+
A = A,
70+
lcon = [-3.0; -4.0],
71+
ucon = [-2.0; Inf],
72+
lvar = l,
73+
uvar = u,
74+
c0 = 0.0,
75+
name = "QM1",
76+
)
77+
sm = SlackModel(qp)
78+
testSM(sm)
7979

80-
# SlackModel!(qp)
81-
# testSM(qp)
80+
SlackModel!(qp)
81+
testSM(qp)
8282

83-
# qpdense = QuadraticModel(
84-
# c,
85-
# H,
86-
# A = A,
87-
# lcon = [-3.0; -4.0],
88-
# ucon = [-2.0; Inf],
89-
# lvar = l,
90-
# uvar = u,
91-
# c0 = 0.0,
92-
# name = "QM1",
93-
# )
94-
# smdense = SlackModel(qpdense)
95-
# testSM(smdense)
96-
# end
83+
qpdense = QuadraticModel(
84+
c,
85+
H,
86+
A = A,
87+
lcon = [-3.0; -4.0],
88+
ucon = [-2.0; Inf],
89+
lvar = l,
90+
uvar = u,
91+
c0 = 0.0,
92+
name = "QM1",
93+
)
94+
smdense = SlackModel(qpdense)
95+
testSM(smdense)
96+
end
9797

98-
# @testset "sort cols COO" begin
99-
# Hrows = [1; 2; 1; 3]
100-
# Hcols = [2; 1; 4; 4]
101-
# Hvals = [1.0; 2.0; 3.0; 4.0]
102-
# Arows = [2; 2; 1; 4]
103-
# Acols = [4; 3; 1; 2]
104-
# Avals = [-1.0; -2.0; -3.0; -4.0]
105-
# c = [-8.0; -3; -3; 2.0]
106-
# l = [0.0; 0; 0; 0]
107-
# u = [Inf; Inf; Inf; Inf]
108-
# qp = QuadraticModel(
109-
# c,
110-
# Hrows,
111-
# Hcols,
112-
# Hvals,
113-
# Arows = Arows,
114-
# Acols = Acols,
115-
# Avals = Avals,
116-
# lcon = [-3.0; -4.0; 2.0; 1.0],
117-
# ucon = [-2.0; Inf; Inf; Inf],
118-
# lvar = l,
119-
# uvar = u,
120-
# c0 = 0.0,
121-
# name = "QM1",
122-
# sortcols = true,
123-
# )
124-
# @test issorted(Hcols)
125-
# @test issorted(Acols)
126-
# end
98+
@testset "sort cols COO" begin
99+
Hrows = [1; 2; 1; 3]
100+
Hcols = [2; 1; 4; 4]
101+
Hvals = [1.0; 2.0; 3.0; 4.0]
102+
Arows = [2; 2; 1; 4]
103+
Acols = [4; 3; 1; 2]
104+
Avals = [-1.0; -2.0; -3.0; -4.0]
105+
c = [-8.0; -3; -3; 2.0]
106+
l = [0.0; 0; 0; 0]
107+
u = [Inf; Inf; Inf; Inf]
108+
qp = QuadraticModel(
109+
c,
110+
Hrows,
111+
Hcols,
112+
Hvals,
113+
Arows = Arows,
114+
Acols = Acols,
115+
Avals = Avals,
116+
lcon = [-3.0; -4.0; 2.0; 1.0],
117+
ucon = [-2.0; Inf; Inf; Inf],
118+
lvar = l,
119+
uvar = u,
120+
c0 = 0.0,
121+
name = "QM1",
122+
sortcols = true,
123+
)
124+
@test issorted(Hcols)
125+
@test issorted(Acols)
126+
end
127127

128128
@testset "LinearOperators" begin
129129
nvar, ncon = 10, 7

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