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jcarpentjcarpent
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Merge pull request #299 from jorisv/topic/fix_unit_tests_scipy_1_12
Fix broken unit tests with scipy 1.12
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‎CHANGELOG.md‎

Lines changed: 3 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -6,6 +6,9 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
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## [Unreleased]
88

9+
### Fixed
10+
* Fix Python tests with scipy>=1.12 ([#299](https://github.com/Simple-Robotics/proxsuite/pull/299))
11+
912
## [0.6.2] - 2024-01-22
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1114
### Fixed

‎test/src/dense_qp_wrapper.py‎

Lines changed: 32 additions & 34 deletions
Original file line numberDiff line numberDiff line change
@@ -3319,7 +3319,7 @@ def test_case_update_A_for_different_initial_guess(self):
33193319
"---testing sparse random strongly convex qp with equality and inequality constraints: test update A for different initial guess---"
33203320
)
33213321
n = 10
3322-
H, g, A_old, b, C, u, l = generate_mixed_qp(n)
3322+
H, g, A_old, b_old, C, u, l = generate_mixed_qp(n)
33233323
n_eq = A_old.shape[0]
33243324
n_in = C.shape[0]
33253325
qp = proxsuite.proxqp.dense.QP(n, n_eq, n_in)
@@ -3330,42 +3330,40 @@ def test_case_update_A_for_different_initial_guess(self):
33303330
H,
33313331
np.asfortranarray(g),
33323332
A_old,
3333-
np.asfortranarray(b),
3333+
np.asfortranarray(b_old),
33343334
C,
33353335
np.asfortranarray(l),
33363336
np.asfortranarray(u),
33373337
True,
33383338
)
33393339
qp.solve()
3340-
A = spa.random(
3341-
n_eq, n, density=0.15, data_rvs=np.random.randn, format="csc"
3342-
).toarray()
3340+
_, _, A_new, b_new, _, _, _ = generate_mixed_qp(n, seed=2)
33433341
dua_res = normInf(
33443342
H @ qp.results.x
33453343
+ g
33463344
+ A_old.transpose() @ qp.results.y
33473345
+ C.transpose() @ qp.results.z
33483346
)
33493347
pri_res = max(
3350-
normInf(A_old @ qp.results.x - b),
3348+
normInf(A_old @ qp.results.x - b_old),
33513349
normInf(
33523350
np.maximum(C @ qp.results.x - u, 0)
33533351
+ np.minimum(C @ qp.results.x - l, 0)
33543352
),
33553353
)
33563354
assert dua_res <= 1e-9
33573355
assert pri_res <= 1e-9
3358-
qp.update(A=A)
3359-
assert normInf(qp.model.A - A) <= 1.0e-9
3356+
qp.update(A=A_new, b=b_new)
3357+
assert normInf(qp.model.A - A_new) <= 1.0e-9
33603358
qp.solve()
33613359
dua_res = normInf(
33623360
H @ qp.results.x
33633361
+ g
3364-
+ A.transpose() @ qp.results.y
3362+
+ A_new.transpose() @ qp.results.y
33653363
+ C.transpose() @ qp.results.z
33663364
)
33673365
pri_res = max(
3368-
normInf(A @ qp.results.x - b),
3366+
normInf(A_new @ qp.results.x - b_new),
33693367
normInf(
33703368
np.maximum(C @ qp.results.x - u, 0)
33713369
+ np.minimum(C @ qp.results.x - l, 0)
@@ -3392,7 +3390,7 @@ def test_case_update_A_for_different_initial_guess(self):
33923390
H,
33933391
np.asfortranarray(g),
33943392
A_old,
3395-
np.asfortranarray(b),
3393+
np.asfortranarray(b_old),
33963394
C,
33973395
np.asfortranarray(l),
33983396
np.asfortranarray(u),
@@ -3406,25 +3404,25 @@ def test_case_update_A_for_different_initial_guess(self):
34063404
+ C.transpose() @ qp2.results.z
34073405
)
34083406
pri_res = max(
3409-
normInf(A_old @ qp2.results.x - b),
3407+
normInf(A_old @ qp2.results.x - b_old),
34103408
normInf(
34113409
np.maximum(C @ qp2.results.x - u, 0)
34123410
+ np.minimum(C @ qp2.results.x - l, 0)
34133411
),
34143412
)
34153413
assert dua_res <= 1e-9
34163414
assert pri_res <= 1e-9
3417-
qp2.update(A=A)
3418-
assert normInf(qp.model.A - A) <= 1.0e-9
3415+
qp2.update(A=A_new, b=b_new)
3416+
assert normInf(qp.model.A - A_new) <= 1.0e-9
34193417
qp2.solve()
34203418
dua_res = normInf(
34213419
H @ qp2.results.x
34223420
+ g
3423-
+ A.transpose() @ qp2.results.y
3421+
+ A_new.transpose() @ qp2.results.y
34243422
+ C.transpose() @ qp2.results.z
34253423
)
34263424
pri_res = max(
3427-
normInf(A @ qp2.results.x - b),
3425+
normInf(A_new @ qp2.results.x - b_new),
34283426
normInf(
34293427
np.maximum(C @ qp2.results.x - u, 0)
34303428
+ np.minimum(C @ qp2.results.x - l, 0)
@@ -3451,7 +3449,7 @@ def test_case_update_A_for_different_initial_guess(self):
34513449
H,
34523450
np.asfortranarray(g),
34533451
A_old,
3454-
np.asfortranarray(b),
3452+
np.asfortranarray(b_old),
34553453
C,
34563454
np.asfortranarray(l),
34573455
np.asfortranarray(u),
@@ -3465,25 +3463,25 @@ def test_case_update_A_for_different_initial_guess(self):
34653463
+ C.transpose() @ qp3.results.z
34663464
)
34673465
pri_res = max(
3468-
normInf(A_old @ qp3.results.x - b),
3466+
normInf(A_old @ qp3.results.x - b_old),
34693467
normInf(
34703468
np.maximum(C @ qp3.results.x - u, 0)
34713469
+ np.minimum(C @ qp3.results.x - l, 0)
34723470
),
34733471
)
34743472
assert dua_res <= 1e-9
34753473
assert pri_res <= 1e-9
3476-
qp3.update(A=A)
3477-
assert normInf(qp.model.A - A) <= 1.0e-9
3474+
qp3.update(A=A_new, b=b_new)
3475+
assert normInf(qp.model.A - A_new) <= 1.0e-9
34783476
qp3.solve()
34793477
dua_res = normInf(
34803478
H @ qp3.results.x
34813479
+ g
3482-
+ A.transpose() @ qp3.results.y
3480+
+ A_new.transpose() @ qp3.results.y
34833481
+ C.transpose() @ qp3.results.z
34843482
)
34853483
pri_res = max(
3486-
normInf(A @ qp3.results.x - b),
3484+
normInf(A_new @ qp3.results.x - b_new),
34873485
normInf(
34883486
np.maximum(C @ qp3.results.x - u, 0)
34893487
+ np.minimum(C @ qp3.results.x - l, 0)
@@ -3510,7 +3508,7 @@ def test_case_update_A_for_different_initial_guess(self):
35103508
H,
35113509
np.asfortranarray(g),
35123510
A_old,
3513-
np.asfortranarray(b),
3511+
np.asfortranarray(b_old),
35143512
C,
35153513
np.asfortranarray(l),
35163514
np.asfortranarray(u),
@@ -3524,25 +3522,25 @@ def test_case_update_A_for_different_initial_guess(self):
35243522
+ C.transpose() @ qp4.results.z
35253523
)
35263524
pri_res = max(
3527-
normInf(A_old @ qp4.results.x - b),
3525+
normInf(A_old @ qp4.results.x - b_old),
35283526
normInf(
35293527
np.maximum(C @ qp4.results.x - u, 0)
35303528
+ np.minimum(C @ qp4.results.x - l, 0)
35313529
),
35323530
)
35333531
assert dua_res <= 1e-9
35343532
assert pri_res <= 1e-9
3535-
qp4.update(A=A)
3536-
assert normInf(qp.model.A - A) <= 1.0e-9
3533+
qp4.update(A=A_new, b=b_new)
3534+
assert normInf(qp.model.A - A_new) <= 1.0e-9
35373535
qp4.solve()
35383536
dua_res = normInf(
35393537
H @ qp4.results.x
35403538
+ g
3541-
+ A.transpose() @ qp4.results.y
3539+
+ A_new.transpose() @ qp4.results.y
35423540
+ C.transpose() @ qp4.results.z
35433541
)
35443542
pri_res = max(
3545-
normInf(A @ qp4.results.x - b),
3543+
normInf(A_new @ qp4.results.x - b_new),
35463544
normInf(
35473545
np.maximum(C @ qp4.results.x - u, 0)
35483546
+ np.minimum(C @ qp4.results.x - l, 0)
@@ -3567,7 +3565,7 @@ def test_case_update_A_for_different_initial_guess(self):
35673565
H,
35683566
np.asfortranarray(g),
35693567
A_old,
3570-
np.asfortranarray(b),
3568+
np.asfortranarray(b_old),
35713569
C,
35723570
np.asfortranarray(l),
35733571
np.asfortranarray(u),
@@ -3581,25 +3579,25 @@ def test_case_update_A_for_different_initial_guess(self):
35813579
+ C.transpose() @ qp5.results.z
35823580
)
35833581
pri_res = max(
3584-
normInf(A_old @ qp5.results.x - b),
3582+
normInf(A_old @ qp5.results.x - b_old),
35853583
normInf(
35863584
np.maximum(C @ qp5.results.x - u, 0)
35873585
+ np.minimum(C @ qp5.results.x - l, 0)
35883586
),
35893587
)
35903588
assert dua_res <= 1e-9
35913589
assert pri_res <= 1e-9
3592-
qp5.update(A=A)
3593-
assert normInf(qp.model.A - A) <= 1.0e-9
3590+
qp5.update(A=A_new, b=b_new)
3591+
assert normInf(qp.model.A - A_new) <= 1.0e-9
35943592
qp5.solve()
35953593
dua_res = normInf(
35963594
H @ qp5.results.x
35973595
+ g
3598-
+ A.transpose() @ qp5.results.y
3596+
+ A_new.transpose() @ qp5.results.y
35993597
+ C.transpose() @ qp5.results.z
36003598
)
36013599
pri_res = max(
3602-
normInf(A @ qp5.results.x - b),
3600+
normInf(A_new @ qp5.results.x - b_new),
36033601
normInf(
36043602
np.maximum(C @ qp5.results.x - u, 0)
36053603
+ np.minimum(C @ qp5.results.x - l, 0)

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