Merge branch 'master' into update_ivc

.github/workflows/openmdao_test_workflow.yml

@@ -81,7 +81,7 @@ jobs:
             OS: ubuntu-latest
             PY: '3.11'
             NUMPY: '1.26'
-            SCIPY: '1.11'
+            SCIPY: '1.12'
             PETSc: '3.18'
             PYOPTSPARSE: 'v2.10.1'
             # PAROPT: true
@@ -98,7 +98,7 @@ jobs:
             OS: macos-latest
             PY: '3.11'
             NUMPY: '1.26'
-            SCIPY: '1.11'
+            SCIPY: '1.12'
             PETSc: '3.18'
             # PYOPTSPARSE: 'v2.10.1'
             # PAROPT: true
@@ -112,7 +112,7 @@ jobs:
             OS: ubuntu-latest
             PY: '3.11'
             NUMPY: '1.26'
-            SCIPY: '1.11'
+            SCIPY: '1.12'
             OPTIONAL: '[test]'
             TESTS: true
             EXCLUDE: ${{ github.event_name == 'workflow_dispatch'  && ! inputs.Ubuntu_Minimal }}
@@ -137,7 +137,7 @@ jobs:
             OS: ubuntu-latest
             PY: '3.11'
             NUMPY: '1.26'
-            SCIPY: '1.11'
+            SCIPY: '1.12'
             PETSc: '3.18'
             PYOPTSPARSE: 'v2.10.1'
             SNOPT: '7.7'
@@ -554,7 +554,7 @@ jobs:
           - NAME: Windows Baseline
             PY: '3.11'
             NUMPY: '1.24'
-            SCIPY: '1.11'
+            SCIPY: '1.12'
             PYOPTSPARSE: '2.10.1'
             BANDIT: true
             EXCLUDE: ${{ github.event_name == 'workflow_dispatch'  && ! inputs.Windows_Baseline }}

openmdao/core/tests/test_approx_derivs.py

@@ -2,7 +2,12 @@
 import time
 import unittest
 
+from packaging.version import Version
+
 import numpy as np
+from scipy import __version__ as scipy_version
+
+ScipyVersion = Version(scipy_version)
 
 import openmdao.api as om
 from openmdao.test_suite.components.impl_comp_array import TestImplCompArray, TestImplCompArrayDense
@@ -279,7 +284,7 @@ def compute_partials(self, inputs, partials):
         model.add_design_var('p2.x2')
         model.add_constraint('comp.y1')
         model.add_constraint('comp.y2')
-        
+
         prob.setup()
         prob.run_model()
         model.run_linearize(driver=prob.driver)
@@ -1083,7 +1088,7 @@ def compute_partials(self, inputs, partials):
         model.add_design_var('p2.x2')
         model.add_constraint('comp.y1')
         model.add_constraint('comp.y2')
-        
+
         prob.setup()
         prob.run_model()
         model.run_linearize(driver=prob.driver)
@@ -1586,6 +1591,8 @@ def test_newton_with_krylov_solver(self):
         assert_near_equal(J['con1', 'z'][0][1], -0.78449158, 1.0e-6)
         assert_near_equal(J['con1', 'x'][0][0], -0.98061448, 1.0e-6)
 
+    @unittest.skipUnless(ScipyVersion < Version("1.13"),
+                         "scipy < 1.13 is required, see issue #3156.")
     def test_newton_with_cscjac_under_cs(self):
         # Basic sellar test.
 

openmdao/drivers/tests/test_scipy_optimizer.py

@@ -9,6 +9,8 @@
 import numpy as np
 from scipy import __version__ as scipy_version
 
+ScipyVersion = Version(scipy_version)
+
 import openmdao.api as om
 from openmdao.test_suite.components.expl_comp_array import TestExplCompArrayDense, TestExplCompArraySparse, TestExplCompArrayJacVec
 from openmdao.test_suite.components.paraboloid import Paraboloid
@@ -1234,7 +1236,7 @@ def test_sellar_mdf_COBYLA(self):
         assert_near_equal(prob['z'][1], 0.0, 1e-3)
         assert_near_equal(prob['x'], 0.0, 1e-3)
 
-    @unittest.skipUnless(Version(scipy_version) >= Version("1.1"),
+    @unittest.skipUnless(ScipyVersion >= Version("1.1"),
                          "scipy >= 1.1 is required.")
     def test_trust_constr(self):
 
@@ -1276,7 +1278,7 @@ def compute(self, inputs, outputs, discrete_inputs=None, discrete_outputs=None):
         self.assertTrue(prob['c'] < 10)
         self.assertTrue(prob['c'] > 0)
 
-    @unittest.skipUnless(Version(scipy_version) >= Version("1.1"),
+    @unittest.skipUnless(ScipyVersion >= Version("1.1"),
                          "scipy >= 1.1 is required.")
     def test_trust_constr_hess_option(self):
 
@@ -1319,7 +1321,7 @@ def compute(self, inputs, outputs, discrete_inputs=None, discrete_outputs=None):
         self.assertTrue(prob['c'] < 10)
         self.assertTrue(prob['c'] > 0)
 
-    @unittest.skipUnless(Version(scipy_version) >= Version("1.1"),
+    @unittest.skipUnless(ScipyVersion >= Version("1.1"),
                          "scipy >= 1.1 is required.")
     def test_trust_constr_equality_con(self):
 
@@ -1360,7 +1362,7 @@ def compute(self, inputs, outputs, discrete_inputs=None, discrete_outputs=None):
 
         assert_near_equal(prob['con.c'], 1., 1e-3)
 
-    @unittest.skipUnless(Version(scipy_version) >= Version("1.2"),
+    @unittest.skipUnless(ScipyVersion >= Version("1.2"),
                          "scipy >= 1.2 is required.")
     def test_trust_constr_inequality_con(self):
 
@@ -1398,7 +1400,7 @@ def compute(self, inputs, outputs, discrete_inputs=None, discrete_outputs=None):
 
         assert_near_equal(prob['c'], 1.0, 1e-2)
 
-    @unittest.skipUnless(Version(scipy_version) >= Version("1.2"),
+    @unittest.skipUnless(ScipyVersion >= Version("1.2"),
                          "scipy >= 1.2 is required.")
     def test_trust_constr_bounds(self):
         class Rosenbrock(om.ExplicitComponent):
@@ -1652,10 +1654,11 @@ def test_call_final_setup(self):
 
         prob.setup()
 
-        expected_msg = \
-            "Problem .*: run_model must be called before total derivatives can be checked\."
-        with self.assertRaisesRegex(RuntimeError, expected_msg):
-            totals = prob.check_totals(method='fd', out_stream=False)
+        with self.assertRaises(RuntimeError) as cm:
+            prob.check_totals(method='fd', out_stream=False)
+
+        self.assertEqual(str(cm.exception), f"Problem {prob._get_inst_id()}: "
+                         "run_model must be called before total derivatives can be checked.")
 
     def test_cobyla_linear_constraint(self):
         # Bug where ScipyOptimizeDriver tried to compute and cache the constraint derivatives for the
@@ -1793,7 +1796,7 @@ def compute_partials(self, inputs, partials):
         assert_near_equal(prob['x'], np.array([0.234171, -0.1000]), 1e-3)
         assert_near_equal(prob['f'], -0.907267, 1e-3)
 
-    @unittest.skipUnless(Version(scipy_version) >= Version("1.2"),
+    @unittest.skipUnless(ScipyVersion >= Version("1.2"),
                          "scipy >= 1.2 is required.")
     def test_dual_annealing_rastrigin(self):
         # Example from the Scipy documentation
@@ -1901,7 +1904,7 @@ def compute(self, inputs, outputs, discrete_inputs=None, discrete_outputs=None):
         assert_near_equal(prob['x'], -np.ones(size), 1e-2)
         assert_near_equal(prob['f'], 3.0, 1e-2)
 
-    @unittest.skipUnless(Version(scipy_version) >= Version("1.4"),
+    @unittest.skipUnless(ScipyVersion >= Version("1.4"),
                          "scipy >= 1.4 is required.")
     def test_differential_evolution_constrained_linear(self):
         # Source of example:
@@ -1935,8 +1938,8 @@ def test_differential_evolution_constrained_linear(self):
         assert_near_equal(prob['x'], [0.96632622, 0.93367155], 1e-2)
         assert_near_equal(prob['f'], 0.0011352416852625719, 1e-2)
 
-    @unittest.skipUnless(Version(scipy_version) >= Version("1.4"),
-                         "scipy >= 1.4 is required.")
+    @unittest.skipUnless(ScipyVersion >= Version("1.4") and ScipyVersion < Version("1.12"),
+                         "scipy >= 1.4, < 1.12 is required.")
     def test_differential_evolution_constrained_nonlinear(self):
         # Source of example:
         # https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.differential_evolution.html
@@ -1969,7 +1972,7 @@ def test_differential_evolution_constrained_nonlinear(self):
         assert_near_equal(prob['x'], [0.96632622, 0.93367155], 1e-2)
         assert_near_equal(prob['f'], 0.0011352416852625719, 1e-2)
 
-    @unittest.skipUnless(Version(scipy_version) >= Version("1.4"),
+    @unittest.skipUnless(ScipyVersion >= Version("1.4"),
                          "scipy >= 1.4 is required.")
     def test_differential_evolution_constrained_linear_nonlinear(self):
         # test of the differential evolution optimizer with both
@@ -2004,7 +2007,7 @@ def test_differential_evolution_constrained_linear_nonlinear(self):
         assert_near_equal(prob['x'], [0.94999253, 0.90250721], 1e-2)
         assert_near_equal(prob['f'], 0.00250079, 1e-2)
 
-    @unittest.skipUnless(Version(scipy_version) >= Version("1.2"),
+    @unittest.skipUnless(ScipyVersion >= Version("1.2"),
                          "scipy >= 1.2 is required.")
     def test_shgo_rosenbrock(self):
         # Source of example:
@@ -2229,7 +2232,7 @@ def test_singular_jac_error_desvars_multidim_indices_con(self):
         self.assertEqual(str(msg.exception),
                          "Constraints or objectives [('parab.f_z', inds=[(1, 1, 0)])] cannot be impacted by the design variables of the problem.")
 
-    @unittest.skipUnless(Version(scipy_version) >= Version("1.2"),
+    @unittest.skipUnless(ScipyVersion >= Version("1.2"),
                          "scipy >= 1.2 is required.")
     def test_feature_shgo_rastrigin(self):
         # Source of example: https://stefan-endres.github.io/shgo/

pyproject.toml

@@ -33,7 +33,7 @@ classifiers = [
 ]
 dependencies = [
     "networkx>=2.0",
-    "numpy",
+    "numpy<2",
     "packaging",
     "requests",
     "scipy",