fix tests

Author: bknueven

pyomo/contrib/pynumero/algorithms/solvers/tests/test_cyipopt_interfaces.py

@@ -156,9 +156,9 @@ def test_model1_CyIpoptNLP_scaling(self):
 
         cynlp = CyIpoptNLP(PyomoNLP(m))
         obj_scaling, x_scaling, g_scaling = cynlp.scaling_factors()
-        self.assertTrue(obj_scaling is None)
-        self.assertTrue(x_scaling is None)
-        self.assertTrue(g_scaling is None)
+        self.assertTrue(obj_scaling == 1.0)
+        self.assertTrue((x_scaling == 1.0).all())
+        self.assertTrue((g_scaling == 1.0).all())
 
     def _check_model1(self, nlp, cynlp):
         # test x_init

pyomo/contrib/pynumero/interfaces/tests/test_external_grey_box_model.py

@@ -1827,7 +1827,7 @@ def create_model_two_equalities_two_outputs(self, external_model):
         m.egb.outputs['Pout'].setub(70)
         return m
 
-    def test_scaling_all_missing(self):
+    def test_scaling_all_one(self):
         m = self.create_model_two_equalities_two_outputs(
             ex_models.PressureDropTwoEqualitiesTwoOutputs()
         )
@@ -1836,9 +1836,9 @@ def test_scaling_all_missing(self):
         fs = pyomo_nlp.get_obj_scaling()
         xs = pyomo_nlp.get_primals_scaling()
         cs = pyomo_nlp.get_constraints_scaling()
-        self.assertIsNone(fs)
-        self.assertIsNone(xs)
-        self.assertIsNone(cs)
+        self.assertEqual(fs, 1.0)
+        self.assertTrue((xs == 1.0).all())
+        self.assertTrue((cs == 1.0).all())
 
     def test_scaling_pyomo_model_only(self):
         m = self.create_model_two_equalities_two_outputs(

pyomo/contrib/pynumero/interfaces/tests/test_pyomo_grey_box_nlp.py

@@ -2248,7 +2248,7 @@ def create_model_two_equalities_two_outputs(self, external_model):
         m.egb.outputs['Pout'].setub(70)
         return m
 
-    def test_scaling_all_missing(self):
+    def test_scaling_all_one(self):
         m = self.create_model_two_equalities_two_outputs(
             ex_models.PressureDropTwoEqualitiesTwoOutputs()
         )
@@ -2257,9 +2257,9 @@ def test_scaling_all_missing(self):
         fs = pyomo_nlp.get_obj_scaling()
         xs = pyomo_nlp.get_primals_scaling()
         cs = pyomo_nlp.get_constraints_scaling()
-        self.assertIsNone(fs)
-        self.assertIsNone(xs)
-        self.assertIsNone(cs)
+        self.assertEqual(fs, 1.0)
+        self.assertTrue((xs == 1.0).all())
+        self.assertTrue((cs == 1.0).all())
 
     def test_scaling_pyomo_model_only(self):
         m = self.create_model_two_equalities_two_outputs(