run Black

idaes/core/util/model_diagnostics.py

@@ -634,8 +634,8 @@ def display_variables_with_none_value(self, stream=None):
 
     def display_variables_with_none_value_in_activated_constraints(self, stream=None):
         """
-        Prints a list of variables with values of None that are present in the 
-        mathematical program generated to solve the model. This list includes only 
+        Prints a list of variables with values of None that are present in the
+        mathematical program generated to solve the model. This list includes only
         variables in active constraints that are reachable through active blocks.
 
         Args:
@@ -652,7 +652,9 @@ def display_variables_with_none_value_in_activated_constraints(self, stream=None
             stream=stream,
             lines_list=[
                 f"{v.name}"
-                for v in variables_with_none_value_in_activated_equalities_set(self._model)
+                for v in variables_with_none_value_in_activated_equalities_set(
+                    self._model
+                )
             ],
             title=f"The following variable(s) have a value of None:",
             header="=",
@@ -661,12 +663,14 @@ def display_variables_with_none_value_in_activated_constraints(self, stream=None
 
     def _verify_active_variables_initialized(self, stream=None):
         """
-        Validate that all variables are initialized (i.e., have values set to 
-        something other than None) before doing further numerical analysis. 
-        Stream argument provided for forward compatibility (in case we want 
+        Validate that all variables are initialized (i.e., have values set to
+        something other than None) before doing further numerical analysis.
+        Stream argument provided for forward compatibility (in case we want
         to print a list or something).
         """
-        n_uninit = len(variables_with_none_value_in_activated_equalities_set(self._model))
+        n_uninit = len(
+            variables_with_none_value_in_activated_equalities_set(self._model)
+        )
         if n_uninit > 0:
             raise RuntimeError(
                 f"Found {n_uninit} variables with a value of None in the mathematical "
@@ -973,8 +977,6 @@ def display_overconstrained_set(self, stream=None):
 
         stream.write("=" * MAX_STR_LENGTH + "\n")
 
-
-
     def display_variables_with_extreme_jacobians(self, stream=None):
         """
         Prints the variables associated with columns in the Jacobian with extreme
@@ -1385,7 +1387,7 @@ def display_constraints_with_no_free_variables(self, stream=None):
 
         """
         # Although, in principle, this method doesn't require
-        # all variables to be initialized, its current 
+        # all variables to be initialized, its current
         # implementation does.
         self._verify_active_variables_initialized(stream=stream)
 

idaes/core/util/model_statistics.py

@@ -1729,16 +1729,17 @@ def number_active_variables_in_deactivated_blocks(block):
     """
     return len(active_variables_in_deactivated_blocks_set(block))
 
+
 def variables_with_none_value_in_activated_equalities_set(block):
     """
-    Method to return a ComponentSet of all Var components which 
+    Method to return a ComponentSet of all Var components which
     have a value of None in the set of activated constraints.
 
     Args:
         block : model to be studied
 
     Returns:
-        A ComponentSet including all Var components which 
+        A ComponentSet including all Var components which
         have a value of None in the set of activated constraints.
     """
     var_set = ComponentSet()
@@ -1747,21 +1748,23 @@ def variables_with_none_value_in_activated_equalities_set(block):
             var_set.add(v)
     return var_set
 
+
 def number_variables_with_none_value_in_activated_equalities(block):
     """
-    Method to return the number of Var components which 
+    Method to return the number of Var components which
     have a value of None in the set of activated constraints.
 
     Args:
         block : model to be studied
 
     Returns:
-        Number of Var components which 
+        Number of Var components which
         have a value of None in the set of activated constraints.
     """
 
     return len(variables_with_none_value_in_activated_equalities_set(block))
 
+
 # -------------------------------------------------------------------------
 # Reporting methods
 def report_statistics(block, ostream=None):

idaes/core/util/tests/test_model_diagnostics.py

@@ -184,9 +184,10 @@ def test_vars_near_zero(model):
     for i in near_zero_vars:
         assert i is model.v1
 
+
 class TestVariablesWithNoneValue:
     def err_msg(self, j):
-        return  (
+        return (
             f"Found {j} variables with a value of None in the mathematical "
             "program generated by the model. They must be initialized with non-None "
             "values before numerical analysis can proceed. Run "
@@ -203,23 +204,26 @@ def model(self):
         m.y = Var(range(3), initialize=[1, None, 2])
         m.z = Var()
 
-        m.con_w = Constraint(expr= m.w == 0)
-        m.con_x = Constraint(expr= m.x == 1)
+        m.con_w = Constraint(expr=m.w == 0)
+        m.con_x = Constraint(expr=m.x == 1)
+
         def rule_con_y(b, i):
             return b.y[i] == 3
+
         m.con_y = Constraint(range(3), rule=rule_con_y)
-        m.con_z = Constraint(expr= m.x + m.z == -1)
+        m.con_z = Constraint(expr=m.x + m.z == -1)
 
         m.block1 = Block()
         m.block1.a = Var()
         m.block1.b = Var(initialize=7)
         m.block1.c = Var(initialize=-5)
         m.block1.d = Var()
 
-        m.block1.con_a = Constraint(expr= m.block1.a**2 + m.block1.b == 1)
-        m.block1.con_b = Constraint(expr= m.block1.b + m.block1.c == 3)
-        m.block1.con_c = Constraint(expr= m.block1.c + m.block1.a == -4)
+        m.block1.con_a = Constraint(expr=m.block1.a**2 + m.block1.b == 1)
+        m.block1.con_b = Constraint(expr=m.block1.b + m.block1.c == 3)
+        m.block1.con_c = Constraint(expr=m.block1.c + m.block1.a == -4)
         return m
+
     @pytest.mark.unit
     def test_verify_active_variables_initialized(self, model):
         diag_tbx = DiagnosticsToolbox(model)
@@ -228,7 +232,7 @@ def test_verify_active_variables_initialized(self, model):
             match=self.err_msg(3),
         ):
             diag_tbx._verify_active_variables_initialized()
-        
+
         model.block1.deactivate()
         with pytest.raises(
             RuntimeError,
@@ -267,26 +271,23 @@ def test_error_handling(self, model):
     @pytest.mark.unit
     def test_display_problematic_constraint_terms(self, model):
         """
-        This method needs to be split in a separate function 
+        This method needs to be split in a separate function
         because it takes a constraint as an argument.
         """
         diag_tbx = DiagnosticsToolbox(model)
         with pytest.raises(
             RuntimeError,
             match=self.err_msg(3),
         ):
-            diag_tbx.display_problematic_constraint_terms(
-                model.con_y[1]
-            )
+            diag_tbx.display_problematic_constraint_terms(model.con_y[1])
         # Right now the error message should show whether or not
         # a problematic constraint is called.
         with pytest.raises(
             RuntimeError,
             match=self.err_msg(3),
         ):
-            diag_tbx.display_problematic_constraint_terms(
-                model.con_y[0]
-            )
+            diag_tbx.display_problematic_constraint_terms(model.con_y[0])
+
     @pytest.mark.unit
     def test_display_variables_with_none_value_in_activated_constraints(self, model):
         diag_tbx = DiagnosticsToolbox(model)
@@ -307,6 +308,7 @@ def test_display_variables_with_none_value_in_activated_constraints(self, model)
 """
         assert stream.getvalue() == expected
 
+
 @pytest.mark.unit
 def test_vars_with_none_value(model):
     none_value = _vars_with_none_value(model)

idaes/core/util/tests/test_model_statistics.py

@@ -629,6 +629,7 @@ def test_number_derivative_variables():
 
     assert number_derivative_variables(m) == 0
 
+
 @pytest.mark.unit
 def test_uninitialized_variables_in_activated_constraints():
     m = ConcreteModel()
@@ -638,42 +639,51 @@ def test_uninitialized_variables_in_activated_constraints():
     m.y = Var(range(3), initialize=[1, None, 2])
     m.z = Var()
 
-    m.con_w = Constraint(expr= m.w == 0)
-    m.con_x = Constraint(expr= m.x == 1)
+    m.con_w = Constraint(expr=m.w == 0)
+    m.con_x = Constraint(expr=m.x == 1)
+
     def rule_con_y(b, i):
         return b.y[i] == 3
+
     m.con_y = Constraint(range(3), rule=rule_con_y)
-    m.con_z = Constraint(expr= m.x + m.z == -1)
+    m.con_z = Constraint(expr=m.x + m.z == -1)
 
     m.block1 = Block()
     m.block1.a = Var()
     m.block1.b = Var(initialize=7)
     m.block1.c = Var(initialize=-5)
     m.block1.d = Var()
 
-    m.block1.con_a = Constraint(expr= m.block1.a**2 + m.block1.b == 1)
-    m.block1.con_b = Constraint(expr= m.block1.b + m.block1.c == 3)
-    m.block1.con_c = Constraint(expr= m.block1.c + m.block1.a == -4)
+    m.block1.con_a = Constraint(expr=m.block1.a**2 + m.block1.b == 1)
+    m.block1.con_b = Constraint(expr=m.block1.b + m.block1.c == 3)
+    m.block1.con_c = Constraint(expr=m.block1.c + m.block1.a == -4)
 
     active_uninit_set = ComponentSet([m.y[1], m.z, m.block1.a])
 
     assert variables_with_none_value_in_activated_equalities_set(m) == active_uninit_set
-    assert number_variables_with_none_value_in_activated_equalities(m) == len(active_uninit_set)
+    assert number_variables_with_none_value_in_activated_equalities(m) == len(
+        active_uninit_set
+    )
 
     m.block1.deactivate()
 
     active_uninit_set = ComponentSet([m.y[1], m.z])
 
     assert variables_with_none_value_in_activated_equalities_set(m) == active_uninit_set
-    assert number_variables_with_none_value_in_activated_equalities(m) == len(active_uninit_set)
+    assert number_variables_with_none_value_in_activated_equalities(m) == len(
+        active_uninit_set
+    )
 
     m.block1.activate()
     m.con_z.deactivate()
 
     active_uninit_set = ComponentSet([m.y[1], m.block1.a])
 
     assert variables_with_none_value_in_activated_equalities_set(m) == active_uninit_set
-    assert number_variables_with_none_value_in_activated_equalities(m) == len(active_uninit_set)
+    assert number_variables_with_none_value_in_activated_equalities(m) == len(
+        active_uninit_set
+    )
+
 
 # -------------------------------------------------------------------------
 # Objective methods