New year infrastructure / CI fixes

pyomo/contrib/doe/doe.py

@@ -1458,7 +1458,7 @@ def compute_FIM_full_factorial(
             }
         )
 
-        succeses = 0
+        successes = 0
         failures = 0
         total_points = np.prod(
             np.array([len(v) for k, v in design_ranges_enum.items()])
@@ -1477,14 +1477,14 @@ def compute_FIM_full_factorial(
 
             # Compute FIM with given options
             try:
-                curr_point = succeses + failures + 1
+                curr_point = successes + failures + 1
 
                 # Logging information for each run
                 self.logger.info("This is run %s out of %s.", curr_point, total_points)
 
                 # Attempt the FIM computation
                 self.compute_FIM(model=model, method=method)
-                succeses += 1
+                successes += 1
 
                 # iteration time
                 iter_t = iter_timer.toc(msg=None)

pyomo/core/base/indexed_component.py

@@ -344,7 +344,7 @@ def _create_objects_for_deepcopy(self, memo, component_list):
             # For indexed components, we will pre-emptively clone all
             # component data objects as well (as those are the objects
             # that will be referenced by things like expressions).  It
-            # is important to only clone "normal" ComponentData obects:
+            # is important to only clone "normal" ComponentData objects:
             # so we will want to skip this for all scalar components
             # (where the _data points back to self) and references
             # (where the data may be stored outside this block tree and

pyomo/core/expr/taylor_series.py

@@ -43,7 +43,7 @@ def taylor_series_expansion(
         The method for differentiation.
     order: The order of the taylor series expansion
         If order is not 1, then symbolic differentiation must
-        be used (differentiation.Modes.reverse_sybolic or
+        be used (differentiation.Modes.reverse_symbolic or
         differentiation.Modes.sympy).
 
     Returns

pyomo/solvers/plugins/solvers/cplex_direct.py

@@ -846,7 +846,9 @@ def _postsolve(self):
 
                 if extract_slacks:
                     linear_slacks = self._solver_model.solution.get_linear_slacks()
-                    qudratic_slacks = self._solver_model.solution.get_quadratic_slacks()
+                    quadratic_slacks = (
+                        self._solver_model.solution.get_quadratic_slacks()
+                    )
                     for i, con_name in enumerate(
                         self._solver_model.linear_constraints.get_names()
                     ):
@@ -869,7 +871,7 @@ def _postsolve(self):
                     for i, con_name in enumerate(
                         self._solver_model.quadratic_constraints.get_names()
                     ):
-                        soln_constraints[con_name]["Slack"] = qudratic_slacks[i]
+                        soln_constraints[con_name]["Slack"] = quadratic_slacks[i]
         elif self._load_solutions:
             if cpxprob.solution.get_solution_type() > 0:
                 self.load_vars()