IPOPT duplicated history handling

pyoptsparse/postprocessing/OptView_baseclass.py

@@ -162,8 +162,8 @@ def OptimizationHistory(self):
                 # Raise warning for IPOPT's duplicated history
                 if db["metadata"]["optimizer"] == "IPOPT" and "iter" not in db["0"].keys():
                     pyOptSparseWarning(
-                        "The optimization history of IPOPT has duplicated entries at every iteration, and the OptView plot is not correct. \
-                        Install the latest version of pyOptSparse for a fix."
+                        "The optimization history file has duplicated entries at every iteration, and the OptView plot is not correct. \
+                        Re-run the optimization with a current version of pyOptSparse to generate a correct history file."
                     )
 
                 # Save information from the history file for the funcs.

pyoptsparse/pyOpt_history.py

@@ -675,7 +675,10 @@ def getValues(self, names=None, callCounters=None, major=True, scale=False, stac
 
         # Raise warning for IPOPT's duplicated history
         if self.db["metadata"]["optimizer"] == "IPOPT" and "iter" not in self.db["0"].keys():
-            pyOptSparseWarning("The optimization history of IPOPT has duplicated entries at every iteration.")
+            pyOptSparseWarning(
+                "The optimization history of IPOPT has duplicated entries at every iteration. \
+                Fix the history manually, or re-run the optimization with a current version of pyOptSparse to generate a correct history file."
+            )
         return data
 
     def _checkIPOPTDuplicateHistory(self, val):

pyoptsparse/pyOpt_optimizer.py

@@ -61,6 +61,7 @@ def __init__(
             checkDefaultOptions=checkDefaultOptions,
             caseSensitiveOptions=caseSensitiveOptions,
         )
+        # callCounter will be incremented after the function calls, iterCounters will be incremented before the calls.
         self.callCounter = 0  # counts all function calls (fobj, fcon, gobj, gcon)
         self.iterCounter = -1  # counts iteration(new x point)
         self.sens: Union[None, Callable, Gradient] = None