Fix empty hist

pyoptsparse/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "2.11.0"
+__version__ = "2.11.1"
 
 from .pyOpt_history import History
 from .pyOpt_variable import Variable
@@ -19,3 +19,25 @@
 from .pyNSGA2.pyNSGA2 import NSGA2
 from .pyALPSO.pyALPSO import ALPSO
 from .pyParOpt.ParOpt import ParOpt
+
+__all__ = [
+    "History",
+    "Variable",
+    "Gradient",
+    "Constraint",
+    "Objective",
+    "Optimization",
+    "Optimizer",
+    "OPT",
+    "Optimizers",
+    "Solution",
+    "SNOPT",
+    "IPOPT",
+    "SLSQP",
+    "CONMIN",
+    "PSQP",
+    "NLPQLP",
+    "NSGA2",
+    "ALPSO",
+    "ParOpt",
+]

pyoptsparse/pyOpt_history.py

@@ -651,7 +651,10 @@ def getValues(self, names=None, callCounters=None, major=True, scale=False, stac
         # reshape lists into numpy arrays
         for name in names:
             # we just stack along axis 0
-            data[name] = np.stack(data[name], axis=0)
+            if len(data[name]) > 0:
+                data[name] = np.stack(data[name], axis=0)
+            else:
+                data[name] = np.array(data[name])
             # we cast 1D arrays to 2D, for scalar values
             if data[name].ndim == 1:
                 data[name] = np.expand_dims(data[name], 1)

tests/test_hs015.py

@@ -193,6 +193,22 @@ def test_snopt_snstop(self):
         # we should get 70/74
         self.assert_inform_equal(sol, optInform=74)
 
+    def test_snopt_failed_initial(self):
+        def failed_fun(x_dict):
+            funcs = {"obj": 0.0, "con": [np.nan, np.nan]}
+            fail = True
+            return funcs, fail
+
+        self.optName = "SNOPT"
+        self.setup_optProb()
+        # swap obj to report NaN
+        self.optProb.objFun = failed_fun
+        sol = self.optimize(optOptions={}, storeHistory=True)
+        self.assert_inform_equal(sol, optInform=61)
+        # make sure empty history does not error out
+        hist = History(self.histFileName, flag="r")
+        hist.getValues()
+
 
 if __name__ == "__main__":
     unittest.main()