Fix all test cases

examples/algorithms/moo/nsga2/nsga2_custom.py

@@ -6,7 +6,7 @@
 from pymoo.core.crossover import Crossover
 from pymoo.core.duplicate import ElementwiseDuplicateElimination
 from pymoo.core.mutation import Mutation
-from pymoo.core.problem import Problem, ElementwiseProblem
+from pymoo.core.problem import ElementwiseProblem
 from pymoo.core.sampling import Sampling
 from pymoo.optimize import minimize
 from pymoo.visualization.scatter import Scatter

pymoo/core/problem.py

@@ -253,8 +253,10 @@ def _evaluate_elementwise(self, X, out, *args, **kwargs):
 
                 out[k].append(v)
 
+        # convert to arrays (the none check is important because otherwise an empty array is initialized)
         for k in out:
-            out[k] = anp.array(out[k])
+            if out[k] is not None:
+                out[k] = anp.array(out[k])
 
     def _format_dict(self, out, N, return_values_of):
 
@@ -280,8 +282,7 @@ def _format_dict(self, out, N, return_values_of):
                         v = v.reshape(shape[name])
                     except Exception as e:
                         raise Exception(
-                            f"Problem Error: {name} can not be set, expected shape {shape[name]} but provided {v.shape}",
-                            e)
+                            f"Problem Error: {name} can not be set, expected shape {shape[name]} but provided {v.shape}", e)
 
                 ret[name] = v
 

pymoo/gradient/automatic.py

@@ -27,8 +27,11 @@ def __call__(self, x):
 
 class ElementwiseAutomaticDifferentiation(Meta, Problem):
 
-    def __init__(self, object, copy=True):
-        super().__init__(object, copy)
+    def __init__(self, problem, copy=True):
+        if not problem.elementwise:
+            raise Exception("Elementwise automatic differentiation can only be applied to elementwise problems.")
+
+        super().__init__(problem, copy)
         self.elementwise_func = ElementwiseEvaluationFunctionWithGradient
 
 
@@ -52,5 +55,3 @@ def do(self, x, return_values_of, *args, **kwargs):
             out["d" + k] = v
 
         return out
-
-

tests/algorithms/test_algorithms.py

@@ -74,8 +74,6 @@ class MyThreadedProblem(ElementwiseProblem):
         def __init__(self):
             super().__init__(n_var=2,
                              n_obj=1,
-                             n_ieq_constr=0,
-                             parallelization=("threads", 4),
                              xl=np.array([0, 0]),
                              xu=np.array([100, 100]))
 

tests/problems/test_autodiff.py

@@ -1,7 +1,7 @@
 import numpy as np
 import pytest
 
-from pymoo.gradient.automatic import AutomaticDifferentiation
+from pymoo.gradient.automatic import AutomaticDifferentiation, ElementwiseAutomaticDifferentiation
 from pymoo.gradient.grad_complex import ComplexNumberGradient
 from pymoo.operators.sampling.rnd import FloatRandomSampling
 from pymoo.problems import get_problem