Working on usage test fix

Author: Julian Blank

pymoo/algorithms/deriv/__init__.py pymoo/algorithms/convex/__init__.pypymoo/algorithms/deriv/__init__.py renamed to pymoo/algorithms/convex/__init__.py

@@ -1,6 +1,6 @@
 import numpy as np
 
-from pymoo.algorithms.so_gradient_descent import GradientBasedAlgorithm
+from pymoo.algorithms.convex.base import GradientBasedAlgorithm
 
 
 class Adam(GradientBasedAlgorithm):

pymoo/algorithms/deriv/adam.py pymoo/algorithms/convex/adam.pypymoo/algorithms/deriv/adam.py renamed to pymoo/algorithms/convex/adam.py

@@ -79,16 +79,3 @@ def _next(self):
 
         # set the gradient to none to be ready for the next iteration
         self.dX = None
-
-
-class GradientDescent(GradientBasedAlgorithm):
-
-    def __init__(self, X, learning_rate=0.005, **kwargs) -> None:
-        super().__init__(X, **kwargs)
-        self.learning_rate = learning_rate
-
-    def restart(self):
-        self.learning_rate /= 2
-
-    def apply(self):
-        self.X = self.X - self.learning_rate * self.dX

…moo/algorithms/deriv/gradient_descent.py pymoo/algorithms/convex/base.pypymoo/algorithms/deriv/gradient_descent.py renamed to pymoo/algorithms/convex/base.py pymoo/algorithms/deriv/gradient_descent.py renamed to pymoo/algorithms/convex/base.py

@@ -0,0 +1,14 @@
+from pymoo.algorithms.convex.base import GradientBasedAlgorithm
+
+
+class GradientDescent(GradientBasedAlgorithm):
+
+    def __init__(self, X, learning_rate=0.005, **kwargs) -> None:
+        super().__init__(X, **kwargs)
+        self.learning_rate = learning_rate
+
+    def restart(self):
+        self.learning_rate /= 2
+
+    def apply(self):
+        self.X = self.X - self.learning_rate * self.dX

pymoo/algorithms/convex/gradient_descent.py

@@ -6,7 +6,6 @@
 from pymoo.algorithms.genetic_algorithm import GeneticAlgorithm
 from pymoo.docs import parse_doc_string
 from pymoo.factory import get_decomposition
-from pymoo.model.individual import Individual
 from pymoo.model.population import Population
 from pymoo.operators.crossover.simulated_binary_crossover import SimulatedBinaryCrossover
 from pymoo.operators.mutation.polynomial_mutation import PolynomialMutation

pymoo/algorithms/ctaea.py

@@ -88,6 +88,8 @@ def setup(self, problem, **kwargs):
         if not isinstance(self.termination, MaximumGenerationTermination):
             raise Exception("Please use the n_gen or n_eval as a termination criterion to execute RVEA!")
 
+        return self
+
     def _next(self):
         super()._next()