V0.5.7 : refactoring params genetic_operator

moead_framework/core/genetic_operator/abstract_operator.py

@@ -3,9 +3,8 @@
 
 class GeneticOperator(ABC):
 
-    def __init__(self, solutions, crossover_points=1):
+    def __init__(self, solutions, **kwargs):
         self.solutions = solutions
-        self.crossover_points = crossover_points
 
     @abstractmethod
     def run(self):

moead_framework/core/genetic_operator/combinatorial/cross_mut.py

@@ -4,11 +4,22 @@
 
 
 class CrossoverAndMutation(GeneticOperator):
+    def __init__(self, solutions, **kwargs):
+        super().__init__(solutions, **kwargs)
+        if kwargs.get("crossover_points") is None:
+            self.crossover_points = 1
+        else:
+            self.crossover_points = int(kwargs.get("crossover_points"))
+
+        if kwargs.get("mutation_probability") is None:
+            self.mutation_probability = 1
+        else:
+            self.mutation_probability = int(kwargs.get("mutation_probability"))
 
     def run(self):
         self.number_of_solution_is_correct(n=2)
 
         child = Crossover(solutions=self.solutions, crossover_points=self.crossover_points).run()
-        child = BinaryMutation(solutions=[child]).run()
+        child = BinaryMutation(solutions=[child], mutation_probability=self.mutation_probability).run()
 
         return child

moead_framework/core/genetic_operator/combinatorial/crossover.py

@@ -5,6 +5,13 @@
 
 class Crossover(GeneticOperator):
 
+    def __init__(self, solutions, **kwargs):
+        super().__init__(solutions, **kwargs)
+        if kwargs.get("crossover_points") is None:
+            self.crossover_points = 1
+        else:
+            self.crossover_points = int(kwargs.get("crossover_points"))
+
     def run(self):
         self.number_of_solution_is_correct(n=2)
         solution1 = self.solutions[0]

moead_framework/core/genetic_operator/combinatorial/mutation.py

@@ -4,6 +4,13 @@
 
 class BinaryMutation(GeneticOperator):
 
+    def __init__(self, solutions, **kwargs):
+        super().__init__(solutions, **kwargs)
+        if kwargs.get("mutation_probability") is None:
+            self.mutation_probability = 1
+        else:
+            self.mutation_probability = int(kwargs.get("mutation_probability"))
+
     def run(self):
 
         self.number_of_solution_is_correct(n=1)
@@ -14,7 +21,7 @@ def run(self):
         for i in range(len(solution)):
             probability = random.randint(0, n)
 
-            if probability < (1 / n):
+            if probability < (self.mutation_probability / n):
                 solution[i] = abs(solution[i]-1)
 
         return solution

moead_framework/problem/combinatorial/knapsack.py

@@ -23,7 +23,7 @@ def __init__(self, objective_number, instance_file):
             indexes_to_split.append(index_to_split_one * (i+1) + 1)
 
         kps = np.split(np.array(file_content), indexes_to_split)
-        print(len(kps))
+
         for kp in kps:
             # print(kp)
             if kp[0] == "=":

setup.py

@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name="moead-framework",
-    version="0.5.6",
+    version="0.5.7",
     author="Geoffrey Pruvost",
     author_email="geoffrey@pruvost.xyz",
     description="MOEA/D Framework in Python 3",