Major structural changes

src/EasyGA.py

@@ -1,15 +1,11 @@
-# Import all the data structure onjects
-from initialization.gene import gene
-from initialization.chromosome import chromosome
-from initialization.population import population
-
-
-from initialization.random_gene import random_gene
+# Import all the data prebuilt modules
+from initialization.gene_creation.gene_random import random_gene
 from initialization.random_initialization import random_initialization
 
+
+
 class GA:
     def __init__(self):
-
         # Default variables
         self.population = None
         self.generations = 3
@@ -17,7 +13,7 @@ class GA:
         self.population_size = 5
         self.mutation_rate = 0.03
         # Defualt EastGA implimentation structure
-        self.gene_function_impl = random_gene(1,100)
+        self.gene_function_impl = random_gene
         # Set the GA Configuration
         self.initialization_impl = random_initialization()
         #self.mutation_impl = PerGeneMutation(Mutation_rate)

src/initialization/gene_creation/gene_random.py

@@ -9,7 +9,5 @@ def check_values(low,high):
     assert high > low , "High value can not be smaller then low value"
     assert high != 0, "High value can not be zero"
 
-def random_gene(low,high):
-    # Check the values so that they follow the rules.
-    check_values(low,high)
+def random_gene():
     return random.randint(1,100)

src/initialization/initialization.py

@@ -1,3 +0,0 @@
-class initialization:
-    def initialize(self,chromosome_length,population_size,gene_function):
-        return []  # return an array of chromosomes for generation 0

src/initialization/population_structure/population.py

@@ -1,8 +1,8 @@
 class population:
     # population = [chromosome,chromosome,etc]
     def __init__(self):
-        self.chromosomes = []
         self.fitness = None
-
+        self.chromosomes = []
+        
     def add_chromosome(self,chromosome):
         self.chromosomes.append(chromosome)

src/initialization/random_initialization.py

@@ -1,20 +1,23 @@
-from initialization.population import population
-from initialization.chromosome import chromosome
-from initialization.gene import gene
+# Import the data structure
+from .population_structure.population import population as create_population
+from .chromosome_structure.chromosome import chromosome as create_chromosome
+from .gene_structure.gene import gene as create_gene
 
-from initialization.initialization import initialization
+from .initialization import initialization
 
-class random_initialization(initialization):
+class random_initialization:
     def initialize(self,chromosome_length,population_size,gene_function):
+        # I dont understand why python needs this in its scope but it does.
+        global population
+        global chromosome
+        global gene
         # Create the population object
-        population = population.population()
+        population = create_population()
         # Fill the population with chromosomes
         for i in range(population_size):
-            chromosome = chromosome.chromosome()
+            chromosome = create_chromosome()
             #Fill the Chromosome with genes
             for j in range(chromosome_length):
-                gene = gene.gene(gene_function)
-                chromosome.add_gene(gene)
-
+                chromosome.add_gene(create_gene(gene_function()))
             population.add_chromosome(chromosome)
         return population

src/run_testing.py

@@ -4,6 +4,8 @@ import EasyGA
 # Create the Genetic algorithm
 ga = EasyGA.GA()
 
+# Start the population
 ga.initialize()
 
-ga.population.chromosome[0].print_chromosome()
+for chromosome in ga.population.chromosomes:
+    print(chromosome.genes[0].__dict__)