Commented EasyGA.py

src/EasyGA.py

@@ -1,4 +1,5 @@
 import random
+
 # Import all the data prebuilt modules
 from initialization.population_structure.population import population as create_population
 from initialization.chromosome_structure.chromosome import chromosome as create_chromosome
@@ -7,9 +8,10 @@ from initialization.gene_structure.gene import gene as create_gene
 # Import functionality defaults
 from initialization.random_initialization import random_initialization
 
-
 class GA:
     def __init__(self):
+        """Initialize the GA."""
+        
         # Default variables
         self.chromosome_impl = None
         self.gene_impl = None
@@ -19,6 +21,7 @@ class GA:
         self.chromosome_length = 3
         self.population_size = 5
         self.mutation_rate = 0.03
+        
         # Defualt EastGA implimentation structure
         self.initialization_impl = random_initialization
         self.update_fitness = True
@@ -28,7 +31,8 @@ class GA:
         #self.termination_impl = GenerationTermination(Total_generations)
         #self.evaluation_impl = TestEvaluation()
 
-    def initialize(self):
+    def initialize_population(self):
+        """Initialize the population"""
         self.population = self.initialization_impl(
         self.population_size,
         self.chromosome_length,
@@ -43,7 +47,11 @@ class GA:
         """Updates the ga to the next generation.
         If update_fitness is set then all fitness values are updated.
         Otherwise only fitness values set to None (i.e. uninitialized fitness values) are updated."""
+        
+        # for each chromosome in the population
         for chromosome in self.population.get_all_chromosomes():
+            
+            # if the fitness should be updated, update it
             if self.update_fitness or chromosome.get_fitness() is None:
                 chromosome.set_fitness(self.fitness_impl(chromosome))
     
@@ -52,15 +60,18 @@ class GA:
         return self.current_generation < self.generations
 
     def evolve_generation(self, number_of_generations):
-        # If you want to evolve through a number of generations
+        """Evolves the ga the specified number of generations."""
-        # and be able to pause and output data based on that generation run.
+        for n in range(number_of_generations):
-        pass
+            self.evolve()
 
     def make_gene(self,value):
+        """Let's the user create a gene."""
         return create_gene(value)
 
     def make_chromosome(self):
+        """Let's the user create a chromosome."""
         return create_chromosome()
 
     def make_population(self):
+        """Let's the user create a population."""
         return create_population()

src/run_testing.py

@@ -15,6 +15,6 @@ def user_gene_domain(gene_index):
 # If the user wants to use a domain
 ga.chromosome_impl = user_gene_domain
 
-ga.initialize()
+ga.initialize_population()
 
 ga.population.print_all()