Change domain feature

src/EasyGA.py

@@ -1,3 +1,4 @@
+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
@@ -12,14 +13,15 @@ from initialization.random_initialization import random_initialization
 class GA:
     def __init__(self):
         # Default variables
-        self.domain = range(1, 100)
+        self.domain = None
+        self.new_range = None
         self.population = None
         self.generations = 3
-        self.chromosome_length = 4
+        self.chromosome_length = 3
         self.population_size = 5
         self.mutation_rate = 0.03
         # Defualt EastGA implimentation structure
-        self.gene_function_impl = random_gene
+        
         # Set the GA Configuration
         self.initialization_impl = random_initialization
         #self.mutation_impl = PerGeneMutation(Mutation_rate)
@@ -29,14 +31,11 @@ class GA:
         #self.evaluation_impl = TestEvaluation()
 
     def initialize(self):
-        if isinstance(self.domain, range):
-            self.domain = [x/float(100) for x in range(int(min(self.domain)*100), int(max(self.domain)*100))]
-        # Create the first population
         self.population = self.initialization_impl(
         self.population_size,
         self.chromosome_length,
-        self.gene_function_impl,
+        self.domain,
-        self.domain)
+        self.new_range)
 
     def evolve():
         # If you just want to evolve through all generations

src/initialization/random_initialization.py

@@ -3,7 +3,7 @@ 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
 
-def random_initialization(chromosome_length, population_size, gene_function, domain):
+def random_initialization(population_size, chromosome_length, domain, new_range):
     # Create the population object
     population = create_population()
     # Fill the population with chromosomes
@@ -11,6 +11,16 @@ def random_initialization(chromosome_length, population_size, gene_function, dom
         chromosome = create_chromosome()
         #Fill the Chromosome with genes
         for j in range(chromosome_length):
-            chromosome.add_gene(create_gene(gene_function(domain)))
+            if domain != None:
+                # Each chromosome location is specified with its own function
+                chromosome.add_gene(create_gene(domain(j)))
+                # Will break if chromosome_length != lists in domain
+            elif new_range != None:
+                # new_rnage = [range function,lowerbound,upperbound]
+                function = new_range[0]
+                chromosome.add_gene(create_gene(function(new_range[1],new_range[2])))
+            else:
+                #Exit because either were not specified
+                print("Your domain or range were not specified")
         population.add_chromosome(chromosome)
     return population

src/run_testing.py

@@ -1,14 +1,22 @@
 import EasyGA
-
+import random
 # Create the Genetic algorithm
 ga = EasyGA.GA()
 
-# input domain
+def user_gene_domain(gene_index):
-#ga.domain = range(3, 10)
+    """Each gene index is assosiated to its index in the chromosome"""
-ga.domain = ['left', 'right']
+    domain = [
+    random.randrange(1,100),
+    random.uniform(10,5),
+    random.choice(["up","down"])
+    ]
+    return domain[gene_index]
+
+# If the user wants to use a domain
+ga.domain = user_gene_domain
+# If the user wants to use a custom range
+#ga.new_range = [random.randrange,1,100]
 
-# initialize random population
 ga.initialize()
 
-# Print population
 ga.population.print_all()