Reverted back to old style of attributes.

src/run_testing.py

@@ -2,34 +2,11 @@ import random
 import EasyGA
 
 # Create the Genetic algorithm
-#   Reproduce 30% of the population.
-#   Mutate 20% of the population.
-#   Mutate 3% of the genes in each mutated chromosome.
-#   
-#   Create 100 chromosomes each with 25 genes
-#   Create random genes from 0 to 10
-#   
-#   Minimize the sum of the genes
-#   Terminate when a chromosome has all 0's
-#     or 150 generations pass
-# 
-ga = EasyGA.GA(
-    parent_ratio = 0.30,
-    chromosome_mutation_rate = 0.20,
-    gene_mutation_rate = 0.03,
-    population_size = 100,
-    chromosome_length = 25,
-    gene_impl = lambda: random.randint(0, 10),
-    fitness_function_impl = lambda chromosome: sum(gene.get_value() for gene in chromosome.get_gene_list()),
-    target_fitness_type = 'min',
-    fitness_goal = 0,
-    generation_goal = 150
-)
+ga = EasyGA.GA()
 
-# Run 10 generations at a time
-while ga.active():
-    ga.evolve_generation(10)
-    ga.print_generation()
-    ga.print_best()
-    #ga.print_population()
-    print('-'*75)
+# Evolve the genetic algorithm
+ga.evolve()
+
+# Print your default genetic algorithm
+ga.print_generation()
+ga.print_population()