Updated Implementation Framework

Updated to cover changes made by Dan to Master regarding general design changes

Also added remove_two_worst survivor selection method

src/mutation/mutation_methods.py

@@ -0,0 +1,42 @@
+import random
+
+class Mutation_Methods:
+    
+    def __init__(self):
+        pass
+
+    def random_mutation(self, ga, chromosome_set = None):
+        
+        if chromosome_set == None:
+            chromosome_set = ga.population.get_all_chromosomes()
+
+        chromosome_mutate_num = int(len(chromosome_set)*ga.mutation_rate)
+        temp_population = ga.initialization_impl(ga)
+
+        while chromosome_mutate_num > 0:
+            chromosome_set[random.randint(0,ga.population_size-1)] = temp_population.get_all_chromosomes()[chromosome_mutate_num]
+            chromosome_mutate_num -= 1
+        
+        return chromosome_set
+    
+    def per_gene_mutation(self, ga, chromosome_set = None, gene_mutate_count = 1):
+        
+        gene_mutate_count_static = int(gene_mutate_count)
+
+        if chromosome_set == None:
+            chromosome_set = ga.population.get_all_chromosomes()
+
+        for i in range(len(chromosome_set)):
+            random_num = random.uniform(0,1)
+
+            if (random_num <= ga.mutation_rate):
+                while gene_mutate_count > 0:
+                    dummy_population = ga.initialization_impl(ga) #Really inefficient, but works for now
+                    random_index = random.randint(0, ga.chromosome_length-1)
+                    chromosome_set[i].get_genes()[random_index] = dummy_population.get_all_chromosomes()[random.randint(0,ga.population_size-1)].get_genes()[random_index]
+                    gene_mutate_count -= 1
+            gene_mutate_count = int(gene_mutate_count_static)
+
+        return chromosome_set
+
+