From 985fac54a29a8b3f56affe0c7d183e3ce1127021 Mon Sep 17 00:00:00 2001
From: George Lacey <georgelaceyy@gmail.com>
Date: Sun, 1 Oct 2017 20:45:49 +0100
Subject: [PATCH] Revamp algorithm

- Implement variable elitism and crossover
- Don't crossover all members
---
 src/individual.py | 21 ++++++++++++-
 src/main.py       | 12 +++++---
 src/population.py | 75 +++++++++++++++++++++++++++++++----------------
 3 files changed, 77 insertions(+), 31 deletions(-)

diff --git a/src/individual.py b/src/individual.py
index 5e27443..571a210 100644
--- a/src/individual.py
+++ b/src/individual.py
@@ -1,14 +1,23 @@
-from math import pow, sin, pi, cos
+from math import pow, sin, pi
 from random import Random
+from enum import Enum
 
 rand = Random()
 
 
+class Flag(Enum):
+    UNSET = 1,
+    PARENT = 2,
+    ELITE = 3,
+    PERSIST = 4
+
+
 class Individual(object):
 
     def __init__(self):
         self.x = self.get_rand_param()
         self.y = self.get_rand_param()
+        self.flag = Flag(Flag.UNSET)
 
     @classmethod
     def from_params(cls, x, y):
@@ -42,3 +51,13 @@ class Individual(object):
     @staticmethod
     def get_rand_param():
         return rand.uniform(0, 1)
+
+    def set_flag(self, flag):
+        if self.flag is Flag.UNSET:
+            self.flag = flag
+            return True
+        else:
+            return False
+
+    def reset_flag(self):
+        self.flag = Flag.UNSET
diff --git a/src/main.py b/src/main.py
index 3ef1b6c..b19beb7 100644
--- a/src/main.py
+++ b/src/main.py
@@ -22,13 +22,17 @@ pop = Population(args.pop)
 for i in range(0, args.iter):
     cls()
     print("Epoch: %d " % i)
-    pop.advance_generation()
-    best = pop.best_fitness()
-    best_fit.append(pop.avg_fitness())
+    elite = round(args.pop * .1)
+    crossover = round(args.pop * .8)
+    pop.advance_generation(elite, crossover)
+    best_fit.append(pop.best_fitness().fitness())
     #input("...")
     sleep(args.wait)
 
+print("Best: ")
+print(pop.best_fitness())
+
 plt.plot(best_fit)
 plt.xlabel("Epoch")
 plt.ylabel("Fitness")
-plt.savefig("fig.png")
+plt.show()
diff --git a/src/population.py b/src/population.py
index 19a9ebf..2325f31 100644
--- a/src/population.py
+++ b/src/population.py
@@ -1,4 +1,4 @@
-from individual import Individual
+from individual import Individual, Flag
 from random import Random
 
 rand = Random()
@@ -24,14 +24,15 @@ class Population(object):
                          (best.x, best.y, best.fitness())
         return return_string
 
-    def fitness_function(self):
-        for member in self.members:
-            member.fitness()
-
-    def total_fitness(self):
+    def total_fitness(self, members=None):
         total = 0
-        for member in self.members:
+
+        if members is None:
+            members = self.members
+
+        for member in members:
             total += member.fitness()
+
         return total
 
     def avg_fitness(self):
@@ -45,33 +46,55 @@ class Population(object):
                 best_member = member
         return best_member
 
-    def roulette(self, divisor=1):
-        total = self.total_fitness() / divisor
+    def roulette(self, members=None):
+        total = self.total_fitness(members=members)
         position = rand.uniform(0, total)
 
-        for member in self.members:
-            position -= member.fitness() / divisor
+        if members is None:
+            members = self.members
+
+        for member in members:
+            position -= member.fitness()
             if position <= 0:
-                #print(member)
-                return member
+                return member.set_flag(Flag.PARENT)
 
     def mutate(self, chance):
         for member in self.members:
             if rand.random() < chance/100:
                 member.mutate()
 
-    def advance_generation(self):
-        # todo: elitism
-        # todo: don't crossover all
-        self.fitness_function()
-        parents = list()
-        for i in range(0, len(self.members)):
-            parents.append(self.roulette())
+    def elite(self, amount):
+        return sorted(self.members, key=lambda x: x.fitness(),
+                      reverse=True)[:amount]
+
+    def advance_generation(self, n_elite, n_crossover):
+
+        for member in self.members:
+            member.reset_flag()
+
+        # elitism
+        for member in self.elite(n_elite):
+            member.flag = Flag.ELITE
+
+        potential_parents = [member for member in self.members if member.flag
+                             is Flag.UNSET]
+        # parent
+        for ind in range(0, n_crossover):
+            while not self.roulette(members=potential_parents):
+                pass
+
+        # persist
+        [member.set_flag(Flag.PERSIST) for member in self.members
+         if member.flag is Flag.UNSET]
+
+        parents = [member for member in self.members if member.flag is
+                   Flag.PARENT]
+
+        for ind in range(0, len(parents), 2):
+            if ind is len(parents) - 1:
+                parents[ind].set_flag(Flag.PERSIST)
+            else:
+                parents[ind], parents[ind + 1] = parents[ind]\
+                    .crossover(parents[ind + 1])
 
-        children = list()
-        for i in range(0, len(parents) - 1, 2):
-            one, two = self.members[i].crossover(parents[i + 1])
-            children.append(one)
-            children.append(two)
-        self.members = children
         self.mutate(2)