From bba32ae7088c269c95fe34903e6e4390fca90c6b Mon Sep 17 00:00:00 2001
From: parimatrix <parikansh.ahluwalia@gmail.com>
Date: Thu, 17 Oct 2019 10:46:16 +0530
Subject: [PATCH] Minor Fixes

---
 geneticAlgo/crossover.py                 | 17 +++++++++--------
 geneticAlgo/genetic_algo_initial_popu.py |  4 +---
 geneticAlgo/mutate.py                    |  9 +++++----
 3 files changed, 15 insertions(+), 15 deletions(-)

diff --git a/geneticAlgo/crossover.py b/geneticAlgo/crossover.py
index 43c0b5c..b250232 100644
--- a/geneticAlgo/crossover.py
+++ b/geneticAlgo/crossover.py
@@ -1,4 +1,5 @@
 import random
+from copy import deepcopy
 
 def breed(chromosome1, chromosome2):
     """
@@ -9,11 +10,7 @@ def breed(chromosome1, chromosome2):
         k = random.random()
         # print (k)
         if(k>=0.5):
-            temp = chromosome1[i]
-            chromosome1[i] = chromosome2[i]
-            chromosome2[i] = temp
-    # print (chromosome1)
-    # print (chromosome2)
+            chromosome1[i], chromosome2[i] = chromosome2[i], chromosome1[i]
     
 
 def crossover( matingPool, origChromosomes, noOfElite):
@@ -32,19 +29,23 @@ def crossover( matingPool, origChromosomes, noOfElite):
     newChromosome = []
     # Copy the elite chromosomes and persist them to next generation
     for i in range(0, noOfElite):
-        newChromosome.append(origChromosomes[matingPool[i]])
+        newChromosome.append(deepcopy(origChromosomes[matingPool[i]]))
     LowerPtrForCrossover = noOfElite
     UpperPtrForCrossover = sizeOfMatingPool-1
     while (LowerPtrForCrossover<UpperPtrForCrossover):
         ind1 = matingPool[LowerPtrForCrossover]
         ind2 = matingPool[UpperPtrForCrossover]
-        tempChromo1 = origChromosomes[ind1]
-        tempChromo2 = origChromosomes[ind2]
+        tempChromo1 = deepcopy(origChromosomes[ind1])
+        tempChromo2 = deepcopy(origChromosomes[ind2])
         breed(tempChromo1,tempChromo2)
         newChromosome.append(tempChromo1)
         newChromosome.append(tempChromo2)
         LowerPtrForCrossover+=1
         UpperPtrForCrossover-=1
+    if(LowerPtrForCrossover==UpperPtrForCrossover):
+        ind1 = matingPool[LowerPtrForCrossover]
+        tempChromo1 = deepcopy(origChromosomes[ind1])
+        newChromosome.append(tempChromo1)
 
     return newChromosome
 
diff --git a/geneticAlgo/genetic_algo_initial_popu.py b/geneticAlgo/genetic_algo_initial_popu.py
index c38ddbc..f23a4f0 100644
--- a/geneticAlgo/genetic_algo_initial_popu.py
+++ b/geneticAlgo/genetic_algo_initial_popu.py
@@ -9,7 +9,5 @@ def createInitialPopu(maxDishes, initialPopuSize):
 
     initialPopuSize -> Size of initial population pool
     """
-    population = []
-    for i in range(1, initialPopuSize+1):
-        population.append(createChromosome(maxDishes))
+    population = [createChromosome(maxDishes) for i in range(initialPopuSize)]
     return population
diff --git a/geneticAlgo/mutate.py b/geneticAlgo/mutate.py
index 9f318d0..35ac9fc 100644
--- a/geneticAlgo/mutate.py
+++ b/geneticAlgo/mutate.py
@@ -1,4 +1,5 @@
 import random
+from copy import deepcopy
 # from genetic_algo_gene import Dish
 
 
@@ -32,7 +33,7 @@ def mutate(individual, mutationRate):
             individual[i].qty = tempArrQty[i-startPtr]
     return individual
 
-def mutatePopulation ( population, mutationRate):
+def mutatePopulation ( population, noOfElite, mutationRate):
     """
     This function performs mutation on entire population
 
@@ -43,9 +44,9 @@ def mutatePopulation ( population, mutationRate):
     """
     popuLen = len(population)
     newPopu = []
-    for i in range(0,popuLen):
-        mutantIndi = mutate(population[i],mutationRate)
-        newPopu.append(mutantIndi)
+    newPopu.extend([deepcopy(individual) for individual in population[:noOfElite]])
+    newPopu.extend([mutate(individual, mutationRate) for individual in population[noOfElite:popuLen]])
+
     return newPopu
 
 # mutate function test