From 7a6571ccd4c37da6e0402c79131f5c20511a6ccc Mon Sep 17 00:00:00 2001
From: AKM Elias <akmelias11@gmail.com>
Date: Tue, 5 Dec 2017 23:46:49 +0600
Subject: [PATCH] Update genticAlgorithForReproduction.py

code updated
---
 genticAlgorithForReproduction.py | 143 +++++++++++--------------------
 1 file changed, 51 insertions(+), 92 deletions(-)

diff --git a/genticAlgorithForReproduction.py b/genticAlgorithForReproduction.py
index b26f1f7..12afeb1 100644
--- a/genticAlgorithForReproduction.py
+++ b/genticAlgorithForReproduction.py
@@ -6,7 +6,7 @@
 
 import math
 #population...
-populations  = [[1,0,0,1,0],[1,1,1,1,1],[0,0,0,0,0],[1,1,1,1,0],[0,0,1,0,1]]
+populations  = [[1,0,0,1,0],[1,1,1,1,1],[0,0,0,0,0],[1,1,1,1,0],[1,0,1,1,1]]
 #expected outecome or target generation
 expected_output = [1,1,0,1,0]
 #maximum bit not changed..
@@ -25,26 +25,39 @@
 #main algo start...
 #we will need these list later..
 listToCross = []
-listToCross2 = []
+listToCross2 = populations
 #homany time the expected generation found..
 maincount = 0
 #threshold_value assigninig or assuming..let assume 2 for this problem
 thv = 2
 flag=0
+
 #fitness function..we will do this by comparing eith expected outecome to all the population given
 value = []
-j = 0
-for i in range(len(populations)):
-    cnt = 0
-    for bit in range(len(populations[i])):
-        #print(populations[i][bit])
-        if populations[i][bit]!=expected_output[bit]:
-            cnt+=1
-    value.append(cnt)
+def bestFit(population):  
+    global value
+    value = []
+    #print("bestfit")
+    j = 0
+    for i in range(len(population)):
+        cnt = 0
+        for bit in range(len(population[i])):
+            #print(populations[i][bit])
+            if population[i][bit]!=expected_output[bit]:
+                cnt+=1
+        value.append(cnt)
     #j+=1
-
-#function for crossover..
-def crossover(i):
+    
+#list assigning after best fit function..
+def assigningBestPopulations(population):
+    global value
+    for i in range(len(population)):
+        if value[i]<=2:
+            #print(value[i]) 
+            listToCross.append(population[i])
+        
+        
+def crossover():
     #print(i)
     global listToCross2
     global mxbit
@@ -52,76 +65,31 @@ def crossover(i):
     check = 0
     flag=0
     maincount = 0
-    if i==0:
+   
         #crossover for every combination..
-        for j in range(len(listToCross)-1):
-            cmp1 = j
-            for k in range(len(listToCross)-j-1):
-                cmp1+=1
-                temp1 = []
-                temp2 = []
-                for vl in range(len(listToCross[cmp1])):
-                    #bit can remain same upto maxbit ..
-                    if vl<mxbit:
-                        temp1.append(listToCross[j][vl])
-                        temp2.append(listToCross[cmp1][vl])
-                    #else flip the bit ...    
-                    else:
-                        temp1.append(listToCross[cmp1][vl])
-                        temp2.append(listToCross[j][vl])
-                        
-                check = 0
-                for vl in range(len(expected_output)):
-                    #print(temp1[vl])
-                    if temp1[vl]!=expected_output[vl]:
-                        #print(1)
-                        check=1
-                        
-                if check==0:
-                    maincount+=1
-                    flag=1
-                    #print(1)
-                check=0
-              
-                for vl in range(len(expected_output)):
-                    #print(temp1[vl])
-                    if temp2[vl]!=expected_output[vl]:
-                        check=1
-                        
-                if check==0:
-                    flag=1
-                    maincount+=1
-                    #print(1)
-                #new two population found after crossover...                           
-                listcr.append(temp1)
-                listcr.append(temp2)
-        #storing the new populations for future need like if i >0..these new populations will crossover among them..      
-        listToCross2 = listcr 
-    #equations are smae here but combinations are different..     
-    else:
-        cmp2 = 0
-        #print(len(listToCross2))
-        for j in range(0,len(listToCross2),2):
+    for j in range(len(listToCross)-1):
+        cmp1 = j
+        for k in range(len(listToCross)-j-1):
+            cmp1+=1
             temp1 = []
             temp2 = []
-            print(j)
-            for vl in range(len(listToCross2[j])):
-                   
+            for vl in range(len(listToCross[cmp1])):
+                    #bit can remain same upto maxbit ..
                 if vl<mxbit:
-                    temp1.append(listToCross2[j][vl])
-                    temp2.append(listToCross2[cmp2+1][vl])
+                    temp1.append(listToCross[j][vl])
+                    temp2.append(listToCross[cmp1][vl])
+                    #else flip the bit ...    
                 else:
-                        temp1.append(listToCross2[cmp2+1][vl])
-                        temp2.append(listToCross2[cmp2][vl])
-            #cmp2+=2
-            #print(cmp2)
+                    temp1.append(listToCross[cmp1][vl])
+                    temp2.append(listToCross[j][vl])
+                        
             check = 0
             for vl in range(len(expected_output)):
                     #print(temp1[vl])
                 if temp1[vl]!=expected_output[vl]:
                         #print(1)
                     check=1
-                       
+                        
             if check==0:
                 maincount+=1
                 flag=1
@@ -137,36 +105,27 @@ def crossover(i):
                 flag=1
                 maincount+=1
                     #print(1)
-                                           
+                #new two population found after crossover...                           
             listcr.append(temp1)
             listcr.append(temp2)
-                
-    listToCross2 = listcr 
-            
-            
-            
+        #storing the new populations for future need like if i >0..these new populations will crossover among them..      
+        listToCross2 = listcr 
+    #equations are smae here but combinations are different..     
+   
        
        
         #print(listcr)
        
-    return flag,maincount        
-    
-#list assigning after best fit function..  
-for i in range(len(populations)):
-    if value[i]<=2:
-        listToCross.append(populations[i])
-        
+    return flag,maincount 
 #here looping limit is 3 because it assumed that within 3 crossover target generation will be found..
-
 for i in range(3):
-    
-    flag,maincount = crossover(i)
+    bestFit(listToCross2)
+    assigningBestPopulations(listToCross2)
+    flag,maincount = crossover()
     if flag==1:
-        print("expected genertion found ",maincount,"time!!")
+        print("found ",maincount)
         break
-         
-        
-        
+