diff --git a/homework1.4/task.py b/homework1.4/task.py
index 5da90d9..74e9b22 100644
--- a/homework1.4/task.py
+++ b/homework1.4/task.py
@@ -3,33 +3,50 @@
           ['red', 'red', 'green', 'green', 'red'],
           ['red', 'red', 'red', 'red', 'red']]
 
-measurements = ['green', 'green', 'green', 'green', 'green']
+measurements = ['green', 'green', 'green' ,'green', 'green']
+p=[]
 
-
-motions = [[0, 0], [0, 1], [1, 0], [1, 0], [0, 1]]
+motions = [[0,0],[0,1],[1,0],[1,0],[0,1]]
 
 sensor_right = 0.7
-
 p_move = 0.8
-
+sensor_wrong=1.0-sensor_right
+p_stay=1.0-p_move
+
+def sense(p,colors,measurement):
+   aux=[[0.0 for row in range (len(p[0]))] for col in range(len(p))]
+   s=0.0
+   
+   for i in range(len(p)):
+     for j in range (len(p[i])):
+        hit=(measurement==colors[i][j])
+        aux[i][j]=p[i][j]*(hit*sensor_right+(1-hit)*(sensor_wrong))
+        s+=aux[i][j]
+   
+   for i in range (len(aux)):
+      for j in range (len(p[i])):
+        aux[i][j]/=s
+   return aux
+    
+def move(p, motion):
+  aux=[[0.0 for row in range(len(p[0]))] for col in range (len(p))]
+    
+  for i in range(len(p)):
+      for j in range (len(p[i])):
+          aux[i][j]=(p_move*p[(i-motion[0])%len(p)][(j-motion[1])%len(p[i])])+(p_stay*p[i][j])
+  return aux
+
+                                                                
 def show(p):
     for i in range(len(p)):
         print p[i]
 
+            
+pinit=1.0/float(len(colors))/float(len(colors[0]))
+p=[[pinit for row in range(len(colors[0]))] for col in range(len(colors))]
+   
+for k in range(len(measurements)):
+    p=move(p, motions[k])
+    p=sense(p,colors,measurements[k])
 
-def calculate():
-
-    #DO NOT USE IMPORT
-    #ENTER CODE BELOW HERE
-    #ANY CODE ABOVE WILL CAUSE
-    #HOMEWORK TO BE GRADED
-    #INCORRECT
-  
-    p = []
-
-    #Your probability array must be printed 
-    #with the following code.
-
-    show(p)
-    return p
-
+show(p)