Merge branch 'master' of https://git.ccom.uprrp.edu/CCOM4030/EdElSe into Eduardo-quickSort

.gitignore

@@ -0,0 +1 @@
+.DS_Store

sorting.py

@@ -9,13 +9,83 @@ Al final se imprimen los promedios de cada algortimo
 from random import randint
 import time
 
-def mergeSort(lista):
+def merge(lista, start, middle, end):
+	# Create Temp arrays with specifically needed sizes foe the given array
+	sizeOfHalf1 = middle - start + 1
+	sizeOfHalf2 = end - middle
+	half1 = [0] * (sizeOfHalf1)
+	half2 = [0] * (sizeOfHalf2)
+    # Copy data from the received array to the temporary working arrays
+	for i in range(0, sizeOfHalf1):
+		half1[i] = lista[start + i]
+	for t in range(0,sizeOfHalf2):
+		half2[t] = lista[middle + 1 + t] 
+	
+	# Merge the temporary arrays back into the recieved list
+	i = 0 # initial index of firs subarray 
+	t = 0 # initial index of second subarray
+	k = start # initial index of merged subarray
+
+	while i < sizeOfHalf1 and t < sizeOfHalf2:
+		if half1[i] <= half2[t]:
+			lista[k] = half1[i]
+			i += 1
+		else:
+			lista[k] = half2[t]
+			t += 1
+		k += 1
+	# Copy the remaining elements on half1 if there are any
+	while i < sizeOfHalf1:
+		lista[k] = half1[i]
+		i += 1
+		k += 1
+
+	# Copy the remaining elements on half2 if there are any
+	while t < sizeOfHalf2:
+		lista[k] = half2[t]
+		t += 1
+		k += 1
+
+# start is for left index and end is the right index of the subarray
+# of lista to be stored 
+
+def mergeSort(lista,l,r):
 	#definan el algoritmo de ordenamiento mergesort
+	if l < r:
+		# Same as (l+r)//2, but avoids overflow for
+        # large l and h
+		m = l+(r-l)//2
+
+		# Sort each half
+		mergeSort(lista, l, m)
+		mergeSort(lista, m+1, r)
+		# Merge the sorted halves
+		merge(lista, l, m, r)
+
 	return lista
 
+# https://en.wikipedia.org/wiki/Heapsort
+def heapify(lista, n, i):
+	largest = i
+	l = 2 * i + 1
+	r = 2 * i + 2
+	if l < n and lista[i] < lista[l]:
+		largest = l
+	if r < n and lista[largest] < lista[r]:
+		largest = r
+	if largest != i:
+		lista[i], lista[largest] = lista[largest], lista[i]
+		heapify(lista, n, largest)
+
 def heapSort(lista):
-	#definan el algoritmo de ordenamiento heapsort
-	return lista
+	n = len(lista)
+
+	for i in range(n//2, -1, -1):
+		heapify(lista, n, i)
+
+	for i in range(n-1, 0, -1):
+		lista[i], lista[0] = lista[0], lista[i]
+		heapify(lista, i, 0)
 
 def quickSort(lista):
     #definan el algoritmo de ordenamiento quicksort
@@ -65,7 +135,9 @@ for i in range(veces):
 	searchlista=list(mergelista)
 
 	t1 = time.clock() 				#seteamos el tiempo al empezar
-	mergeSort(mergelista) 				#ejecutamos el algoritmo mergeSort
+	l = 0
+	r = len(mergelista) - 1
+	finished = mergeSort(mergelista, l,r) 				#ejecutamos el algoritmo mergeSort
 	acumulaMerge+=time.clock()-t1 	#acumulamos el tiempo de ejecucion
 	
 	t1 = time.clock()				#seteamos el tiempo al empezar
@@ -81,7 +153,7 @@ for i in range(veces):
 	acumulaShell+=time.clock()-t1 	#acumulamos el tiempo de ejecucion
 
 #imprimos los resultados
-print "Promedio de tiempo de ejecucion de "+ str(veces) +" listas de largo " + str(largoLista)
+print "Promedio de tiempo de ejecucion de " + str(veces) +" listas de largo " + str(largoLista)
 print "MergeSort " + str(acumulaMerge/veces) + " segundos"
 print "HeapSort " + str(acumulaHeap/veces) + " segundos"
 print "QuickSort " + str(acumulaQuick/veces) + " segundos"