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@@ -9,86 +9,40 @@ Al final se imprimen los promedios de cada algortimo
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from random import randint
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import time
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-def merge(lista, start, middle, end):
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- # Create Temp arrays with specifically needed sizes foe the given array
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- sizeOfHalf1 = middle - start + 1
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- sizeOfHalf2 = end - middle
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- half1 = [0] * (sizeOfHalf1)
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- half2 = [0] * (sizeOfHalf2)
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- # Copy data from the received array to the temporary working arrays
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- for i in range(0, sizeOfHalf1):
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- half1[i] = lista[start + i]
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- for t in range(0,sizeOfHalf2):
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- half2[t] = lista[middle + 1 + t]
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-
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- # Merge the temporary arrays back into the recieved list
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- i = 0 # initial index of firs subarray
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- t = 0 # initial index of second subarray
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- k = start # initial index of merged subarray
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-
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- while i < sizeOfHalf1 and t < sizeOfHalf2:
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- if half1[i] <= half2[t]:
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- lista[k] = half1[i]
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- i += 1
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- else:
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- lista[k] = half2[t]
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- t += 1
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- k += 1
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- # Copy the remaining elements on half1 if there are any
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- while i < sizeOfHalf1:
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- lista[k] = half1[i]
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- i += 1
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- k += 1
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-
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- # Copy the remaining elements on half2 if there are any
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- while t < sizeOfHalf2:
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- lista[k] = half2[t]
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- t += 1
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- k += 1
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-
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-# start is for left index and end is the right index of the subarray
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-# of lista to be stored
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-
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-def mergeSort(lista,l,r):
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+def mergeSort(lista):
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#definan el algoritmo de ordenamiento mergesort
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- if l < r:
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- # Same as (l+r)//2, but avoids overflow for
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- # large l and h
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- m = l+(r-l)//2
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-
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- # Sort each half
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- mergeSort(lista, l, m)
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- mergeSort(lista, m+1, r)
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- # Merge the sorted halves
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- merge(lista, l, m, r)
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+ return lista
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+def heapSort(lista):
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+ #definan el algoritmo de ordenamiento heapsort
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return lista
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-# https://en.wikipedia.org/wiki/Heapsort
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-def heapify(lista, n, i):
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- largest = i
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- l = 2 * i + 1
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- r = 2 * i + 2
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- if l < n and lista[i] < lista[l]:
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- largest = l
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- if r < n and lista[largest] < lista[r]:
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- largest = r
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- if largest != i:
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- lista[i], lista[largest] = lista[largest], lista[i]
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- heapify(lista, n, largest)
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+def quickSort(lista):
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+ #definan el algoritmo de ordenamiento quicksort
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+ elements = len(lista)
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-def heapSort(lista):
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- n = len(lista)
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+ #Base case
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+ if elements < 2:
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+ return lista
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- for i in range(n//2, -1, -1):
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- heapify(lista, n, i)
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+ current_position = 0 #Position of the partitioning element
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- for i in range(n-1, 0, -1):
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- lista[i], lista[0] = lista[0], lista[i]
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- heapify(lista, i, 0)
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+ for i in range(1, elements): #Partitioning loop
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+ if lista[i] <= lista[0]:
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+ current_position += 1
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+ temp = lista[i]
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+ lista[i] = lista[current_position]
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+ lista[current_position] = temp
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-def quickSort(lista):
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- #definan el algoritmo de ordenamiento quicksort
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+ temp = lista[0]
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+ lista[0] = lista[current_position]
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+ lista[current_position] = temp #Brings pivot to it's appropriate position
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+
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+ left = quickSort(lista[0:current_position]) #Sorts the elements to the left of pivot
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+ right = quickSort(lista[current_position+1:elements]) #sorts the elements to the right of pivot
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+
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+ lista = left + [lista[current_position]] + right #Merging everything together
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+
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return lista
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def shellSort(lista):
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@@ -111,9 +65,7 @@ for i in range(veces):
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searchlista=list(mergelista)
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t1 = time.clock() #seteamos el tiempo al empezar
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- l = 0
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- r = len(mergelista) - 1
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- finished = mergeSort(mergelista, l,r) #ejecutamos el algoritmo mergeSort
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+ mergeSort(mergelista) #ejecutamos el algoritmo mergeSort
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acumulaMerge+=time.clock()-t1 #acumulamos el tiempo de ejecucion
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t1 = time.clock() #seteamos el tiempo al empezar
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@@ -129,7 +81,7 @@ for i in range(veces):
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acumulaShell+=time.clock()-t1 #acumulamos el tiempo de ejecucion
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#imprimos los resultados
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-print "Promedio de tiempo de ejecucion de " + str(veces) +" listas de largo " + str(largoLista)
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+print "Promedio de tiempo de ejecucion de "+ str(veces) +" listas de largo " + str(largoLista)
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print "MergeSort " + str(acumulaMerge/veces) + " segundos"
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print "HeapSort " + str(acumulaHeap/veces) + " segundos"
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print "QuickSort " + str(acumulaQuick/veces) + " segundos"
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