def timeAlgorithm(array, algorithm):
if algorithm == "counting":
start = time.time_ns()
countingSort(array)
end = time.time_ns()
elif algorithm == "quick":
start = time.time_ns()
quickSort(array, 0, len(array) - 1)
end = time.time_ns()
elif algorithm == "insertion":
start = time.time_ns()
insertionSort(array)
end = time.time_ns()
elif algorithm == "merge":
start = time.time_ns()
mergeSort(array)
end = time.time_ns()
elif algorithm == "heap":
start = time.time_ns()
heapSort(array, 0, len(array))
end = time.time_ns()
elif algorithm == "intro":
start = time.time_ns()
introSort(array)
end = time.time_ns()
else:
return 1
return end - start
def introSortRec(array, start, end, maxDepth):
if end - start > 1:
array, pivot = partition(array, start, end)
if maxDepth == 0:
heapSort(array, start, end)
elif start < end:
introSortRec(array, start, pivot, maxDepth - 1)
introSortRec(array, pivot + 1, end, maxDepth - 1)
def generateAndTime(arraySize):
array = np.random.rand(arraySize)
t1 = time.time()
heapSort(array)
t2 = time.time()
# print(array)
elapsed = t2 - t1
return elapsed
def sampleMedianSelect(list, left, right, m):
if m >= len(list[left:right + 1]):
#print("m>len(list)->decreasing m")
m = len(list[left:right + 1])
S = random.sample(list[left:right + 1], m)
if m <= 20:
selectionSort(S)
else:
heapSort(S)
return S[ceil(len(S) / 2)]
def sort_all(N): # num of array = 2**N
input = read_input(N) #读取待排序数据，input为python list
ret = {} #python 字典
ret["origin"] = input #初始数据
#ret["merge_sort"][0] 存放排序结果 ret["merge_sort"][1] 存放排序所花时间，下同
begin = time.time()
ret["merge_sort"] = [ mergeSort(input.copy(), 0, len(input) - 1) ]
end = time.time()
ret["merge_sort"].append(end - begin)
begin = time.time()
ret["heap_sort"] = [ heapSort(input.copy()) ]
end = time.time()
ret["heap_sort"].append(end - begin)
begin = time.time()
ret["quick_sort"] = [ quickSort(input.copy(), 0, len(input) - 1) ]
end = time.time()
ret["quick_sort"].append(end - begin)
begin = time.time()
ret["count_sort"] = [ countSort(input.copy(), 65536) ]
end = time.time()
ret["count_sort"].append(end - begin)
return ret
def main():
n = int(input("Enter the number of items you would like to sort: "))
myList = []
for index in range(n):
myList.append(random.randint(1, n))
#print( "Unsorted List:", myList)
start = time.perf_counter()
heapSort(myList)
endSort = time.perf_counter()
#print( "Sorted List: ", myList)
print("Total heap sort time of", n,
"random items %7.6f" % (endSort - start))
def startAlgorithm():
global data
if not data: return
if(algMenu.get() == 'Bubble Sort'):
bubbleSort(data, drawData, speedScale.get())
elif(algMenu.get() == 'Quick Sort'):
quickSort(data, drawData, speedScale.get())
drawData(data, ['green' for x in range(len(data))])
elif(algMenu.get() == 'Insertion Sort'):
insertionSort(data, drawData, speedScale.get())
elif(algMenu.get() == 'Selection Sort'):
selectionSort(data, drawData, speedScale.get())
elif (algMenu.get() == 'Heap Sort'):
heapSort(data, drawData, speedScale.get())
elif (algMenu.get() == 'Merge Sort'):
mergeSort(data, drawData, speedScale.get())
drawData(data, ['green' for x in range(len(data))])
def introSort(array, begin=0, end=None, depth=0, *, reverse=False):
if end is None:
end = len(array) - 1
if depth < log2(len(array)):
if begin < end:
mid = partition(array, begin, end, reverse=reverse)
introSort(array, begin, mid - 1, depth + 1, reverse=reverse)
introSort(array, mid + 1, end, depth + 1, reverse=reverse)
else:
array[begin:end + 1] = heapSort(array[begin:end + 1], reverse=reverse)
def main(filename, e):
try:
fd = open(filename, 'r')
except:
print('Unable to open file')
exit(-1)
_items = fd.read()
items = map(lambda x: int(x), _items.split())
items = heapSort.heapSort(items)
print('Sorted list = %s' %items)
index = findIndex(items, e)
print(index)
def timeElapsed(algoritmo, arr):
start_time = time.time()
comparaciones = 0
if(algoritmo == "quickStatic"):
comparaciones = quickSortStaticPiv.quickSort(arr)
elif(algoritmo == "quickAle"):
comparaciones = quickSortRandomPiv.quickSort(arr)
elif(algoritmo == "heap"):
comparaciones = heapSort.heapSort(arr)
elapsed_time = time.time() - start_time
print("TamList: ", len(arr), "\tTime: ", elapsed_time, "Comps: ", comparaciones)
def quicheSortRec(lst, limit):
"""
A non in-place, depth limited quickSort, using median-of-3 pivot.
Once the limit drops to 0, it uses heapSort instead.
"""
if lst == []:
return lst
if limit==0:
return heapSort.heapSort(lst)
else:
pivot= qsPivotMedian3.medianOf3(lst) # select the first element as the pivot
less, same, more = qsPivotFirst.partition(pivot, lst)
return quicheSortRec(less,limit-1) + same + quicheSortRec(more,limit-1)
def sampleMedianSelect(list, left, right, m):
if m >= len(list[left:right + 1]):
print(
"m>len(list)->decreasing m"
) # il caso in cui m sia più grande dell'array viene gestito portandolo
m = len(
list[left:right + 1]
) # alla minima grandezza accettabile affinche l'algoritmo funzioni
# cosi in un caso pratico in cui verrebbe utilizzato in qualche applicazione
S = random.sample(
list[left:right + 1], m
) # in cui m è scelto a caso l'algoritmo non si ferma,al massimo rallenta un po'
if m <= 20: # oppure potrebbe anche non accadere mai con opportuni controlli a monte
bubbleSort(
S
) # nella scelta di m da parte dell'utente o dalla funzione chiamante
#inserctionSort(S)
#selectionSort(S)
else:
#S.sort()
#mergeSort(S)
#quickSort(S)
heapSort(S)
return S[ceil(len(S) / 2)]
def quicheSortRec(lst, limit):
"""
A non in-place, depth limited quickSort, using median-of-3 pivot.
Once the limit drops to 0, it uses heapSort instead.
"""
if lst == []:
return lst
if limit == 0:
return heapSort.heapSort(lst)
else:
pivot = qsPivotMedian3.medianOf3(
lst) # select the first element as the pivot
less, same, more = qsPivotFirst.partition(pivot, lst)
return quicheSortRec(less, limit - 1) + same + quicheSortRec(
more, limit - 1)
def sortAlgo():
global boo
global array
global barRec
global epochs
epochs = [0]
boo = True
try:
size = int(sizeEntry.get())
except:
size = 15
if size < 0:
size = 1
#change the value of the speed selected
s = 1001 - speed.get()
#decide the algo
if algDropDown.get() == "Merge Sort":
algo = mergeSort(array, 0, size - 1)
elif algDropDown.get() == "Bubble Sort":
algo = bubbleSort(array)
elif algDropDown.get() == "Quick Sort":
algo = quickSort(array, 0, size - 1)
elif algDropDown.get() == "Insertion Sort":
algo = insertionSort(array)
elif algDropDown.get() == "Selection Sort":
algo = selectionSort(array)
elif algDropDown.get() == "Heap Sort":
algo = heapSort(array)
elif algDropDown.get() == "Radix Sort":
algo = radixSort(array)
#start animation
anima = anim.FuncAnimation(fig,
func=updatePlot,
fargs=(barRec, epochs),
frames=algo,
interval=s,
repeat=False,
blit=False)
anima._start()
def quipSortRec(lst, limit):
"""
A non in-place, depth limited quickSort, using median-of-3 pivot.
Once the limit drops to 0, it uses heapSort instead.
"""
if len(lst) == 1 or lst == []:
return lst
if limit <= 0:
return heapSort.heapSort(lst)
pivot = [median([lst[0], lst[len(lst) // 2], lst[len(lst) - 1]])]
lst2 = []
lst3 = []
for i in lst:
if i < pivot[0]:
lst2.append(i)
elif i > pivot[0]:
lst3.append(i)
else:
pivot.append(i)
return quipSortRec(lst2, limit - 1) + pivot + quipSortRec(lst3, limit - 1)
def quipSortRec(lst, limit):
"""
A non in-place, depth limited quickSort, using median-of-3 pivot.
Once the limit drops to 0, it uses heapSort instead.
"""
if len(lst) == 1 or lst == []:
return lst
if limit <= 0:
return heapSort.heapSort(lst)
pivot = [median([lst[0], lst[len(lst) // 2], lst[len(lst) - 1]])]
lst2 = []
lst3 = []
for i in lst:
if i < pivot[0]:
lst2.append(i)
elif i > pivot[0]:
lst3.append(i)
else:
pivot.append(i)
return quipSortRec(lst2, limit - 1) + pivot + quipSortRec(lst3, limit - 1)
def sort_me_timed_heap(arr):
heapSort.heapSort(heapSort.makeHeap(arr))
def test_heapSort(self):
arr1 = [2, 5, 3, 10, 12]
sortedArray = heapSort(arr1)
result = np.arrayEqual([2, 3, 5, 10, 12], sortedArray)
self.assertTrue(result)
end = time.time()
print(end - start)
print "END"
print "----------------------------------"
for j in range(0, number_of_element):
for i in range(0, number_of_array):
#now = datetime.datetime.now() #print the time and date for the record
#print now
start = time.time()
#sorted(array[i])
#mergeSort(array_set1[j][i])
#quickSortHoare(array_set[j][i])
#quickSortLomuto(array[i])
#quickSortOpenSource(array[i])
heapSort(array_set2[j][i])
#array[i] = quickSort(array[i])
end = time.time()
print(end - start)
print "END"
print "----------------------------------"
for j in range(0, number_of_element):
for i in range(0, number_of_array):
#now = datetime.datetime.now() #print the time and date for the record
#print now
start = time.time()
#sorted(array[i])
#mergeSort(array_set1[j][i])
#quickSortHoare(array_set[j][i])
#quickSortLomuto(array[i])
end = time()
temp = end - start
print("Sample sorted with bubbleSort time -->", temp)
# OTHER SORTING ALGHORITMS
A = B
start = time()
mergeSort(A) # mergeSort
end = time()
temp = end - start
print("Array sorted with mergeSort time-->", temp)
A = B
start = time()
heapSort(A) # heapSort
end = time()
temp = end - start
print("Array sorted with heapSort time-->", temp)
A = B
start = time()
quickSort(A, False) # non-deterministic quickSort
end = time()
temp = end - start
print(
"Array sorted with classic non-deterministic quickSort time-->",
temp)
A = B
start = time()
def test_SortByHeap(self):
nums=[3,1,2,5,6,7,8,10,2,4]
heapSort(nums,len(nums)-1)
self.assertEqual([1,2,2,3,4,5,6,7,8,10],nums);
def testHeapSort(self):
A = [5, 1, 3, 0, 10]
heapSort.heapSort(A)
B = [0, 1, 3, 5, 10]
if (A != B):
self.fail("heapSort method fails.")
def comp(list1, list2):
for val in list1:
if val in list2:
return True
return False
"""
for i in range (0,len_each_array):
print i,
testArray[i].sort()
print len(testArray[i]),
quickSortHoare(testArrayCopy[i])
print len(testArrayCopy[i])
"""
len_array_test = len(arrayTest)
for i in range(0, len_array_test):
for j in range(0, 5):
print i, j, len(arrayTest[i][j]),
arrayTest[i][j].sort()
#arrayTestCopy[i][j] = quickSort(arrayTestCopy[i][j])
#quickSortOpenSource(arrayTestCopy[i][j])
#mergeSort(arrayTestCopy[i][j])
heapSort(arrayTestCopy[i][j])
if comp(arrayTestCopy[i][j], arrayTestCopy[i][j]) == True:
print "PASS"
else:
print "FAIL"
print("The quick sorted array with size ", len(array), "is ")
for i in range(0, len(array)):
print("array[", i, "] = ", array[i])
end_time = time.time()
quick_sort_time = end_time - start_time
print("Quick sort time for size", n, "is ", quick_sort_time)
arr.clear()
for j in range(0, n):
arr.append(random.randrange(0, 1000, 1))
start_time = time.time()
array = bubbleSort.bubbleSort(arr)
print("The bubble sorted array with size ", len(array), "is ")
for i in range(0, len(array)):
print("array[", i, "] = ", array[i])
end_time = time.time()
bubble_sort_time = end_time - start_time
print("Bubble sort time for size", n, "is ", bubble_sort_time)
arr.clear()
for j in range(0, n):
arr.append(random.randrange(0, 1000, 1))
start_time = time.time()
array = heapSort.heapSort(arr)
print("The Heap sorted array with size ", len(array), "is ")
for i in range(0, len(array)):
print("array[", i, "] = ", array[i])
end_time = time.time()
heap_sort_time = end_time - start_time
print("Heap sort time for size", n, "is ", heap_sort_time)
import TestHelper
import MergeSort
import QuickSort
import heapSort
from time import time
l = TestHelper.CreateRandomIntList(100000, 10, 9000000)
lc = list(l)
t0 = time()
qck = QuickSort.QuickSort(l)
t1 = time()
s = MergeSort.MergeSort(l)
t2 = time()
heapSort.heapSort(lc)
t3 = time()
print((l[99], s[99]))
print((l[99], qck[99]))
print((l[99], lc[99]))
print('function vers1 takes %f' % (t1 - t0))
print('function vers2 takes %f' % (t2 - t1))
print('function vers3 takes %f' % (t3 - t2))
