for k in range(0, repetitions):
for n in range(100, 10100, 100):
random_data = random.sample(range(n), n)
qsort_data = random_data
merge_data = random_data
insert_data = random_data
dqsort_data = random_data
# Perform QuickSort on our randomly-generated data
q_sorting = QuickSort()
start = time.time()
q_sorting.quick_sort(qsort_data, 0, len(qsort_data) - 1)
end = time.time()
elapsed = end - start
qsort[array_index] = [
k, n, q_sorting._compares, q_sorting._shifts, elapsed
]
# Perform MergeSort on our randomly-generated data
m_sorting = MergeSort()
start = time.time()
result = m_sorting.mergesort_asc(merge_data)
end = time.time()
elapsed = end - start
from quick_sort import QuickSort my_list = [4, 6, 44, 57, 1, 77, 32, 11, 33, 3, 4] qc = QuickSort(my_list) print(qc.partition()) qc.quick_sort() print(my_list)
def fn_quick_sort(input, output, start):
q_sort = QuickSort()
q_sort.quick_sort(0, len(input) - 1, input)
assert input == output
end = time.time()
from utils import algorithms.CArray
from selection_sort import selection_sort
from bubble_sort import bubble_sort
from insertion_sort import insertion_sort
from quick_sort import QuickSort
list = algorithms.CArray(20)
list.set_data()
print('///// ARRAY TO ORDER /////')
print(list.data_store)
print('//////////////////////////')
print('QuickSort')
sortable_array = QuickSort(list.data_store)
sortable_array.quick_sort(0, len(list.data_store) - 1)
print(sortable_array.array)
print('BubbleSort')
print(bubble_sort(list.data_store))
print('SelectionSort')
print(selection_sort(list.data_store))
print('InsertionSort')
print(insertion_sort(list.data_store))
def test_quick_sort(self):
sortedList = QuickSort.quick_sort(self.targetList)
self.assertTrue(sortedList == self.checkList)
