def startAlgorithm():
global data
if not data: return
if algMenu.get() == 'Quick Sort':
quick_sort(data, 0, len(data) - 1, drawData, speedScale.get())
elif algMenu.get() == 'Bubble Sort':
bubble_sort(data, drawData, speedScale.get())
elif algMenu.get() == 'Insertion Sort':
insertion_sort(data, drawData, speedScale.get())
elif algMenu.get() == 'Merge Sort':
merge_sort(data, drawData, speedScale.get())
elif algMenu.get() == 'Selection Sort':
selection_sort(data, drawData, speedScale.get())
elif algMenu.get() == 'Selection Sort':
selection_sort(data, drawData, speedScale.get())
elif algMenu.get() == 'Radix Sort':
radix_sort(data, drawData, speedScale.get())
drawData(data, ['green' for x in range(len(data))])
def reinsert(self, old_paths, new_paths, population):
# 父子融合
tmp_paths = old_paths
tmp_paths.extend(new_paths)
# 优胜劣汰
quick_sort(tmp_paths)
return tmp_paths[:population]
def satrtAlgo():
global data
if not data: return
if (algMenu.get() == 'Quick Sort'):
quick_sort(data, 0, len(data) - 1, drawData, speedScale.get())
elif (algMenu.get() == 'Bubble Sort'):
bubble_sort(data, drawData, speedScale.get())
elif (algMenu.get() == 'Merge Sort'):
merge_sort(data, drawData, speedScale.get())
drawData(data, ['green' for x in range(len(data))])
def StartAlgo():
global data
if not data: return
if algMenu.get() == "Quick Sort":
quick_sort(data, 0, len(data) - 1, draw_data, speedScale.get())
if algMenu.get() == "Bubble Sort":
bubbleSort(data, draw_data, speedScale.get())
elif algMenu.get() == "Merge Sort":
merge_sort(data, draw_data, speedScale.get())
draw_data(data, ["yellow" for x in range(len(data))])
def startAlgo():
global data
if not data: return
if algMenu.get() == 'Quick Sort':
quick_sort(data, 0,
len(data) - 1, drawData, speedScale.get(), sizeEntry.get())
elif algMenu.get() == 'Bubble Sort':
bubble_sort(data, drawData, speedScale.get(), sizeEntry.get())
elif algMenu.get() == 'Merge Sort':
start_mergeSort(data, drawData, speedScale.get(), sizeEntry.get())
drawData(data, sizeEntry.get(), ['navy' for x in range(len(data))])
def startAlgorithm():
global data
#check which algorithm is selected
if algoMenu.get() == 'Bubble Sort':
bubbleSort(data, draw, speed.get())
elif algoMenu.get() == 'Merge Sort':
mergeSort(data, draw, speed.get())
elif algoMenu.get() == 'Selection Sort':
selectionSort(data, draw, speed.get())
elif algoMenu.get() == 'Insertion Sort':
insertionSort(data, draw, speed.get())
elif algoMenu.get() == 'Quick Sort':
quick_sort(data, 0, len(data) - 1, draw, speed.get())
draw(data, ['green' for x in range(len(data))])
def StartAlgorithm():
global data
if not data: return
if algMenu.get() == 'Quick Sort':
quick_sort(data, 0, len(data) - 1, drawData, speedScale.get())
drawData(data, ['green' for x in range(len(data))])
elif algMenu.get() == 'Bubble Sort':
bubble_sort(data, drawData, speedScale.get())
elif algMenu.get() == 'Merge Sort':
print("Merge Sort Selected")
def startAlgorithm():
global array
if not array:
return
# get the speed of the algorithm visualiser
sizeNum = sizeEntry.get()
speed = 10 / (sizeNum * pow(sizeNum, 0.5))
# visualise an algorithm
if algoMenu.get() == "Insertionsort":
insertion_sort(array, drawArray, speed)
if algoMenu.get() == "Mergesort":
merge_sort(array, drawArray, speed)
if algoMenu.get() == "Bubblesort":
bubble_sort(array, drawArray, speed)
if algoMenu.get() == "Quicksort":
quick_sort(array, drawArray, speed)
if algoMenu.get() == "Heapsort":
heap_sort(array, drawArray, speed)
def binary(lis, elem):
comparisons = 0
array_accesses = 0
(comp1, access1) = quick_sort(lis, 0, len(lis) - 1, 0, 0)
comparisons += comp1
access1 += access1
(result, comparisons,
array_accesses) = binary_search(lis, 0,
len(lis) - 1, elem, comparisons,
array_accesses)
if result != -1:
print("Binary search:")
print("Element is present at index: " + str(result))
print("No. comparisons: " + str(comparisons) +
", no. array accesses: " + str(array_accesses))
else:
print("Element is not present in array")
data1.sort() e0 = time.clock() print 'The python sorted:', e0-s0 s7 = time.clock() shellSort.shellSort(data7) e7 = time.clock() print 'shellSort:', e7-s7 s1 = time.clock() mergeSort.mergeSort(data1) e1 = time.clock() print 'mergeSort:', e1-s1 s5 = time.clock() quickSort.quick_sort(data5,0,len(data5)) e5 = time.clock() print 'quick_sort:', e5-s5 s6 = time.clock() quickSort.qSort(data6) e6 = time.clock() print 'qSort:', e6-s6 s3 = time.clock() insertionSort.insertionSort(data3) e3 = time.clock() print 'insertionSort:', e3-s3 s8 = time.clock() insertionSort.insertSort(data8, 0, len(data8))
bucket_sort(temp, how_many // 100)
temp = array[:]
comb_sort(temp)
temp = array[:]
counting_sort(temp)
temp = array[:]
heap_sort(temp)
temp = array[:]
insertion_sort(temp)
temp = array[:]
shell_sort(temp)
temp = array[:]
lsd_radix_sort(temp)
temp = array[:]
pigeonhole_sort(temp)
temp = array[:]
selection_sort(temp)
temp = array[:]
(comparisons, array_accesses, additional_space) = merge_sort(temp)
print("Merge sort:")
print("No. comparisons: " + str(comparisons) + ", no. array accesses: " +
str(array_accesses) + ", no. additional space required: " +
str(additional_space))
temp = array[:]
(comparisons, array_accesses) = quick_sort(temp, 0, len(temp) - 1, 0, 0)
additional_space = 0
print("Quick sort:")
print("No. comparisons: " + str(comparisons) + ", no. array accesses: " +
str(array_accesses) + ", no. additional space required: " +
str(additional_space))
paths = alg.init_population(starting_point, objectives, Kca)
for p in range(len(paths)):
paths[p].fitness = alg.get_fitness(paths[p], occ_grid, pri_grid,
starting_point, end_point,
privacy_sum, obstacle_num)
max_p = max(paths, key=lambda x: x.fitness)
max_f = -5
count = 0
fitnv = []
print(len(paths))
for i in range(max_generation):
quick_sort(paths)
if max_f < paths[0].fitness:
max_f = paths[0].fitness
print('\033[94m Current maximum fitness:\033[0m\033[92m ' +
str(max_f) + '\033[0m\033[94m, Generation:\033[0m\033[92m ' +
str(i) + ' \033[0m')
for j in range(len(paths[0].points)):
print(paths[0].points[j])
print("the generation", i, len(paths[0].points))
alg.get_fitness(paths[0], occ_grid, pri_grid, starting_point,
end_point, privacy_sum, obstacle_num)
'''
p1 = alg.tournament_select(paths)
p2 = alg.tournament_select(paths)
new_path = []
print("Selection Sort Timer: ", end-start, "s", sep='')
print("List Returned:", test1)
space(1)
border('M')
# MERGE SORT TEST
start = time.time()
merge_sort(test2)
end = time.time()
border('M')
space(1)
print("Merge Sort Timer: ", end-start, "s", sep='')
print("List Returned:", test2)
space(1)
border('M')
# QUICK SORT TEST
start = time.time()
quick_sort(test3, 0, MAX - 1)
end = time.time()
border('M')
space(1)
print("Quick Sort Timer: ", end-start, "s", sep='')
print("List Returned:", test3)
space(1)
# print closing
border('D')
space(3)
if list[middle] < value: return bit_search(list, value, middle+1, high) elif list[middle] > value: return bit_search(list, value, low, middle-1) else: return middle def bit_search_by_loop(list, value, low, high): if low > high: return -1 while(True): middle = (low + high) / 2 if (list[middle] < value): low = middle + 1 elif (list[middle] > value): high = middle - 1 else: return middle if __name__ == '__main__': lis = [3, 987, 6, 22, 9, 333, 22, 44, 9999, 555, 999, 1234, 1235, 1255, 1288] val = 1235 sortList = quick_sort(lis) ret = bit_search_by_loop(sortList, val, 0, len(lis)) print sortList print ret, lis[ret]
def main():
from quickSort import q_count
sys.setrecursionlimit(10000)
# instantiate write to file
write_file = WriteToFile()
merge_sort = MergeSort()
# 100 list
first_list, second_list, third_list, fourth_list = arrayGenerator.generate_random_list_number(100)
print("{}, {}, {}, {}".format(len(first_list), len(second_list), len(third_list), len(fourth_list)))
# sorting 100 list with bubblesort
start_time = time.perf_counter()
first_list, comparisons = bubbleSort.bubble_sort(first_list)
end_time = time.perf_counter()
print("Bubble Sort time: %s seconds" % (end_time - start_time))
print("Bubble Sort comparisions: ", comparisons)
# Creating the semisorted list
first_list = arrayGenerator.randomizer(first_list)
# sorting 100 semisorted list with bubblesort
start_time_semisorted = time.perf_counter()
first_list, semisorted_comparisons = bubbleSort.bubble_sort(first_list)
end_time_semisorted = time.perf_counter()
print("Bubble Sort time on semisorted array: %s seconds" % (end_time_semisorted - start_time_semisorted))
print("Bubble Sort comparisions on semisorted array: ", semisorted_comparisons)
# Writing the Bubble Sort data to the file
write_file.write_to_file('Bubble Sort', 'O(n^2)', 'O(n)', 100, end_time - start_time, comparisons, end_time_semisorted - start_time_semisorted, semisorted_comparisons)
# sorting 100 list with selectionsort
start_time = time.perf_counter()
second_list, comparisons = selectionSort.selection_sort(second_list)
end_time = time.perf_counter()
print("Selection Sort time: %s seconds" % (end_time - start_time))
print("Selection Sort comparisions: ", comparisons)
# Creating the semisorted list
second_list = arrayGenerator.randomizer(second_list)
# sorting 100 semisorted list with selectionsort
start_time_semisorted = time.perf_counter()
second_list, semisorted_comparisons = selectionSort.selection_sort(first_list)
end_time_semisorted = time.perf_counter()
print("Selection Sort time on semisorted array: %s seconds" % (end_time_semisorted - start_time_semisorted))
print("Selection Sort comparisions on semisorted array: ", semisorted_comparisons)
# Writing the Selection Sort data to the file
write_file.write_to_file('Selection Sort', 'O(n^2)', 'O(n^2)', 100, end_time - start_time, comparisons, end_time_semisorted - start_time_semisorted, semisorted_comparisons)
# sorting 100 list with mergesort
start_time = time.perf_counter()
third_list = merge_sort.merge_sort(third_list)
end_time = time.perf_counter()
print("Merge Sort time: %s seconds" % (end_time - start_time))
comparisons = merge_sort.count
print("Merge Sort comparisions: ", merge_sort.count)
# Creating the semisorted list
third_list = arrayGenerator.randomizer(third_list)
# sorting 100 semisorted list with mergesort
start_time_semisorted = time.perf_counter()
third_list = merge_sort.merge_sort(third_list)
end_time_semisorted = time.perf_counter()
print("Merge Sort time on semisorted array: %s seconds" % (end_time_semisorted - start_time_semisorted))
semisorted_comparisons = merge_sort.count
print("Merge Sort comparisions on semisorted array: ", semisorted_comparisons)
# Writing the Merge Sort data to the file
write_file.write_to_file('Merge Sort', 'O(nlog(n))', 'O(nlog(n))', 100, end_time - start_time, comparisons, end_time_semisorted - start_time_semisorted, semisorted_comparisons)
# sorting 100 list with quicksort
start_time = time.perf_counter()
quickSort.quick_sort(fourth_list)
end_time = time.perf_counter()
print("Quick Sort time: %s seconds " % (end_time - start_time))
comparisons = quickSort.q_count
print("Quick Sort comparisions: ", quickSort.q_count)
# Creating the semisorted list
fourth_list = arrayGenerator.randomizer(fourth_list)
# sorting 100 semisorted list with quicksort
start_time_semisorted = time.perf_counter()
quickSort.quick_sort(fourth_list)
end_time_semisorted = time.perf_counter()
print("Quick Sort time on semisorted array: %s seconds" % (end_time_semisorted - start_time_semisorted))
semisorted_comparisons = quickSort.q_count
print("Quick Sort comparisions on semisorted array: ", semisorted_comparisons)
# Writing the Quick Sort data to the file
write_file.write_to_file('Quick Sort', 'O(n^2)', 'O(nlog(n))', 100, end_time - start_time, comparisons, end_time_semisorted - start_time_semisorted, semisorted_comparisons)
# 1000 list
first_list, second_list, third_list, fourth_list = arrayGenerator.generate_random_list_number(1000)
print("{}, {}, {}, {}".format(len(first_list), len(second_list), len(third_list), len(fourth_list)))
# sorting 1000 list with bubblesort
start_time = time.perf_counter()
first_list, comparisons = bubbleSort.bubble_sort(first_list)
end_time = time.perf_counter()
print("Bubble Sort time: %s seconds" % (end_time - start_time))
print("Bubble Sort comparisions: ", comparisons)
# Creating the semisorted list
first_list = arrayGenerator.randomizer(first_list)
# sorting 1000 semisorted list with bubblesort
start_time_semisorted = time.perf_counter()
first_list, semisorted_comparisons = bubbleSort.bubble_sort(first_list)
end_time_semisorted = time.perf_counter()
print("Bubble Sort time on semisorted array: %s seconds" % (end_time_semisorted - start_time_semisorted))
print("Bubble Sort comparisions on semisorted array: ", semisorted_comparisons)
# Writing the Bubble Sort data to the file
write_file.write_to_file('Bubble Sort', 'O(n^2)', 'O(n)', 1000, end_time - start_time, comparisons, end_time_semisorted - start_time_semisorted, semisorted_comparisons)
# sorting 1000 list with selectionsort
start_time = time.perf_counter()
second_list, comparisons = selectionSort.selection_sort(second_list)
end_time = time.perf_counter()
print("Selection Sort time: %s seconds" % (end_time - start_time))
print("Selection Sort comparisions: ", comparisons)
# Creating the semisorted list
second_list = arrayGenerator.randomizer(second_list)
# sorting 1000 semisorted list with selectionsort
start_time_semisorted = time.perf_counter()
second_list, semisorted_comparisons = selectionSort.selection_sort(first_list)
end_time_semisorted = time.perf_counter()
print("Selection Sort time on semisorted array: %s seconds" % (end_time_semisorted - start_time_semisorted))
print("Selection Sort comparisions on semisorted array: ", semisorted_comparisons)
# Writing the Selection Sort data to the file
write_file.write_to_file('Selection Sort', 'O(n^2)', 'O(n^2)', 1000, end_time - start_time, comparisons, end_time_semisorted - start_time_semisorted, semisorted_comparisons)
# sorting 1000 list with mergesort
start_time = time.perf_counter()
third_list = merge_sort.merge_sort(third_list)
end_time = time.perf_counter()
print("Merge Sort time: %s seconds" % (end_time - start_time))
print("Merge Sort comparisions: ", merge_sort.count)
# Creating the semisorted list
third_list = arrayGenerator.randomizer(third_list)
# sorting 1000 semisorted list with mergesort
start_time_semisorted = time.perf_counter()
third_list = merge_sort.merge_sort(third_list)
end_time_semisorted = time.perf_counter()
print("Merge Sort time on semisorted array: %s seconds" % (end_time_semisorted - start_time_semisorted))
semisorted_comparisons = merge_sort.count
print("Merge Sort comparisions on semisorted array: ", semisorted_comparisons)
# Writing the Merge Sort data to the file
write_file.write_to_file('Merge Sort', 'O(nlog(n))', 'O(nlog(n))', 1000, end_time - start_time, comparisons, end_time_semisorted - start_time_semisorted, semisorted_comparisons)
# sorting 1000 list with quicksort
start_time = time.perf_counter()
quickSort.quick_sort(fourth_list)
end_time = time.perf_counter()
print("Quick Sort time: %s seconds " % (end_time - start_time))
comparisons = quickSort.q_count
print("Quick Sort comparisions: ", quickSort.q_count)
# Creating the semisorted list
fourth_list = arrayGenerator.randomizer(fourth_list)
# sorting 1000 semisorted list with quicksort
start_time_semisorted = time.perf_counter()
quickSort.quick_sort(fourth_list)
end_time_semisorted = time.perf_counter()
print("Quick Sort time on semisorted array: %s seconds" % (end_time_semisorted - start_time_semisorted))
semisorted_comparisons = quickSort.q_count
print("Quick Sort comparisions on semisorted array: ", semisorted_comparisons)
# Writing the Quick Sort data to the file
write_file.write_to_file('Quick Sort', 'O(n^2)', 'O(nlog(n))', 1000, end_time - start_time, comparisons, end_time_semisorted - start_time_semisorted, semisorted_comparisons)
# 10000 list
first_list, second_list, third_list, fourth_list = arrayGenerator.generate_random_list_number(10000)
print("{}, {}, {}, {}".format(len(first_list), len(second_list), len(third_list), len(fourth_list)))
# sorting 10000 list with bubblesort
start_time = time.perf_counter()
first_list, comparisons = bubbleSort.bubble_sort(first_list)
end_time = time.perf_counter()
print("Bubble Sort time: %s seconds" % (end_time - start_time))
print("Bubble Sort comparisions: ", comparisons)
# Creating the semisorted list
first_list = arrayGenerator.randomizer(first_list)
# sorting 10000 semisorted list with bubblesort
start_time_semisorted = time.perf_counter()
first_list, semisorted_comparisons = bubbleSort.bubble_sort(first_list)
end_time_semisorted = time.perf_counter()
print("Bubble Sort time on semisorted array: %s seconds" % (end_time_semisorted - start_time_semisorted))
print("Bubble Sort comparisions on semisorted array: ", semisorted_comparisons)
# Writing the Bubble Sort data to the file
write_file.write_to_file('Bubble Sort', 'O(n^2)', 'O(n)', 10000, end_time - start_time, comparisons, end_time_semisorted - start_time_semisorted, semisorted_comparisons)
# sorting 10000 list with selectionsort
start_time = time.perf_counter()
second_list, comparisons = selectionSort.selection_sort(second_list)
end_time = time.perf_counter()
print("Selection Sort time: %s seconds" % (end_time - start_time))
print("Selection Sort comparisions: ", comparisons)
# Creating the semisorted list
second_list = arrayGenerator.randomizer(second_list)
# sorting 10000 semisorted list with selectionsort
start_time_semisorted = time.perf_counter()
second_list, semisorted_comparisons = selectionSort.selection_sort(first_list)
end_time_semisorted = time.perf_counter()
print("Selection Sort time on semisorted array: %s seconds" % (end_time_semisorted - start_time_semisorted))
print("Selection Sort comparisions on semisorted array: ", semisorted_comparisons)
# Writing the Selection Sort data to the file
write_file.write_to_file('Selection Sort', 'O(n^2)', 'O(n^2)', 10000, end_time - start_time, comparisons, end_time_semisorted - start_time_semisorted, semisorted_comparisons)
# sorting 10000 list with mergesort
start_time = time.perf_counter()
third_list = merge_sort.merge_sort(third_list)
end_time = time.perf_counter()
print("Merge Sort time: %s seconds" % (end_time - start_time))
print("Merge Sort comparisions: ", merge_sort.count)
# Creating the semisorted list
third_list = arrayGenerator.randomizer(third_list)
# sorting 10000 semisorted list with mergesort
start_time_semisorted = time.perf_counter()
third_list = merge_sort.merge_sort(third_list)
end_time_semisorted = time.perf_counter()
print("Merge Sort time on semisorted array: %s seconds" % (end_time_semisorted - start_time_semisorted))
semisorted_comparisons = merge_sort.count
print("Merge Sort comparisions on semisorted array: ", semisorted_comparisons)
# Writing the Merge Sort data to the file
write_file.write_to_file('Merge Sort', 'O(nlog(n))', 'O(nlog(n))', 10000, end_time - start_time, comparisons, end_time_semisorted - start_time_semisorted, semisorted_comparisons)
# sorting 10000 list with quicksort
start_time = time.perf_counter()
quickSort.quick_sort(fourth_list)
end_time = time.perf_counter()
print("Quick Sort time: %s seconds " % (end_time - start_time))
comparisons = quickSort.q_count
print("Quick Sort comparisions: ", quickSort.q_count)
# Creating the semisorted list
fourth_list = arrayGenerator.randomizer(fourth_list)
# sorting 10000 semisorted list with quicksort
start_time_semisorted = time.perf_counter()
quickSort.quick_sort(fourth_list)
end_time_semisorted = time.perf_counter()
print("Quick Sort time on semisorted array: %s seconds" % (end_time_semisorted - start_time_semisorted))
semisorted_comparisons = quickSort.q_count
print("Quick Sort comparisions on semisorted array: ", semisorted_comparisons)
# Writing the Quick Sort data to the file
write_file.write_to_file('Quick Sort', 'O(n^2)', 'O(nlog(n))', 10000, end_time - start_time, comparisons, end_time_semisorted - start_time_semisorted, semisorted_comparisons)
write_file.close()
return bit_search(list, value, middle + 1, high)
elif list[middle] > value:
return bit_search(list, value, low, middle - 1)
else:
return middle
def bit_search_by_loop(list, value, low, high):
if low > high:
return -1
while (True):
middle = (low + high) / 2
if (list[middle] < value):
low = middle + 1
elif (list[middle] > value):
high = middle - 1
else:
return middle
if __name__ == '__main__':
lis = [
3, 987, 6, 22, 9, 333, 22, 44, 9999, 555, 999, 1234, 1235, 1255, 1288
]
val = 1235
sortList = quick_sort(lis)
ret = bit_search_by_loop(sortList, val, 0, len(lis))
print sortList
print ret, lis[ret]
