def list_test(): s = [11, 33, 22, 55, 44] for v in s: print(v) a = 1 b = 3 print(s[a:b]) print(s.sort()) print(str(s)) print('bubble_sort: ', bubble_sort.sort(s)) print('quick_sort: ', quick_sort.sort(s)) xx = [x * x for x in range(10)] print(xx)
def srt_operations(f_code, v): if f_code == 1: res = bogo_sort.sort(v) return res elif f_code == 2: res = bubble_sort.sort(v) return res elif f_code == 3: res = cocktail_sort.sort(v) return res elif f_code == 4: res = comb_sort.sort(v) return res elif f_code == 5: res = gnome_sort.sort(v) return res elif f_code == 6: res = heap_sort.sort(v) return res elif f_code == 7: res = insertion_sort.sort(v) return res elif f_code == 8: res = merge_sort.sort(v) return res elif f_code == 9: res = quick_sort.sort(v) return res elif f_code == 10: res = quick_sort_in_place.sort(v, 0, len(v) - 1) return res elif f_code == 11: res = selection_sort.sort(v) return res elif f_code == 12: res = shell_sort.sort(v) return res
def noise_removal(DDSM): for i in (DDSM): ds = pydicom.dcmread(i) # initialize the y part of the pixel in the array y = 0 # initialize x x = 0 # size of image pixels = ds.pixel_array.shape[0] * ds.pixel_array.shape[1] for pixel in range(pixels): # define the pixel we're looking at """ n = ds.pixel_array[y , x] n_up = ds.pixel_array[y - 1, x] n_upl = ds.pixel_array[y - 1, x - 1] n_l = ds.pixel_array[y, x - 1] n_downl = ds.pixel_array[y + 1, x - 1] n_down = ds.pixel_array[y + 1, x] n_downr = ds.pixel_array[y + 1, x + 1] n_r = ds.pixel_array[y, x + 1] n_upr = ds.pixel_array[y - 1, x + 1] window = [n, n_up, n_upr, n_upl, n_l, n_downl, n_down, n_downr, n_r] """ window = pectoral_muscle.neighbors(y, x, ds.pixel_array) # sorting window = quick_sort.sort(window) # set value to pixel\ ds.pixel_array[y, x] = ds.pixel_array[window[len(window) / 2][0], window[len(window) / 2][1]] if x == ds.pixel_array.shape[1] - 1: y = y + 1 x = 0 continue x += 1 # print("done with iteration " + str(pixel) +" for median noise") ds.PixelData = ds.pixel_array.tostring() ds.save_as(i)
def test_quicksort(self): self.output = quick_sort.sort(self.input) self.assertEqual(self.correct, self.output)
test_list2 = [] quick_times = [] test_size = [1, 10, 100, 1000] test_size2 = [1000, 2000, 3000, 4000] for size in test_size: for x in range(0, size): new_val = random.randint(math.pow(10, 4), math.pow(10, 5)) test_list.append(new_val) #QUICK SORT start = time.clock() quick_sort.sort(test_list) end = time.clock() result_quick = end - start quick_times.append(result_quick) plot = [] for i in range(0, len(quick_times)): plot.append(i) plt.title('Analisis Experimental') plt.plot(test_size2, quick_times) plt.ylabel('Tiempo (s)') plt.xlabel('Tamano (10^n)') plt.legend(['quick sort'], loc='upper left') plt.show()
def test_quick_sort_iterative(self, array): assert not is_sorted(array) quick_sort.sort(array) assert is_sorted(array)
def test_quick_sort_recursive(self, array): assert not is_sorted(array) quick_sort.sort(array, iterative=False) assert is_sorted(array)
countingSort(arr,exp) exp *= 10 r = list() q = list() for i in range(1,6): test=list(range(pow(10,i))) for x in range(0,pow(10,i)): test[x]=randint(pow(10,i-1), pow(10,i)) print(test) start = time.clock() quick_sort.sort(test) end = time.clock() print ("quick: ") print (end - start) q.append(end-start) start = time.clock() radixSort(test) end = time.clock() print ("radix: ") print (end - start) r.append(end-start) print("r: "), print(r) print("q: "),
def quick_time(test_list): start = time.clock() quick_sort.sort(test_list) end = time.clock() result = end - start return result