Add the quicksort algorithm to this python code. Below is the code to modify # selectionsortanimation.py """Animated selection sort visualization.""" from matplotlib import animation import matplotlib.pyplot as plt import numpy as np import seaborn as sns import sys
Add the quicksort
# selectionsortanimation.py
"""Animated selection sort visualization."""
from matplotlib import animation
import matplotlib.pyplot as plt
import numpy as np
import seaborn as sns
import sys
#from ch11soundutilities import play_sound
def update(frame_data):
"""Display bars representing the current state."""
# unpack info for graph update
data, colors, swaps, comparisons = frame_data
plt.cla() # clear old contents of current Figure
# create barplot and set its xlabel
bar_positions = np.arange(len(data))
axes = sns.barplot(bar_positions, data, palette=colors) # new bars
axes.set(xlabel=f'Comparisons: {comparisons}; Swaps: {swaps}',
xticklabels=data)
def flash_bars(index1, index2, data, colors, swaps, comparisons):
"""Flash the bars about to be swapped and play their notes."""
for x in range(0, 2):
colors[index1], colors[index2] = 'white', 'white'
yield (data, colors, swaps, comparisons)
colors[index1], colors[index2] = 'purple', 'purple'
yield (data, colors, swaps, comparisons)
#play_sound(data[index1], seconds=0.05)
#play_sound(data[index2], seconds=0.05)
def selection_sort(data):
"""Sort data using the selection sort algorithm and
yields values that update uses to visualize the algorithm."""
swaps = 0
comparisons = 0
colors = ['lightgray'] * len(data) # list of bar colors
# display initial bars representing shuffled values
yield (data, colors, swaps, comparisons)
# loop over len(data) - 1 elements
for index1 in range(0, len(data) - 1):
smallest = index1
# loop to find index of smallest element's index
for index2 in range(index1 + 1, len(data)):
comparisons += 1
colors[smallest] = 'purple'
colors[index2] = 'red'
yield (data, colors, swaps, comparisons)
#play_sound(data[index2], seconds=0.05)
# compare elements at positions index and smallest
if data[index2] < data[smallest]:
colors[smallest] = 'lightgray'
smallest = index2
colors[smallest] = 'purple'
yield (data, colors, swaps, comparisons)
else:
colors[index2] = 'lightgray'
yield (data, colors, swaps, comparisons)
# ensure that last bar is not purple
colors[-1] = 'lightgray'
# flash the bars about to be swapped
yield from flash_bars(index1, smallest, data, colors,
swaps, comparisons)
# swap the elements at positions index1 and smallest
swaps += 1
data[smallest], data[index1] = data[index1], data[smallest]
# flash the bars that were just swapped
yield from flash_bars(index1, smallest, data, colors,
swaps, comparisons)
# indicate that bar index1 is now in its final spot
colors[index1] = 'lightgreen'
yield (data, colors, swaps, comparisons)
# indicate that last bar is now in its final spot
colors[-1] = 'lightgreen'
yield (data, colors, swaps, comparisons)
#play_sound(data[-1], seconds=0.05)
# play each bar's note once and color it darker green
for index in range(len(data)):
colors[index] = 'green'
yield (data, colors, swaps, comparisons)
#play_sound(data[index], seconds=0.05)
def main():
number_of_values = int(sys.argv[1]) if len(sys.argv) == 2 else 10
figure = plt.figure('Selection Sort') # Figure to display barplot
numbers = np.arange(1, number_of_values + 1) # create array
np.random.shuffle(numbers) # shuffle the array
# start the animation
anim = animation.FuncAnimation(figure, update, repeat=False,
frames=selection_sort(numbers), interval=50)
plt.show() # display the Figure
# call main if this file is executed as a script
if __name__ == '__main__':
main()
Example of the quick sore algoritim is below
class QuickSort:
# sort the array in it is location in the memory .
@classmethod
# l > low, h > high
def quickSort(cls,array,l,h):
if l < h :
pi =cls.qsort_helper(array, l, h)
# sort the smaller part
cls.quickSort(array, l, pi - 1)
# sort the greater part
cls.quickSort(array, pi + 1, h)
@classmethod
def qsort_helper(cls,array,l,h):
p = array[h]
# print(p)
low = l - 1
# i > poiter for greater element
for j in range(l, h):
# find the smaller element of the pivot, if found swap it with the low element
if array[j] < p :
low += 1
(array[low], array[j]) = (array[j], array[low])
(array[low + 1], array[h]) = (array[h], array[low + 1])
return low + 1
def main ():
array = [5, 8, 5,4, 6, 978, 9, 0, 47, 0, 4, 9]
QuickSort.quickSort(array, 0, len(array) - 1)
print(array)
main()
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Is there a way you can put the output of the code? And also indent the code.
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