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How to visualize selection and insertion sort using Tkinter in Python?

  • Last Updated : 19 Dec, 2021

In this article, we are going to create a GUI application that will make us visualize and understand two of the most popular sorting algorithms better, using Tkinter module.  Those two sorting algorithms are selection sort and insertion sort.  

Selection sort and Insertion sort are the two most popular algorithms. Selection sort is a comparison-based algorithm. One advantage of selection sort is, it does less memory writes with respect to other algorithms. Selection sort is an in-place algorithm therefore we do not require any extra space. Time complexity is O(n2). Insertion sort is also an in-place sorting algorithm like selection sort.

Approach

  • Import the required modules.
  • Create a dictionary that will keep the record of which algorithm is selected by the user.
algos = { ‘insertion’: False, ‘selection’: False}  
  • Define a display() function that will display the arrays as horizontal bars. The array will contain the height of each bar.
  • Shuffle() function to shuffle the array.
  • Create a canvas and four buttons, one to select the insertion sort, one to select the selection sort, another to start the visualizer or the sorting visualization process, and last to shuffle the array.
  • selection() function to change the algos dictionary and mark “selection” as True and “insertion” as False if it is True.
  • insertion() function to change the algos dictionary and mark “insertion” as True and “selection” as False if it is True.
  • Slide function is added to give users the liberty of controlling the speed and size of the array with the Tkinter GUI slider.
  • Finally, the start() function. This is the main function that will be triggered upon clicking the “Start Sorting” Button.

First, check which key value in the dictionary algos, is TRUE. Since we have already written the two functions selection() and insertion() such that anyone algorithm can be selected at a time. So the key whose corresponding value is True will be displayed on the screen. 

In selection sort, the idea is to select the minimum element from the array of concern and swap it with the last element of the sorted array in the front. 

 Algorithm:

  • Run a for loop till N-1. Then inside that for loop, use another loop, this will iterate through the array of concerns and find the minimum element. To find the minimum element in an array one has to travel the entire array at least once.
  • To find the minimum element we will maintain a min_index variable to track the index of the minimum element. Then after one complete iteration, we will swap the two elements and update the display screen by calling the display() function.
  • In the case of Insertion sort, the idea is to insert the current element at concern into its correct position in the given array. Again we will check the algos dictionary and if the value corresponding to “insertion” is true then the insertion sorting algorithm will be displayed.
  • Assuming that you already know the algorithm of insertion sort, understanding the idea behind insertion sort visualization is simple.  The algorithm consists of two loops, one is for loop to iterate through the array and another is a while loop that will help us to swap the element at focus to its correct position. We will simply call the display() function after each iteration to show the updated array and also call the display() from inside the while loop to show the element at focus changing its position. The code below will help you to understand it better.

Below is the implementation:

Python3




from tkinter import *
from tkinter import ttk, messagebox
from ttkbootstrap import *
import numpy as np
import time
  
N = 50
speed = 100
array = np.linspace(10, 390, N, dtype=np.uint16)
  
#  this is the display function to display the arrays
#  as bars on the screen
  
def display(n, array, color):
    
  
    __canvas.delete('all')
  
    width = 1560/(3*n-1)
    gap = width/2
  
    for i in range(n):
        __canvas.create_rectangle(7+i*width+i*gap, 0, 7 +
                                  (i+1)*width+i*gap, array[i],
                                  fill=color[i])
  
    root.update_idletasks()
      
  
def shuffle():
    
    # to shuffle the array
    np.random.shuffle(array)
    display(N, array, colors)
  
  
def start():
    if algos['selection'] == True:
        
        # sorting algorithm for selection sort
        for i in range(len(array)-1):
            min_index = i
            for j in range(i+1, len(array)):
                display(N, array, ['yellow' if a == min_index or a ==
                                   i else 'green' if
                                   a <= i else 'cyan'
                                   for a in range(N)])
                  
                time.sleep(1/speed)
                if array[min_index] > array[j]:
                    display(N, array, ['red' if a == min_index or a ==
                                       j else 'green' if 
                                       a <= i else 'cyan'
                                       for a in range(N)])
                      
                    time.sleep(1/speed)
                    min_index = j
            if min_index != i:
                array[i], array[min_index] = array[min_index],
                array[i]
                  
                display(N, array, ['pink' 
                                   if a == min_index or a ==
                                   i else 'green' if a <=
                                   else 'cyan' for a in range(N)])
                  
                time.sleep(1/speed)
        display(N, array, ['yellow' for _ in range(N)])
  
    elif algos['insertion'] == True:
        
        # sorting algorithm for insertion sort
        for j in range(1, len(array)):
            key = array[j]
            i = j-1
            display(N, array, ['yellow' if a == i or a == i +
                               1 else 'green' if a <= j
                               else'cyan' for a in range(N)])
            time.sleep(1/speed)
            while i >= 0 and array[i] > key:
                array[i+1] = array[i]
                display(N, array, [
                        'pink' if a == i else 'green' if a <=
                  else'cyan' for a in range(N)])
                time.sleep(1/speed)
                i -= 1
            array[i+1] = key
        display(N, array, ['yellow' for _ in range(N)])
  
    else:
        
        # to show an error message if
        # the user clicked the start
        # button without selecting any sorting algorithm
        messagebox.showerror("Algorithm Visualizer",
                             "You need to select a sorting algorithm")
  
  
def slide():
    
    # this function will change
    # the length of the array
    # this will modify the speed and
    # number of elements in real time
    global speed
    global N
    global array
    N = int(_scale.get()/20)
    array = np.linspace(5, 400, N, dtype=np.uint16)
    speed = int(_scale.get())
      
    # shuffle method is called to display the new array
    shuffle()
      
      
  
# this method will select selection sort
# and unselect insertion sort
def selection():
  
    if algos['selection'] is False:
        algos['selection'] = True
        __selec.config(style='success.TButton')
  
        algos['insertion'] = False
        __in.config(style='danger.TButton')
  
    else:
        algos['selection'] = False
        __selec.config(style='danger.TButton')
  
# this method will select the insertion sort
# and unselect the selection sort
def insertion():
  
    if algos['insertion'] is False:
        algos['insertion'] = True
        __in.config(style='success.TButton')
        algos['selection'] = False
        __selec.config(style='danger.TButton')
  
    else:
        algos['insertion'] = False
        __in.config(style='danger.TButton')
  
  
if __name__ == '__main__':
  
    # superheor is a theme that comes with the
    # ttkbootstrap package
    root = Style(theme='superhero').master
  
    # a dictionary to mark the sorting algorithm TRUE
    # when selected
    algos = {'insertion': False, 'selection': False}
  
    root.title('Sorting visualizer')
    root.resizable(0, 0)
      
    # this is to fix the dimension of the window
    Label(root, text='Selection and insertion sort visualization'
         ).grid(row=0,column=0, columnspan=8)
  
    # below are buttons to select the cyan sorting algorithm
  
    __in = ttk.Button(root, text='Insertion sort', width=16,
                      padding=5, command=insertion)
    __in.grid(row=1, column=0, pady=20)
    __selec = ttk.Button(root, text='Selection sort',
                         width=16, padding=5, command=selection)
    __selec.grid(row=1, column=1, pady=20)
    __start = ttk.Button(root, text='Start Sorting',
                         width=16, padding=5, command=start)
    __start.grid(row=1, column=2, pady=20)
    __shuffle = ttk.Button(root, text='Shuffle Array',
                           width=16, padding=5, command=shuffle)
    __shuffle.grid(row=1, column=3, pady=20)
  
    # this will provide the user the ability
    # to change the size of the array
    _scale = ttk.Scale(root, from_=50, to=1000
                       length=250, value=1000,
                       command=lambda x: slide())
    _scale.grid(row=1, column=4, columnspan=4, padx=5)
  
    # to color the array bars
    colors = ['cyan' for _ in range(N)]
      
  
    __canvas = Canvas(root, width=800, height=400)
    __canvas.grid(row=2, column=0, columnspan=8)
  
    shuffle()
    display(N, array, colors)
  
    root.mainloop()

Output:


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