Sorting objects using In-Place sorting algorithm

Given an array of red, blue and yellow objects, the task is to use an in-place sorting algorithm to sort the array in such a way that all the blue objects appear before all the red objects and all the red objects appear before all the yellow objects.

Examples:

Input: arr[] = {“blue”, “red”, “yellow”, “blue”, “yellow”}
Output: blue blue red yellow yellow



Input: arr[] = {“red”, “blue”, “red”, “yellow”, “blue”}
Output: blue blue red red yellow

Approach: First of all map the values of blue, red and yellow objects to 1, 2 and 3 respectively using a hash table. Now use these mapped values whenever a comparison of two objects is required. So, the algorithm will sort the array of objects such that all blue objects ( mapping to value 1 ) will appear first, then all red objects ( mapping to value 2 ) and then all yellow objects ( mapping to value 3 ).

Below is the implementation of the above approach:

C++

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// C++ implementation of the approach
#include <bits/stdc++.h>
using namespace std;
  
// Partition function which will partition
// the array and into two parts
int partition(vector<string>& objects, int l, int r,
            unordered_map<string, int>& hash)
{
    int j = l - 1;
  
    int last_element = hash[objects[r]];
  
    for (int i = l; i < r; i++) {
  
        // Compare hash values of objects
        if (hash[objects[i]] <= last_element) {
            j++;
            swap(objects[i], objects[j]);
        }
    }
  
    j++;
  
    swap(objects[j], objects[r]);
  
    return j;
}
  
// Classic quicksort algorithm
void quicksort(vector<string>& objects, int l, int r, 
                    unordered_map<string, int>& hash)
{
    if (l < r) {
        int mid = partition(objects, l, r, hash);
        quicksort(objects, l, mid - 1, hash);
        quicksort(objects, mid + 1, r, hash);
    }
}
  
// Function to sort and print the objects
void sortObj(vector<string>& objects)
{
  
    // Create a hash table
    unordered_map<string, int> hash;
  
    // As the sorting order is blue objects,
    // red objects and then yellow objects
    hash["blue"] = 1;
    hash["red"] = 2;
    hash["yellow"] = 3;
  
    // Quick sort function
    quicksort(objects, 0, int(objects.size() - 1), hash);
  
    // Printing the sorted array
    for (int i = 0; i < objects.size(); i++)
        cout << objects[i] << " ";
}
  
// Driver code
int main()
{
  
    // Let's represent objects as strings
    vector<string> objects{ "red", "blue",
                            "red", "yellow", "blue" };
  
    sortObj(objects);
  
    return 0;
}

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Java

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// Java implementation of the approach
import java.util.*;
class GFG 
{
  
// Partition function which will partition
// the array and into two parts
static int partition(Vector<String> objects, int l, int r,
                        Map<String, Integer> hash)
{
    int j = l - 1;
  
    int last_element = hash.get(objects.get(r));
  
    for (int i = l; i < r; i++) 
    {
  
        // Compare hash values of objects
        if (hash.get(objects.get(i)) <= last_element) 
        {
            j++;
            Collections.swap(objects, i, j);
        }
    }
  
    j++;
  
    Collections.swap(objects, j, r);
  
    return j;
}
  
// Classic quicksort algorithm
static void quicksort(Vector<String> objects, int l, int r,
                         Map<String, Integer> hash)
{
    if (l < r)
    {
        int mid = partition(objects, l, r, hash);
        quicksort(objects, l, mid - 1, hash);
        quicksort(objects, mid + 1, r, hash);
    }
}
  
// Function to sort and print the objects
static void sortObj(Vector<String> objects)
{
  
    // Create a hash table
    Map<String, Integer> hash = new HashMap<>();
  
    // As the sorting order is blue objects,
    // red objects and then yellow objects
    hash. put("blue", 1);
    hash. put("red", 2);
    hash. put("yellow", 3);
  
    // Quick sort function
    quicksort(objects, 0, objects.size() - 1, hash);
  
    // Printing the sorted array
    for (int i = 0; i < objects.size(); i++)
        System.out.print(objects.get(i) + " ");
}
  
// Driver code
public static void main(String []args)
{
    // Let's represent objects as strings
    Vector<String> objects = new Vector<>(Arrays.asList( "red", "blue",
                                                         "red", "yellow"
                                                         "blue" ));
  
    sortObj(objects);
}
}
  
// This code is contributed by PrinciRaj1992

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Python3

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# Python3 implementation of the approach
  
# Partition function which will partition
# the array and into two parts
objects = []
hash = dict()
  
def partition(l, r):
    global objects, hash
    j = l - 1
  
    last_element = hash[objects[r]]
  
    for i in range(l, r):
  
        # Compare hash values of objects
        if (hash[objects[i]] <= last_element):
            j += 1
            (objects[i], 
             objects[j]) = (objects[j], 
                            objects[i])
  
    j += 1
  
    (objects[j], 
     objects[r]) = (objects[r], 
                    objects[j])
  
    return j
  
# Classic quicksort algorithm
def quicksort(l, r):
    if (l < r):
        mid = partition(l, r)
        quicksort(l, mid - 1)
        quicksort(mid + 1, r)
  
# Function to sort and prthe objects
def sortObj():
    global objects, hash
  
    # As the sorting order is blue objects,
    # red objects and then yellow objects
    hash["blue"] = 1
    hash["red"] = 2
    hash["yellow"] = 3
  
    # Quick sort function
    quicksort(0, int(len(objects) - 1))
  
    # Printing the sorted array
    for i in objects:
        print(i, end = " ")
  
# Driver code
  
# Let's represent objects as strings
objects = ["red", "blue", "red"
               "yellow", "blue"]
  
sortObj()
  
# This code is contributed 
# by Mohit Kumar

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C#

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// C# implementation of the approach
using System;
using System.Collections.Generic;
  
class GFG 
{
  
// Partition function which will partition
// the array and into two parts
static int partition(List<String> objects, int l, int r,
                           Dictionary<String, int> hash)
{
    int j = l - 1;
    String temp;
    int last_element = hash[objects[r]];
  
    for (int i = l; i < r; i++) 
    {
  
        // Compare hash values of objects
        if (hash[objects[i]] <= last_element) 
        {
            j++;
            temp = objects[i];
            objects[i] = objects[j];
            objects[j] = temp;
        }
    }
  
    j++;
  
    temp = objects[r];
    objects[r] = objects[j];
    objects[j] = temp;
  
    return j;
}
  
// Classic quicksort algorithm
static void quicksort(List<String> objects, int l, int r,
                            Dictionary<String, int> hash)
{
    if (l < r)
    {
        int mid = partition(objects, l, r, hash);
        quicksort(objects, l, mid - 1, hash);
        quicksort(objects, mid + 1, r, hash);
    }
}
  
// Function to sort and print the objects
static void sortObj(List<String> objects)
{
  
    // Create a hash table
    Dictionary<String, 
               int> hash = new Dictionary<String, 
                                          int>();
  
    // As the sorting order is blue objects,
    // red objects and then yellow objects
    hash.Add("blue", 1);
    hash.Add("red", 2);
    hash.Add("yellow", 3);
  
    // Quick sort function
    quicksort(objects, 0, objects.Count - 1, hash);
  
    // Printing the sorted array
    for (int i = 0; i < objects.Count; i++)
        Console.Write(objects[i] + " ");
}
  
// Driver code
public static void Main(String []args)
{
    // Let's represent objects as strings
    List<String> objects = new List<String>{"red", "blue",
                                            "red", "yellow"
                                            "blue"};
  
    sortObj(objects);
}
}
  
// This code is contributed by Rajput-Ji

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Output:

blue blue red red yellow


My Personal Notes arrow_drop_up

I am doing BTech at Dhirubhai Ambani Institute of Information and Communication Technology

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