Sorting objects using In-Place sorting algorithm
Last Updated :
01 Sep, 2022
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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++ 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;
}
// C++ implementation of the approachusing namespace std;// Partition function which will partition// the array and into two partsint 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 algorithmvoid 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 objectsvoid 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 codeint main(){ // Let's represent objects as strings vector<string> objects{ "red", "blue", "red", "yellow", "blue" }; sortObj(objects); return 0;}// 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
# 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 print the 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
// 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
<script>
// Javascript implementation of the approach
// Partition function which will partition
// the array and into two parts
function partition(objects, l, r, hash)
{
let j = l - 1;
let last_element = hash.get(objects[r]);
for (let i = l; i < r; i++)
{
// Compare hash values of objects
if (hash.get(objects[i]) <= last_element)
{
j++;
let temp = objects[i];
objects[i] = objects[j];
objects[j] = temp;
}
}
j++;
let temp = objects[r];
objects[r] = objects[j];
objects[j] = temp;
return j;
}
// Classic quicksort algorithm
function quicksort(objects, l, r, hash)
{
if (l < r)
{
let 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
function sortObj(objects)
{
// Create a hash table
let hash = new Map();
// As the sorting order is blue objects,
// red objects and then yellow objects
hash. set("blue", 1);
hash. set("red", 2);
hash. set("yellow", 3);
// Quick sort function
quicksort(objects, 0, objects.length - 1, hash);
// Printing the sorted array
for (let i = 0; i < objects.length; i++)
document.write(objects[i] + " ");
}
// Driver code
let objects = ["red", "blue","red", "yellow", "blue"];
sortObj(objects);
// This code is contributed by patel2127
</script>
Output:
blue blue red red yellow
Time complexity: O(n^2) since using quicksort
Auxiliary space: O(n) because using hash table
