Given an array and a value, find if there is a triplet in array whose sum is equal to the given value. If there is such a triplet present in array, then print the triplet and return true. Else return false.
Examples:
Input: array = {12, 3, 4, 1, 6, 9}, sum = 24;
Output: 12, 3, 9
Explanation: There is a triplet (12, 3 and 9) present
in the array whose sum is 24.
Input: array = {1, 2, 3, 4, 5}, sum = 9
Output: 5, 3, 1
Explanation: There is a triplet (5, 3 and 1) present
in the array whose sum is 9.
Method 1: This is the naive approach towards solving the above problem.
- Approach: A simple method is to generate all possible triplets and compare the sum of every triplet with the given value. The following code implements this simple method using three nested loops.
- Algorithm:
- Given an array of length n and a sum s
- Create three nested loop first loop runs from start to end (loop counter i), second loop runs from i+1 to end (loop counter j) and third loop runs from j+1 to end (loop counter k)
- The counter of these loops represents the index of 3 elements of the triplets.
- Find the sum of ith, jth and kth element. If the sum is equal to given sum. Print the triplet and break.
- If there is no triplet, then print that no triplet exist.
- Implementation:
# Python3 program to find a triplet
# that sum to a given value
# returns true if there is triplet with
# sum equal to 'sum' present in A[].
# Also, prints the triplet
def find3Numbers(A, arr_size, sum):
# Fix the first element as A[i]
for i in range( 0, arr_size-2):
# Fix the second element as A[j]
for j in range(i + 1, arr_size-1):
# Now look for the third number
for k in range(j + 1, arr_size):
if A[i] + A[j] + A[k] == sum:
print("Triplet is", A[i],
", ", A[j], ", ", A[k])
return True
# If we reach here, then no
# triplet was found
return False
# Driver program to test above function
A = [1, 4, 45, 6, 10, 8]
sum = 22
arr_size = len(A)
find3Numbers(A, arr_size, sum)
# This code is contributed by Smitha Dinesh Semwal
Output
Triplet is 4, 10, 8
- Complexity Analysis:
- Time Complexity: O(n3).
There are three nested loops traversing the array, so the time complexity is O(n^3) - Space Complexity: O(1).
As no extra space is required.
- Time Complexity: O(n3).
Method 2: This method uses sorting to increase the efficiency of the code.
- Approach: By Sorting the array the efficiency of the algorithm can be improved. This efficient approach uses the two-pointer technique. Traverse the array and fix the first element of the triplet. Now use the Two Pointers algorithm to find if there is a pair whose sum is equal to x – array[i]. Two pointers algorithm take linear time so it is better than a nested loop.
- Algorithm :
- Sort the given array.
- Loop over the array and fix the first element of the possible triplet, arr[i].
- Then fix two pointers, one at i + 1 and the other at n – 1. And look at the sum,
- If the sum is smaller than the required sum, increment the first pointer.
- Else, If the sum is bigger, Decrease the end pointer to reduce the sum.
- Else, if the sum of elements at two-pointer is equal to given sum then print the triplet and break.
- Implementation:
# Python3 program to find a triplet
# returns true if there is triplet
# with sum equal to 'sum' present
# in A[]. Also, prints the triplet
def find3Numbers(A, arr_size, sum):
# Sort the elements
A.sort()
# Now fix the first element
# one by one and find the
# other two elements
for i in range(0, arr_size-2):
# To find the other two elements,
# start two index variables from
# two corners of the array and
# move them toward each other
# index of the first element
# in the remaining elements
l = i + 1
# index of the last element
r = arr_size-1
while (l < r):
if( A[i] + A[l] + A[r] == sum):
print("Triplet is", A[i],
', ', A[l], ', ', A[r]);
return True
elif (A[i] + A[l] + A[r] < sum):
l += 1
else: # A[i] + A[l] + A[r] > sum
r -= 1
# If we reach here, then
# no triplet was found
return False
# Driver program to test above function
A = [1, 4, 45, 6, 10, 8]
sum = 22
arr_size = len(A)
find3Numbers(A, arr_size, sum)
# This is contributed by Smitha Dinesh Semwal
Output
Triplet is 4, 8, 10
- Complexity Analysis:
- Time complexity: O(N^2).
There are only two nested loops traversing the array, so time complexity is O(n^2). Two pointers algorithm takes O(n) time and the first element can be fixed using another nested traversal. - Space Complexity: O(1).
As no extra space is required.
- Time complexity: O(N^2).
Method 3: This is a Hashing-based solution.
- Approach: This approach uses extra space but is simpler than the two-pointers approach. Run two loops outer loop from start to end and inner loop from i+1 to end. Create a hashmap or set to store the elements in between i+1 to j-1. So if the given sum is x, check if there is a number in the set which is equal to x - arr[i] - arr[j]. If yes print the triplet.
- Algorithm:
- Traverse the array from start to end. (loop counter i)
- Create a HashMap or set to store unique pairs.
- Run another loop from i+1 to end of the array. (loop counter j)
- If there is an element in the set which is equal to x- arr[i] - arr[j], then print the triplet (arr[i], arr[j], x-arr[i]-arr[j]) and break
- Insert the jth element in the set.
- Implementation:
# Python3 program to find a triplet using Hashing
# returns true if there is triplet with sum equal
# to 'sum' present in A[]. Also, prints the triplet
def find3Numbers(A, arr_size, sum):
for i in range(0, arr_size-1):
# Find pair in subarray A[i + 1..n-1]
# with sum equal to sum - A[i]
s = set()
curr_sum = sum - A[i]
for j in range(i + 1, arr_size):
if (curr_sum - A[j]) in s:
print("Triplet is", A[i],
", ", A[j], ", ", curr_sum-A[j])
return True
s.add(A[j])
return False
# Driver program to test above function
A = [1, 4, 45, 6, 10, 8]
sum = 22
arr_size = len(A)
find3Numbers(A, arr_size, sum)
# This is contributed by Yatin gupta
Output:
Triplet is 4, 8, 10Time complexity: O(N^2)
Auxiliary Space: O(N)
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Find a triplet that sum to a given valuefor more details!