Find element position in given monotonic sequence
Last Updated :
26 Feb, 2023
Given an integer k and a monotonic increasing sequence:
f(n) = an + bn [log2(n)] + cn^3 where (a = 1, 2, 3, ...), (b = 1, 2, 3, ...), (c = 0, 1, 2, 3, ...)
Here, [log2(n)] means, taking the log to the base 2 and round the value down Thus,
if n = 1, the value is 0.
if n = 2-3, the value is 1.
if n = 4-7, the value is 2.
if n = 8-15, the value is 3.
The task is to find the value n such that f(n) = k, if k doesn't belong to the sequence then print 0.
Note: Values are in such a way that they can be expressed in 64 bits and the three integers a, b and c do not exceed 100.
Examples:
Input: a = 2, b = 1, c = 1, k = 12168587437017
Output: 23001
f(23001) = 12168587437017
Input: a = 7, b = 3, c = 0, k = 119753085330
Output: 1234567890
Naive Approach: Given values of a, b, c, find values of f(n) for every value of n and compare it.
Time Complexity: O(n)
Space Complexity: O(1)
Efficient Approach: Use Binary Search, choose n = (min + max) / 2 where min and max are the minimum and maximum values possible for n then,
- If f(n) < k then increment n.
- If f(n) > k then decrement n.
- If f(n) = k then n is the required answer.
- Repeat the above steps until the required value is found or it is not possible in the sequence.
Below is the implementation of the above approach:
C++
// C++ implementation of the approach
#include <iostream>
#include <math.h>
#define SMALL_N 1000000
#define LARGE_N 1000000000000000
using namespace std;
// Function to return the value of f(n) for given values of a, b, c, n
long long func(long long a, long long b, long long c, long long n)
{
long long res = a * n;
long long logVlaue = floor(log2(n));
res += b * n * logVlaue;
res += c * (n * n * n);
return res;
}
long long getPositionInSeries(long long a, long long b,
long long c, long long k)
{
long long start = 1, end = SMALL_N;
// if c is 0, then value of n can be in order of 10^15.
// if c!=0, then n^3 value has to be in order of 10^18
// so maximum value of n can be 10^6.
if (c == 0) {
end = LARGE_N;
}
long long ans = 0;
// for efficient searching, use binary search.
while (start <= end) {
long long mid = (start + end) / 2;
long long val = func(a, b, c, mid);
if (val == k) {
ans = mid;
break;
}
else if (val > k) {
end = mid - 1;
}
else {
start = mid + 1;
}
}
return ans;
}
// Driver code
int main()
{
long long a = 2, b = 1, c = 1;
long long k = 12168587437017;
cout << getPositionInSeries(a, b, c, k);
return 0;
}
Java
// Java implementation of the approach
import java.util.*;
class GFG {
static long SMALL_N = 1000000;
static Long LARGE_N = Long.parseUnsignedLong("1000000000000000");
// Function to return the value of f(n) for given values
// of a, b, c, n
static long func(long a, long b, long c, long n)
{
long res = a * n;
long logVlaue = (long)(Math.log(n) / Math.log(2));
res += b * n * logVlaue;
res += c * (n * n * n);
return res;
}
static long getPositionInSeries(long a, long b, long c,
long k)
{
long start = 1, end = SMALL_N;
// if c is 0, then value of n can be in order of
// 10^15. if c!=0, then n^3 value has to be in order
// of 10^18 so maximum value of n can be 10^6.
if (c == 0) {
end = LARGE_N;
}
long ans = 0;
// for efficient searching, use binary search.
while (start <= end) {
long mid = (start + end) / 2;
long val = func(a, b, c, mid);
if (val == k) {
ans = mid;
break;
}
else if (val > k) {
end = mid - 1;
}
else {
start = mid + 1;
}
}
return ans;
}
// Driver code
public static void main(String[] args)
{
long a = 2, b = 1, c = 1;
Long k = Long.parseUnsignedLong("12168587437017");
System.out.println(getPositionInSeries(a, b, c, k));
}
}
// This code is contributed by phasing17
Python3
# Python 3 implementation of the approach
from math import log2, floor
SMALL_N = 1000000
LARGE_N = 1000000000000000
# Function to return the value of f(n)
# for given values of a, b, c, n
def func(a, b, c, n) :
res = a * n
logVlaue = floor(log2(n))
res += b * n * logVlaue
res += c * (n * n * n)
return res
def getPositionInSeries(a, b, c, k) :
start = 1
end = SMALL_N
# if c is 0, then value of n
# can be in order of 10^15.
# if c!=0, then n^3 value has
# to be in order of 10^18
# so maximum value of n can be 10^6.
if (c == 0) :
end = LARGE_N
ans = 0
# for efficient searching,
# use binary search.
while (start <= end) :
mid = (start + end) // 2
val = func(a, b, c, mid)
if (val == k) :
ans = mid
break
elif (val > k) :
end = mid - 1
else :
start = mid + 1
return ans;
# Driver code
if __name__ == "__main__" :
a = 2
b = 1
c = 1
k = 12168587437017
print(getPositionInSeries(a, b, c, k))
# This code is contributed by Ryuga
C#
// C# implementation of the approach
using System;
using System.Collections.Generic;
class GFG {
static long SMALL_N = 1000000;
static long LARGE_N = 1000000000000000;
// Function to return the value of f(n) for given values
// of a, b, c, n
static long func(long a, long b, long c, long n)
{
long res = a * n;
long logVlaue = (long)(Math.Log(n) / Math.Log(2));
res += b * n * logVlaue;
res += c * (n * n * n);
return res;
}
static long getPositionInSeries(long a, long b, long c,
long k)
{
long start = 1, end = SMALL_N;
// if c is 0, then value of n can be in order of
// 10^15. if c!=0, then n^3 value has to be in order
// of 10^18 so maximum value of n can be 10^6.
if (c == 0) {
end = LARGE_N;
}
long ans = 0;
// for efficient searching, use binary search.
while (start <= end) {
long mid = (start + end) / 2;
long val = func(a, b, c, mid);
if (val == k) {
ans = mid;
break;
}
else if (val > k) {
end = mid - 1;
}
else {
start = mid + 1;
}
}
return ans;
}
// Driver code
public static void Main(string[] args)
{
long a = 2, b = 1, c = 1;
long k = 12168587437017;
Console.WriteLine(getPositionInSeries(a, b, c, k));
}
}
// This code is contributed by phasing17
PHP
<?php
// PHP implementation of the approach
// from math import log2, floor
$SMALL_N = 1000000;
$LARGE_N = 1000000000000000;
// Function to return the value of f(n)
// for given values of a, b, c, n
function func($a, $b, $c, $n)
{
$res = $a * $n;
$logVlaue = floor(log($n, 2));
$res += $b * $n * $logVlaue;
$res += $c * ($n * $n * $n);
return $res;
}
function getPositionInSeries($a, $b, $c, $k)
{
global $SMALL_N, $LARGE_N;
$start = 1;
$end = $SMALL_N;
// if c is 0, then value of n
// can be in order of 10^15.
// if c!=0, then n^3 value has
// to be in order of 10^18
// so maximum value of n can be 10^6.
if ($c == 0)
$end = $LARGE_N;
$ans = 0;
// for efficient searching,
// use binary search.
while ($start <= $end)
{
$mid = (int)(($start + $end) / 2);
$val = func($a, $b, $c, $mid) ;
if ($val == $k)
{
$ans = $mid;
break;
}
else if ($val > $k)
$end = $mid - 1;
else
$start = $mid + 1;
}
return $ans;
}
// Driver code
$a = 2;
$b = 1;
$c = 1;
$k = 12168587437017;
print(getPositionInSeries($a, $b, $c, $k));
// This code is contributed by mits
?>
JavaScript
<script>
// Javascript implementation of the approach
const SMALL_N = 1000000;
const LARGE_N = 1000000000000000;
// Function to return the value of f(n)
// for given values of a, b, c, n
function func(a, b, c, n)
{
let res = a * n;
let logVlaue = Math.floor(Math.log(n) /
Math.log(2));
res += b * n * logVlaue;
res += c * (n * n * n);
return res;
}
function getPositionInSeries(a, b, c, k)
{
let start = 1, end = SMALL_N;
// If c is 0, then value of n can be
// in order of 10^15. If c!=0, then
// n^3 value has to be in order of 10^18
// so maximum value of n can be 10^6.
if (c == 0)
{
end = LARGE_N;
}
let ans = 0;
// For efficient searching, use binary search.
while (start <= end)
{
let mid = parseInt((start + end) / 2);
let val = func(a, b, c, mid);
if (val == k)
{
ans = mid;
break;
}
else if (val > k)
{
end = mid - 1;
}
else
{
start = mid + 1;
}
}
return ans;
}
// Driver code
let a = 2, b = 1, c = 1;
let k = 12168587437017;
document.write(getPositionInSeries(a, b, c, k));
// This code is contributed by souravmahato348
</script>
Time Complexity: O(log n), since it's a binary search where each time the elements are reduced to half.
Auxiliary Space: O(1), since no extra space has been taken.
Similar Reads
Basics & Prerequisites
Data Structures
Array Data StructureIn this article, we introduce array, implementation in different popular languages, its basic operations and commonly seen problems / interview questions. An array stores items (in case of C/C++ and Java Primitive Arrays) or their references (in case of Python, JS, Java Non-Primitive) at contiguous
3 min read
String in Data StructureA string is a sequence of characters. The following facts make string an interesting data structure.Small set of elements. Unlike normal array, strings typically have smaller set of items. For example, lowercase English alphabet has only 26 characters. ASCII has only 256 characters.Strings are immut
2 min read
Hashing in Data StructureHashing is a technique used in data structures that efficiently stores and retrieves data in a way that allows for quick access. Hashing involves mapping data to a specific index in a hash table (an array of items) using a hash function. It enables fast retrieval of information based on its key. The
2 min read
Linked List Data StructureA linked list is a fundamental data structure in computer science. It mainly allows efficient insertion and deletion operations compared to arrays. Like arrays, it is also used to implement other data structures like stack, queue and deque. Hereâs the comparison of Linked List vs Arrays Linked List:
2 min read
Stack Data StructureA Stack is a linear data structure that follows a particular order in which the operations are performed. The order may be LIFO(Last In First Out) or FILO(First In Last Out). LIFO implies that the element that is inserted last, comes out first and FILO implies that the element that is inserted first
2 min read
Queue Data StructureA Queue Data Structure is a fundamental concept in computer science used for storing and managing data in a specific order. It follows the principle of "First in, First out" (FIFO), where the first element added to the queue is the first one to be removed. It is used as a buffer in computer systems
2 min read
Tree Data StructureTree Data Structure is a non-linear data structure in which a collection of elements known as nodes are connected to each other via edges such that there exists exactly one path between any two nodes. Types of TreeBinary Tree : Every node has at most two childrenTernary Tree : Every node has at most
4 min read
Graph Data StructureGraph Data Structure is a collection of nodes connected by edges. It's used to represent relationships between different entities. If you are looking for topic-wise list of problems on different topics like DFS, BFS, Topological Sort, Shortest Path, etc., please refer to Graph Algorithms. Basics of
3 min read
Trie Data StructureThe Trie data structure is a tree-like structure used for storing a dynamic set of strings. It allows for efficient retrieval and storage of keys, making it highly effective in handling large datasets. Trie supports operations such as insertion, search, deletion of keys, and prefix searches. In this
15+ min read
Algorithms
Searching AlgorithmsSearching algorithms are essential tools in computer science used to locate specific items within a collection of data. In this tutorial, we are mainly going to focus upon searching in an array. When we search an item in an array, there are two most common algorithms used based on the type of input
2 min read
Sorting AlgorithmsA Sorting Algorithm is used to rearrange a given array or list of elements in an order. For example, a given array [10, 20, 5, 2] becomes [2, 5, 10, 20] after sorting in increasing order and becomes [20, 10, 5, 2] after sorting in decreasing order. There exist different sorting algorithms for differ
3 min read
Introduction to RecursionThe process in which a function calls itself directly or indirectly is called recursion and the corresponding function is called a recursive function. A recursive algorithm takes one step toward solution and then recursively call itself to further move. The algorithm stops once we reach the solution
14 min read
Greedy AlgorithmsGreedy algorithms are a class of algorithms that make locally optimal choices at each step with the hope of finding a global optimum solution. At every step of the algorithm, we make a choice that looks the best at the moment. To make the choice, we sometimes sort the array so that we can always get
3 min read
Graph AlgorithmsGraph is a non-linear data structure like tree data structure. The limitation of tree is, it can only represent hierarchical data. For situations where nodes or vertices are randomly connected with each other other, we use Graph. Example situations where we use graph data structure are, a social net
3 min read
Dynamic Programming or DPDynamic Programming is an algorithmic technique with the following properties.It is mainly an optimization over plain recursion. Wherever we see a recursive solution that has repeated calls for the same inputs, we can optimize it using Dynamic Programming. The idea is to simply store the results of
3 min read
Bitwise AlgorithmsBitwise algorithms in Data Structures and Algorithms (DSA) involve manipulating individual bits of binary representations of numbers to perform operations efficiently. These algorithms utilize bitwise operators like AND, OR, XOR, NOT, Left Shift, and Right Shift.BasicsIntroduction to Bitwise Algorit
4 min read
Advanced
Segment TreeSegment Tree is a data structure that allows efficient querying and updating of intervals or segments of an array. It is particularly useful for problems involving range queries, such as finding the sum, minimum, maximum, or any other operation over a specific range of elements in an array. The tree
3 min read
Pattern SearchingPattern searching algorithms are essential tools in computer science and data processing. These algorithms are designed to efficiently find a particular pattern within a larger set of data. Patten SearchingImportant Pattern Searching Algorithms:Naive String Matching : A Simple Algorithm that works i
2 min read
GeometryGeometry is a branch of mathematics that studies the properties, measurements, and relationships of points, lines, angles, surfaces, and solids. From basic lines and angles to complex structures, it helps us understand the world around us.Geometry for Students and BeginnersThis section covers key br
2 min read
Interview Preparation
Practice Problem