Faster Harmonic Number? - c++

I'm a beginner in programming. I am trying to make a program that given two numbers it substracts one harmonic from the other. (Input: n, m / Output: Hn-Hm)
#include <iostream>
#include <iomanip>
#include <math.h>
using namespace std;
int main() {
double n1, n2, h1 = 0, h2 = 0, i; // n = number, h = harmonic
cin >> n1 >> n2;
if (n1 == 0) {
h1 = 0;
}
else {
for (i = 1; i <= n1; i++) {
h1 += 1 / i;
if (i <= n2) {
h2 += 1 / i;
}
}
}
cout << fixed << setprecision(10) << h1 - h2 << endl;
system("pause");
return 0;
}
The program gives correct results but I'm using a website of my university and it says that the program is slow. I've tried to make it faster but I can't figure out how.
Thanks.

You don't need to calculate the full harmonic numbers. Assuming n1 < n2, the two series will be:
H(n1) = 1 + 1/2 + 1/3 + ... + 1/n1
H(n2) = 1 + 1/2 + 1/3 + ... + 1/n1 + 1/(n1+1) + 1(n1+2) + ... + 1/n2
So when you subtract H(n2) - H(n1), the first n1 terms in the two series cancel each other out, so
H(n2) - H(n1) = 1/(n1+1) + 1(n1+2) + ... + 1/n2
If n1 > n2 the result is the negative of this.
double result = 0, mult = 1;
if (n1 > n2) {
double temp = n1;
n1 = n2;
n2 = temp;
mult = -1;
}
for (double denom = n1+1; denom <= n2; denom++) {
result += 1/denom;
}
result *= mult; // Flip the sign if we swapped n1 and n2
cout << fixed << setprecision(10) << result << endl;

Related

Cpp program not giving output

I am creating a script that calculates the sum of first n Fibonacci numbers and returns the last digit of the sum.
The python script works perfect but the C++ script does not and the logic is same.
Any help will be appreciated.
Python Code
def calc_fib(n):
f = [0, 1]
for i in range(2, 61):
f.insert(i, (f[i-1] + f[i-2]) % 10)
rem = n % 60
quotient = (n - rem) / 60
return int((sum(f) * quotient + sum(f[0: rem+1])) % 10)
n = int(input())
print(calc_fib(n))
C++ Code
#include <iostream>
#include <vector>
#include <numeric>
using namespace std;
long long fibonacci_sum_last_digit(long long n) {
vector<int> f(n + 1);
f[0] = 0;
f[1] = 1;
for (int i = 2; i <= 60; i++){
f[i] = (f[i-1] + f[i-2]) % 10;
}
int rem = n % 60;
int quotient = (n - rem) / 60;
return (accumulate(f.begin(), f.end(), 0) * quotient + accumulate(f.begin(), f.begin() + rem + 1, 0)) % 10;
}
int main() {
int n;
cin >> n;
if (n <= 1)
cout << n;
else
cout << fibonacci_sum_last_digit(n) << '\n';
return 0;
}
vector<int> f(n + 1);
f[0] = 0;
f[1] = 1;
for (int i = 2; i <= 60; i++){
f[i] = (f[i-1] + f[i-2]) % 10;
}
The vector is size n+1 and you access until 60 => it's a bug
This should fix :
vector<int> f(60 + 1);
Or
vector<int> f;
f.push_back(0);
f.push_back(1);
for (int i = 2; i <= 60; i++){
f.push_back((f[i-1] + f[i-2]) % 10);
}

greatest divisor of a number and prime factors relation

Question is as follows :
Given two numbers n and k. For each number in the interval [1, n], your task is to calculate its largest divisor that is not divisible by k. Print the sum of all these divisors.
Note: k is always a prime number.
t=3*10^5,1<=n<=10^9, 2<=k<=10^9
My approach toward the question:
for every i in range 1 to n, the required divisors is i itself,only when that i is not a multiple of k.
If that i is multiple of k, then we have to find the greatest divisor of a number and match with k. If it does not match, then this divisor is my answer. otherwise, 2nd largest divisor is my answer.
for example,take n=10 and k=2, required divisors for every i in range 1 to 10 is 1, 1, 3, 1, 5, 3, 7, 1, 9, 5. sum of these divisors are 36. So ans=36.
My code,which works for a few test cases and failed for some.
#include<bits/stdc++.h>
using namespace std;
#define ll long long int
ll div2(ll n, ll k) {
if (n % k != 0 || n == 1) {
return n;
}
else {
for (int i = 2; i * i <= n; i++) {
if (n % i == 0) {
ll aa = n / i;
if (aa % k != 0) {
return aa;
}
}
}
}
return 1;
}
int main() {
ios_base::sync_with_stdio(false);
cin.tie(NULL);
int t;
cin >> t;
while (t--) {
ll n, k;
cin >> n >> k;
ll sum = 0, pp;
for (pp = 1; pp <= n; pp++) {
//cout << div2(pp, k);
sum = sum + div2(pp, k);
}
cout << sum << '\n';
}
}
Can someone help me where I am doing wrong or suggest me some faster logic to do this question as some of my test cases is showing TIME LIMIT EXCEED
after looking every possible explanation , i modify my code as follows:
#include<bits/stdc++.h>
using namespace std;
#define ll long long int
int main() {
ios_base::sync_with_stdio(false);
cin.tie(NULL);
int t;
cin >> t;
while (t--) {
ll n, i;
ll k, sum;
cin >> n >> k;
sum = (n * (n + 1)) / 2;
for (i = k; i <= n; i = i + k) {
ll dmax = i / k;
while (dmax % k == 0) {
dmax = dmax / k;
}
sum = (sum - i) + dmax;
}
cout << sum << '\n';
}
}
But still it is giving TIME LIMIT EXCEED for 3 test cases. Someone please help.
Like others already said, look at the constraints: t=3*10^5,1<=n<=10^9, 2<=k<=10^9.
If your test has a complexity O(n), which computing the sum via a loop has, you'll end up doing a t * n ~ 10^14. That's too much.
This challenge is a math one. You'll need to use two facts:
as you already saw, if i = j * k^s with j%k != 0, the largest divisor is j;
sum_{i=1}^t i = (t * (t+1)) / 2
We start with
S = sum(range(1, n)) = n * (n+1) / 2
then for all number of the form k * x we added too much, let's correct:
S = S - sum(k*x for x in range(1, n/k)) + sum(x for x in range(1, n/k))
= S - (k - 1) * (n/k) * (n/k + 1) / 2
continue for number of the form k^2 * x ... then k^p * x until the sum is empty...
Ok, people start writing code, so here's a small Python function:
def so61867604(n, k):
S = (n * (n+1)) // 2
k_pow = k
while k_pow <= n:
up = n // k_pow
S = S - (k - 1) * (up * (up + 1)) // 2
k_pow *= k
return S
and in action here https://repl.it/repls/OlivedrabKeyProjections
In itself this is more of a mathematical problem:
If cur = [1..n], as you have already noticed, the largest divisor = dmax = cur is, if cur % k != 0, otherwise dmax must be < cur. From k we know that it is at most divisible into other prime numbers... Since we want to make sure that dmax is not divisible by k we can do this with a while loop... whereby this is certainly also more elegantly possible (since dmax must be a prime number again due to the prime factorization).
So this should look like this (without guarantee just typed down - maybe I missed something in my thinking):
#include <iostream>
int main() {
unsigned long long n = 10;
unsigned long long k = 2;
for (auto cur_n = decltype(n){1}; cur_n <= n; cur_n++)
{
if (cur_n % k != 0) {
std::cout << "Largest divisor for " << cur_n << ": " << cur_n << " (SELF)" << std::endl;
} else {
unsigned long long dmax= cur_n/k;
while (dmax%k == 0)
dmax= dmax/k;
std::cout << "Largest divisor for " << cur_n << ": " << dmax<< std::endl;
}
}
}
I wonder if something like this is what One Lyner means.
(Note, this code has two errors in it, which are described in the comments, as well as can be elucidated by One Lyner's new code.)
C++ code:
#include <vector>
#include <iostream>
using namespace std;
#define ll long long int
int main()
{
ios_base::sync_with_stdio(false);
cin.tie(NULL);
int t;
cin >> t;
while (t--) {
ll n;
ll k, _k, result;
vector<ll> powers;
cin >> n >> k;
result = n * (n + 1) / 2;
_k = k;
while (_k <= n) {
powers.push_back(_k);
_k = _k * k;
}
for (ll p : powers) {
ll num_js = n / p;
result -= num_js * (num_js + 1) / 2 * (p - 1);
int i = 0;
while (p * powers[i] <= n) {
result += powers[i] * (p - 1);
i = i + 1;
}
}
cout << result << '\n';
}
}

I don't understand the how prime numbers are calculated and modPow function is working in the following code

A Magic Fraction for N is one that has the following properties:
It is a proper fraction (The value is < 1)
It cannot be reduced further (The GCD of the numerator and the denominator is 1)
The product of the numerator and the denominator is factorial of N. i.e. if a/b is the fraction, then a*b = N!
Examples of Magic Fractions are:
1/2 [ gcd(1,2) = 1 and 1*2=2! ]
2/3 [ gcd(2,3) = 1 and 2*3=3! ]
3/8 [ gcd(3,8) = 1 and 3*8=4! ]
2/12 for example, is not a magic fraction, as even though 2*12=4!, gcd(2,12) != 1
And Magic fractions for number 3 are: 2/3 and 1/6 (since both of them satisfy the above criteria, are of the form a/b where a*b = 3!)
Now given a number N, you need to print the total number of magic fractions that exist, for all numbers between 1 and N (include magic fractions for N, too).
Can anybody tell me what is modPow function doing?
Refer the link to see the question, that will give an idea why this code.
using namespace std;
#define ll long long int
#define S(n) scanf("%lld", &n)
ll MOD = 1e18 + 7;
ll modPow(ll a, ll b)
{
ll res = 1;
a %= MOD;
for (; b; b >>= 1) {
if (b & 1)
res = res * a % MOD;
a = a * a % MOD;
}
return res;
}
int main()
{
ll i, j;
ll va = 1;
ll sum = 0;
ll prime[1000] = { 0 };
for (i = 2; i <= 500; i++) {
if (prime[i] == 0)
for (j = 2 * i; j <= 500; j += i)
prime[j] = 1;
}
ll val[600] = { 0 };
val[1] = 0;
val[2] = 1;
ll co = 0;
for (i = 3; i <= 500; i++) {
if (prime[i] == 0) {
co++;
}
ll t1 = modPow(2, co);
val[i] = t1 + val[i - 1];
val[i] %= MOD;
// cout << i << " " << val[i] << "\n";
}
ll n;
S(n);
cout << val[n] << "\n";
}

Quasi-Monte Carlo Integration for inverse cumulative Normal Distribution

I am trying to integrate functions, which includes changing of variables with ICDF function (gsl_cdf_gaussian_Pinv(x[1], 1)), but the results are always wrong:
#include <fstream>
#include <iostream>
#include <memory>
#include <cmath>
#include <iomanip>
#include <ctime>
#include <cmath>
#include <cstdlib>
#include <ctime>
#include <math.h>
#include <stdio.h>
#include <gaussinv.c>
#define _USE_MATH_DEFINES
using namespace std;
double f(double[], int);
double int_mcnd(double(*)(double[], int), double[], double[], int, int);
double varr[100];
int k = 0;
double hj = 0;
double mj = 1;
# include "sobol.hpp"
int DIM_NUM = 10;
int main() {
const int n = 10; /* define how many integrals */
// const int m = 1000000; /* define how many points */
double a[n] = {0, 0, 0, 0, 0, 0, 0, 0, 0, 0}; /* left end-points */
double b[n] = {1, 1, 1, 1, 1, 1, 1, 1, 1, 1}; /* right end-points */
double result;
int i, m;
int ntimes;
cout.setf(ios::fixed | ios::showpoint);
// current time in seconds (begin calculations)
time_t seconds_i;
seconds_i = time(NULL);
m = 1; // initial number of intervals
ntimes = 20; // number of interval doublings with nmax=2^ntimes
cout << setw(12) << n << "D Integral" << endl;
for (i = 0; i <= ntimes; i = i + 1) {
result = int_mcnd(f, a, b, n, m);
cout << setw(10) << m << " " << setprecision(30) << result << endl;
m = m * 2;
}
// current time in seconds (end of calculations)
time_t seconds_f;
seconds_f = time(NULL);
cout << endl << "total elapsed time = " << seconds_f - seconds_i << " seconds" << endl << endl;
return 0;
}
double f(double x[], int n) {
double y;
int j;
y = 0.0;
/* define Multidimensional Gaussian distribution and covariance */
/* X=(x1, k=2, mu = (0, covariance matrix = (v 0 0 0
* x2 0 0 v 0 0
* x3 0 0 0 v 0
* x4) 0) 0 0 0 v) */
double v = 1;
double determinant = pow(v, 10);
double inverse = 1 / v;
double rang = gsl_cdf_gaussian_Pinv(0.99999904632568359375, 1) - gsl_cdf_gaussian_Pinv(0.00000095367431640625, 1) +
gsl_cdf_gaussian_Pinv(0.00000095367431640625, 1);
y = (1 / sqrt(pow(2 * M_PI, 10) * determinant) * exp(-0.5 * (inverse * pow(gsl_cdf_gaussian_Pinv(x[0], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[1], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[2], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[3], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[4], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[5], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[6], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[7], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[8], 1), 2) +
inverse * pow(gsl_cdf_gaussian_Pinv(x[9], 1), 2))));
return y;
}
/*==============================================================
input:
fn - a multiple argument real function (supplied by the user)
a[] - left end-points of the interval of integration
b[] - right end-points of the interval of integration
n - dimension of integral
m - number of random points
output:
r - result of integration
================================================================*/
double int_mcnd(double(*fn)(double[], int), double a[], double b[], int n, int m) {
double r, x[n], p;
int i, j;
double rarr[DIM_NUM];
long long int seed;
seed = 1;
long long int seed_in;
long long int seed_out;
srand(time(NULL)); /* initial seed value (use system time) */
r = 0.0;
p = 1.0;
// step 1: calculate the common factor p
for (j = 0; j < n; j = j + 1) {
// p = p * (b[j] - a[j]);
p=p*(gsl_cdf_gaussian_Pinv(0.99999904632568359375, 1)-gsl_cdf_gaussian_Pinv(0.00000095367431640625, 1));
}
// step 2: integration
for (i = 1; i <= m; i = i + 1) {
seed_in = seed;
i8_sobol(DIM_NUM, &seed, rarr);
seed_out = seed;
// calculate random x[] points
for (j = 0; j < n; j = j + 1) {
x[j] = a[j] + (b[j] - a[j]) * rarr[j];
}
r = r + fn(x, n);
}
cout << endl << "p = " << p << " seconds" << endl << endl;
r = r * p / m;
return r;
}
The problem is in the parametrization parameter p, which I suggest to be
p=p*(gsl_cdf_gaussian_Pinv(0.99999904632568359375, 1)-gsl_cdf_gaussian_Pinv(0.00000095367431640625, 1))
instead of standard - p = p * (b[j] - a[j]);
I want to integrate not only within [0,1]^N intervals, but also in [-20;20].
I can't define my mistake. Can somebody help, please?

self made pow() c++

I was reading through How can I write a power function myself? and the answer given by dan04 caught my attention mainly because I am not sure about the answer given by fortran, but I took that and implemented this:
#include <iostream>
using namespace std;
float pow(float base, float ex){
// power of 0
if (ex == 0){
return 1;
// negative exponenet
}else if( ex < 0){
return 1 / pow(base, -ex);
// even exponenet
}else if ((int)ex % 2 == 0){
float half_pow = pow(base, ex/2);
return half_pow * half_pow;
//integer exponenet
}else{
return base * pow(base, ex - 1);
}
}
int main(){
for (int ii = 0; ii< 10; ii++){\
cout << "pow(" << ii << ".5) = " << pow(ii, .5) << endl;
cout << "pow(" << ii << ",2) = " << pow(ii, 2) << endl;
cout << "pow(" << ii << ",3) = " << pow(ii, 3) << endl;
}
}
though I am not sure if I translated this right because all of the calls giving .5 as the exponent return 0. In the answer it states that it might need a log2(x) based on a^b = 2^(b * log2(a)), but I am unsure about putting that in as I am unsure where to put it, or if I am even thinking about this right.
NOTE: I know that this might be defined in a math library, but I don't need all the added expense of an entire math library for a few functions.
EDIT: does anyone know a floating-point implementation for fractional exponents? (I have seen a double implementation, but that was using a trick with registers, and I need floating-point, and adding a library just to do a trick I would be better off just including the math library)
I have looked at this paper here which describes how to approximate the exponential function for double precision. After a little research on Wikipedia about single precision floating point representation I have worked out the equivalent algorithms. They only implemented the exp function, so I found an inverse function for the log and then simply did
POW(a, b) = EXP(LOG(a) * b).
compiling this gcc4.6.2 yields a pow function almost 4 times faster than the standard library's implementation (compiling with O2).
Note: the code for EXP is copied almost verbatim from the paper I read and the LOG function is copied from here.
Here is the relevant code:
#define EXP_A 184
#define EXP_C 16249
float EXP(float y)
{
union
{
float d;
struct
{
#ifdef LITTLE_ENDIAN
short j, i;
#else
short i, j;
#endif
} n;
} eco;
eco.n.i = EXP_A*(y) + (EXP_C);
eco.n.j = 0;
return eco.d;
}
float LOG(float y)
{
int * nTemp = (int*)&y;
y = (*nTemp) >> 16;
return (y - EXP_C) / EXP_A;
}
float POW(float b, float p)
{
return EXP(LOG(b) * p);
}
There is still some optimization you can do here, or perhaps that is good enough.
This is a rough approximation but if you would have been satisfied with the errors introduced using the double representation, I imagine this will be satisfactory.
I think the algorithm you're looking for could be 'nth root'. With an initial guess of 1 (for k == 0):
#include <iostream>
using namespace std;
float pow(float base, float ex);
float nth_root(float A, int n) {
const int K = 6;
float x[K] = {1};
for (int k = 0; k < K - 1; k++)
x[k + 1] = (1.0 / n) * ((n - 1) * x[k] + A / pow(x[k], n - 1));
return x[K-1];
}
float pow(float base, float ex){
if (base == 0)
return 0;
// power of 0
if (ex == 0){
return 1;
// negative exponenet
}else if( ex < 0){
return 1 / pow(base, -ex);
// fractional exponent
}else if (ex > 0 && ex < 1){
return nth_root(base, 1/ex);
}else if ((int)ex % 2 == 0){
float half_pow = pow(base, ex/2);
return half_pow * half_pow;
//integer exponenet
}else{
return base * pow(base, ex - 1);
}
}
int main_pow(int, char **){
for (int ii = 0; ii< 10; ii++){\
cout << "pow(" << ii << ", .5) = " << pow(ii, .5) << endl;
cout << "pow(" << ii << ", 2) = " << pow(ii, 2) << endl;
cout << "pow(" << ii << ", 3) = " << pow(ii, 3) << endl;
}
return 0;
}
test:
pow(0, .5) = 0.03125
pow(0, 2) = 0
pow(0, 3) = 0
pow(1, .5) = 1
pow(1, 2) = 1
pow(1, 3) = 1
pow(2, .5) = 1.41421
pow(2, 2) = 4
pow(2, 3) = 8
pow(3, .5) = 1.73205
pow(3, 2) = 9
pow(3, 3) = 27
pow(4, .5) = 2
pow(4, 2) = 16
pow(4, 3) = 64
pow(5, .5) = 2.23607
pow(5, 2) = 25
pow(5, 3) = 125
pow(6, .5) = 2.44949
pow(6, 2) = 36
pow(6, 3) = 216
pow(7, .5) = 2.64575
pow(7, 2) = 49
pow(7, 3) = 343
pow(8, .5) = 2.82843
pow(8, 2) = 64
pow(8, 3) = 512
pow(9, .5) = 3
pow(9, 2) = 81
pow(9, 3) = 729
I think that you could try to solve it by using the Taylor's series,
check this.
http://en.wikipedia.org/wiki/Taylor_series
With the Taylor's series you can solve any difficult to solve calculation such as 3^3.8 by using the already known results such as 3^4. In this case you have
3^4 = 81 so
3^3.8 = 81 + 3.8*3( 3.8 - 4) +..+.. and so on depend on how big is your n you will get the closer solution of your problem.
I and my friend faced similar problem while we're on an OpenGL project and math.h didn't suffice in some cases. Our instructor also had the same problem and he told us to seperate power to integer and floating parts. For example, if you are to calculate x^11.5 you may calculate sqrt(x^115, 10) which may result more accurate result.
Reworked on #capellic answer, so that nth_root works with bigger values as well.
Without the limitation of an array that is allocated for no reason:
#include <iostream>
float pow(float base, float ex);
inline float fabs(float a) {
return a > 0 ? a : -a;
}
float nth_root(float A, int n, unsigned max_iterations = 500, float epsilon = std::numeric_limits<float>::epsilon()) {
if (n < 0)
throw "Invalid value";
if (n == 1 || A == 0)
return A;
float old_value = 1;
float value;
for (int k = 0; k < max_iterations; k++) {
value = (1.0 / n) * ((n - 1) * old_value + A / pow(old_value, n - 1));
if (fabs(old_value - value) < epsilon)
return value;
old_value = value;
}
return value;
}
float pow(float base, float ex) {
if (base == 0)
return 0;
if (ex == 0){
// power of 0
return 1;
} else if( ex < 0) {
// negative exponent
return 1 / pow(base, -ex);
} else if (ex > 0 && ex < 1) {
// fractional exponent
return nth_root(base, 1/ex);
} else if ((int)ex % 2 == 0) {
// even exponent
float half_pow = pow(base, ex/2);
return half_pow * half_pow;
} else {
// integer exponent
return base * pow(base, ex - 1);
}
}
int main () {
for (int i = 0; i <= 128; i++) {
std::cout << "pow(" << i << ", .5) = " << pow(i, .5) << std::endl;
std::cout << "pow(" << i << ", .3) = " << pow(i, .3) << std::endl;
std::cout << "pow(" << i << ", 2) = " << pow(i, 2) << std::endl;
std::cout << "pow(" << i << ", 3) = " << pow(i, 3) << std::endl;
}
std::cout << "pow(" << 74088 << ", .3) = " << pow(74088, .3) << std::endl;
return 0;
}
This solution of MINE will be accepted upto O(n) time complexity
utpo input less then 2^30 or 10^8
IT will not accept more then these inputs
It WILL GIVE TIME LIMIT EXCEED warning
but easy understandable solution
#include<bits/stdc++.h>
using namespace std;
double recursive(double x,int n)
{
// static is important here
// other wise it will store same values while multiplying
double p = x;
double ans;
// as we multiple p it will multiply it with q which has the
//previous value of this ans latter we will update the q
// so that q has fresh value for further test cases here
static double q=1; // important
if(n==0){ ans = q; q=1; return ans;}
if(n>0)
{
p *= q;
// stored value got multiply by p
q=p;
// and again updated to q
p=x;
//to update the value to the same value of that number
// cout<<q<<" ";
recursive(p,n-1);
}
return ans;
}
class Solution {
public:
double myPow(double x, int n) {
// double q=x;double N=n;
// return pow(q,N);
// when both sides are double this function works
if(n==0)return 1;
x = recursive(x,abs(n));
if(n<0) return double(1/x);
// else
return x;
}
};
For More help you may try
LEETCODE QUESTION NUMBER 50
**NOW the Second most optimize code pow(x,n) **
logic is that we have to solve it in O(logN) so we devide the n by 2
when we have even power n=4 , 4/2 is 2 means we have to just square it (22)(22)
but when we have odd value of power like n=5, 5/2 here we have square it to get
also the the number itself to it like (22)(2*2)*2 to get 2^5 = 32
HOPE YOU UNDERSTAND FOR MORE YOU CAN VISIT
POW(x,n) question on leetcode
below the optimized code and above code was for O(n) only
*
#include<bits/stdc++.h>
using namespace std;
double recursive(double x,int n)
{
// recursive calls will return the whole value of the program at every calls
if(n==0){return 1;}
// 1 is multiplied when the last value we get as we don't have to multiply further
double store;
store = recursive(x,n/2);
// call the function after the base condtion you have given to it here
if(n%2==0)return store*store;
else
{
return store*store*x;
// odd power we have the perfect square multiply the value;
}
}
// main function or the function for indirect call to recursive function
double myPow(double x, int n) {
if(n==0)return 1;
x = recursive(x,abs(n));
// for negatives powers
if(n<0) return double(1/x);
// else for positves
return x;
}