I am working in a math software with different features one of them to be to find all Carmichael numbers in a given interval [a,b)
This is my code, but I don't know if I have done it correctly or not cause I can't test it since the smallest Carmichael number is 560 which is too big for my pc to process.
#include <stdio.h>
int main() {
unsigned int begin, end;
printf("Write an int (begin):\n");
scanf("%d", &begin);
printf("Write an int (end):\n");
scanf("%d", &end);
int i;
for( int i=begin; i<end; i++ ) {
long unsigned int a_nr = i-1;
int a[a_nr];
for( int j=0; j<a_nr; j++ ) {
a[j] = j;
}
unsigned long c_nr[a_nr];
for( int k=0; k<a_nr; k++ ) {
unsigned long current_c_nr;
int mod;
for( int l=0; l<i; l++ ) {
current_c_nr= current_c_nr * a[k];
}
mod = current_c_nr%i;
if( mod==a[k] && mod!=a[k] ) {
c_nr[k] = i;
}
}
}
return 0;
}
If it is not correct, where is the mistake?
Thank you
P.S Overflow should be prevented.
When you say "This is my code, but I don't know if I have done it correctly or not cause I can't test it since the smallest Carmichael number is 560 which is too big for my pc to process" then the conclusion is -- you haven't done it correctly. You should be able to process 561 (560 must be a typo) in a small fraction of a second. Even if your algorithm is in principle correct, if it can't handle the smallest Carmichael number then it is useless.
n is Carmichael if and only if it is composite and, for all a with 1 < a < n which are relatively prime to n, the congruence a^(n-1) = 1 (mod n) holds. To use this definition directly, you need:
1) An efficient way to test if a and n are relatively prime
2) An efficient way to compute a^(n-1) (mod n)
For the first -- use the Euclidean algorithm for greatest common divisors. It is most efficiently computed in a loop, but can also be defined via the simple recurrence gcd(a,b) = gcd(b,a%b) with basis gcd(a,0) = a. In C this is just:
unsigned int gcd(unsigned int a, unsigned int b){
return b == 0? a : gcd(b, a%b);
}
For the second point -- almost the worst possible thing you can do when computing a^k (mod n) is to first compute a^k via repeated multiplication and to then mod the result by n. Instead -- use exponentiation by squaring, taking the remainder (mod n) at intermediate stages. It is a divide-and-conquer algorithm based on the observation that e.g. a^10 = (a^5)^2 and a^11 = (a^5)^2 * a. A simple C implementation is:
unsigned int modexp(unsigned int a, unsigned int p, unsigned int n){
unsigned long long b;
switch(p){
case 0:
return 1;
case 1:
return a%n;
default:
b = modexp(a,p/2,n);
b = (b*b) % n;
if(p%2 == 1) b = (b*a) % n;
return b;
}
}
Note the use of unsigned long long to guard against overflow in the calculation of b*b.
To test if n is Carmichael, you might as well first test if n is even and return 0 in that case. Otherwise, step through numbers, a, in the range 2 to n-1. First check if gcd(a,n) == 1 Note that if n is composite then you must have at least one a before you reach the square root of n with gcd(a,n) > 1). Keep a Boolean flag which keeps track of whether or not such an a has been encountered and if you exceed the square root without finding such an a, return 0. For those a with gcd(a,n) == 1, compute the modular exponentiation a^(n-1) (mod n). If this is ever different from 1, return 0. If your loop finishes checking all a below n without returning 0, then the number is Carmichael, so return 1. An implementation is:
int is_carmichael(unsigned int n){
int a,s;
int factor_found = 0;
if (n%2 == 0) return 0;
//else:
s = sqrt(n);
a = 2;
while(a < n){
if(a > s && !factor_found){
return 0;
}
if(gcd(a,n) > 1){
factor_found = 1;
}
else{
if(modexp(a,n-1,n) != 1){
return 0;
}
}
a++;
}
return 1; //anything that survives to here is a carmichael
}
A simple driver program:
int main(void){
unsigned int n;
for(n = 2; n < 100000; n ++){
if(is_carmichael(n)) printf("%u\n",n);
}
return 0;
}
output:
C:\Programs>gcc carmichael.c
C:\Programs>a
561
1105
1729
2465
2821
6601
8911
10585
15841
29341
41041
46657
52633
62745
63973
75361
This only takes about 2 seconds to run and matches the initial part of this list.
This is probably a somewhat practical method for checking if numbers up to a million or so are Carmichael numbers. For larger numbers, you should probably get yourself a good factoring algorithm and use Korseldt's criterion as described in the Wikipedia entry on Carmichael numbers.
Related
I have to print numbers between two limits n and m, t times.
I created t variable, and two pointers n, m that points to reserved blocks of memory for t integer values.
I use pointers instead of array to do faster operations.
Outer for loop iterates for every test cases and increasing m and n pointers.
Inner for loop prints primes from m[i] to n[i].
Code
#include <stdio.h>
#include <stdlib.h>
int is_prime(int);
int main(void) {
int t;
int *n = malloc(sizeof(int) * t);
int *m = malloc(sizeof(int) * t);
scanf("%d", &t);
for (int i = 0; i < t; i++, m++, n++) {
scanf("%d %d", &m[i], &n[i]);
for (int j = m[i]; j <= n[i]; j++) {
if (is_prime(j)) {
printf("%d\n", j);
}
}
if (i < t - 1) printf("\n");
}
return 0;
}
int is_prime(int num)
{
if (num <= 1) return 0;
if (num % 2 == 0 && num > 2) return 0;
for(int i = 3; i < num / 2; i+= 2){
if (num % i == 0)
return 0;
}
return 1;
}
Problem: http://www.spoj.com/problems/PRIME1/
Code is correctly compiling on http://ideone.com but I'm giving "time limit exceeded" error when I'm trying submit this code on SPOJ. How can I reduce execution time of this prime number generator?
As #Carcigenicate suggests, you're exceeding the time limit because your prime generator is too slow; and it's too slow since you're using an inefficient algorithm.
Indeed, you should not simply test each consecutive number for primality (which, by the way, you're also doing ineffectively), but rather rule out multiple values at once using known primes (and perhaps additional primes which you compute). For example, you don't need to check multiples of 5 and 10 (other than the actual value 5) for primality, since you know that 5 divides them. So just "mark" the multiples of various primes as irrelevant.
... and of course, that's just for getting you started, there are all sort of tricks you could use for optimization - algorithmic and implementation-related.
I know that you are looking for algorithm improvements, but the following technical optimizations might help:
If you are using Visual Studio, you can use alloca instead of malloc, so that n and m go in the stack instead of the heap.
You can also try to rewrite your algorithm using arrays instead of pointers to put n and m in the stack.
If you want to keep using pointers, use the __restrict keyword after the asterisks, which alerts the compiler that you don't make references of the two pointers.
You can even do it without using pointers or arrays
#include <stdio.h>
#include<math.h>
int is_prime(long n){
if (n == 1 || n % 2 == 0)
return 0;
if (n == 2)
return 1;
for (long i = 3; i <= sqrt(n); i += 2) {
if(n % i == 0)
return 0;
}
return 1;
}
int main() {
int t;
scanf("%d",&t);
while(t--) {
long n, m;
scanf("%ld %ld",&n,&m);
for (long i = n; i <= m; i++) {
if (is_prime(i) == 1)
printf("%ld\n",i);
}
}
return 0;
}
There are several ways to improve the primality check for an integer n. Here are a few that you might find useful.
Reduce the number of checks: A well known theorem is giving the fact that if you want to look for factors of n, let say n = a * b, then you can look for a divisor between 1 and sqrt(n). (Proof is quite easy, the main argument being that we have three cases, either a = b = sqrt(n), or we have a < sqrt(n) < b or b < sqrt(n) < a. And, whatever case we fall in, there will be a factor of n between 1 and sqrt(n)).
Use a Sieve of Eratosthenes: This way allows to discard unnecessary candidates which are previously disqualified (see Sieve of Eratosthenes (Wikipedia))
Use probabilistic algorithms: The most efficient way to check for primality nowadays is to use a probabilistic test. It is a bit more complex to implements but it is way more efficient. You can find a few of these techniques here (Wikipedia).
I am new to programming and C is the only language I know. Read a few answers for the same question written in other programming languages. I have written some code for the same but I only get a few test cases correct (4 to be precise). How do I edit my code to get accepted?
I have tried comparing one element of the array with the rest and then I remove the element (which is being compared with the initial) if their sum is divisible by k and then this continues until there are two elements in the array where their sum is divisible by k. Here is the link to the question:
https://www.hackerrank.com/challenges/non-divisible-subset/problem
#include<stdio.h>
#include<stdlib.h>
void remove_element(int array[],int position,long int *n){
int i;
for(i=position;i<=(*n)-1;i++){
array[i]=array[i+1];
}
*n=*n-1;
}
int main(){
int k;
long int n;
scanf("%ld",&n);
scanf("%d",&k);
int *array=malloc(n*sizeof(int));
int i,j;
for(i=0;i<n;i++)
scanf("%d",&array[i]);
for(i=n-1;i>=0;i--){
int counter=0;
for(j=n-1;j>=0;j--){
if((i!=j)&&(array[i]+array[j])%k==0)
{
remove_element(array,j,&n);
j--;
continue;
}
else if((i!=j)&&(array[i]+array[j])%k!=0){
counter++;
}
}
if(counter==n-1){
printf("%ld",n);
break;
}
}
return 0;
}
I only get about 4 test cases right from 20 test cases.
What Gerhardh in his comment hinted at is that
for(i=position;i<=(*n)-1;i++){
array[i]=array[i+1];
}
reads from array[*n] when i = *n-1, overrunning the array. Change that to
for (i=position; i<*n-1; i++)
array[i]=array[i+1];
Additionally, you have
remove_element(array,j,&n);
j--;
- but j will be decremented when continuing the for loop, so decrementing it here is one time too many, while adjustment of i is necessary, since remove_element() shifted array[i] one position to the left, so change j-- to i--.
Furthermore, the condition
if(counter==n-1){
printf("%ld",n);
break;
}
makes just no sense; remove that block and place printf("%ld\n", n); before the return 0;.
To solve this efficiently, you have to realize several things:
Two positive integer numbers a and b are divisible by k (also positive integer number) if ((a%k) + (b%k))%k = 0. That means, that either ((a%k) + (b%k)) = 0 (1) or ((a%k) + (b%k)) = k (2).
Case (1) ((a%k) + (b%k)) = 0 is possible only if both a and b are multiples of k or a%k=0 and b%k=0. For case (2) , there are at most k/2 possible pairs. So, our task is to pick elements that don't fall in case 1 or 2.
To do this, map each number in your array to its corresponding remainder by modulo k. For this, create a new array remainders in which an index stands for a remainder, and a value stands for numbers having such remainder.
Go over the new array remainders and handle 3 cases.
4.1 If remainders[0] > 0, then we can still pick only one element from the original (if we pick more, then sum of their remainders 0, so they are divisible by k!!!).
4.2 if k is even and remainders[k/2] > 0, then we can also pick only one element (otherwise their sum is k!!!).
4.3 What about the other numbers? Well, for any remainder rem > 0 make sure to pick max(remainders[rem], remainders[k - rem]). You can't pick both since rem + k - rem = k, so numbers from such groups can be divisible by k.
Now, the code:
int nonDivisibleSubset(int k, int s_count, int* s) {
static int remainders[101];
for (int i = 0; i < s_count; i++) {
int rem = s[i] % k;
remainders[rem]++;
}
int maxSize = 0;
bool isKOdd = k & 1;
int halfK = k / 2;
for (int rem = 0; rem <= halfK; rem++) {
if (rem == 0) {
maxSize += remainders[rem] > 0;
continue;
}
if (!isKOdd && (rem == halfK)) {
maxSize++;
continue;
}
int otherRem = k - rem;
if (remainders[rem] > remainders[otherRem]) {
maxSize += remainders[rem];
} else {
maxSize += remainders[otherRem];
}
}
return maxSize;
}
I have to print numbers between two limits n and m, t times.
I created t variable, and two pointers n, m that points to reserved blocks of memory for t integer values.
I use pointers instead of array to do faster operations.
Outer for loop iterates for every test cases and increasing m and n pointers.
Inner for loop prints primes from m[i] to n[i].
Code
#include <stdio.h>
#include <stdlib.h>
int is_prime(int);
int main(void) {
int t;
int *n = malloc(sizeof(int) * t);
int *m = malloc(sizeof(int) * t);
scanf("%d", &t);
for (int i = 0; i < t; i++, m++, n++) {
scanf("%d %d", &m[i], &n[i]);
for (int j = m[i]; j <= n[i]; j++) {
if (is_prime(j)) {
printf("%d\n", j);
}
}
if (i < t - 1) printf("\n");
}
return 0;
}
int is_prime(int num)
{
if (num <= 1) return 0;
if (num % 2 == 0 && num > 2) return 0;
for(int i = 3; i < num / 2; i+= 2){
if (num % i == 0)
return 0;
}
return 1;
}
Problem: http://www.spoj.com/problems/PRIME1/
Code is correctly compiling on http://ideone.com but I'm giving "time limit exceeded" error when I'm trying submit this code on SPOJ. How can I reduce execution time of this prime number generator?
As #Carcigenicate suggests, you're exceeding the time limit because your prime generator is too slow; and it's too slow since you're using an inefficient algorithm.
Indeed, you should not simply test each consecutive number for primality (which, by the way, you're also doing ineffectively), but rather rule out multiple values at once using known primes (and perhaps additional primes which you compute). For example, you don't need to check multiples of 5 and 10 (other than the actual value 5) for primality, since you know that 5 divides them. So just "mark" the multiples of various primes as irrelevant.
... and of course, that's just for getting you started, there are all sort of tricks you could use for optimization - algorithmic and implementation-related.
I know that you are looking for algorithm improvements, but the following technical optimizations might help:
If you are using Visual Studio, you can use alloca instead of malloc, so that n and m go in the stack instead of the heap.
You can also try to rewrite your algorithm using arrays instead of pointers to put n and m in the stack.
If you want to keep using pointers, use the __restrict keyword after the asterisks, which alerts the compiler that you don't make references of the two pointers.
You can even do it without using pointers or arrays
#include <stdio.h>
#include<math.h>
int is_prime(long n){
if (n == 1 || n % 2 == 0)
return 0;
if (n == 2)
return 1;
for (long i = 3; i <= sqrt(n); i += 2) {
if(n % i == 0)
return 0;
}
return 1;
}
int main() {
int t;
scanf("%d",&t);
while(t--) {
long n, m;
scanf("%ld %ld",&n,&m);
for (long i = n; i <= m; i++) {
if (is_prime(i) == 1)
printf("%ld\n",i);
}
}
return 0;
}
There are several ways to improve the primality check for an integer n. Here are a few that you might find useful.
Reduce the number of checks: A well known theorem is giving the fact that if you want to look for factors of n, let say n = a * b, then you can look for a divisor between 1 and sqrt(n). (Proof is quite easy, the main argument being that we have three cases, either a = b = sqrt(n), or we have a < sqrt(n) < b or b < sqrt(n) < a. And, whatever case we fall in, there will be a factor of n between 1 and sqrt(n)).
Use a Sieve of Eratosthenes: This way allows to discard unnecessary candidates which are previously disqualified (see Sieve of Eratosthenes (Wikipedia))
Use probabilistic algorithms: The most efficient way to check for primality nowadays is to use a probabilistic test. It is a bit more complex to implements but it is way more efficient. You can find a few of these techniques here (Wikipedia).
I need to input this equation and there's a factorial in it. I would like to know if there was something like * = multiplication or pow(1,3) for factorial of something in C.
term = pow(-1, K) * pow(x, 2K)/(2K)
The factorial would be for the last 2K.
Rarely you need a function for computing factorials. Factorials grow so fast that a look-up-table is sufficient for the few values for which the computation does not overflow. If you are computing terms in a loop, you can avoid computing the factorial using an accumulator for the entire term.
K = 0;
term = 1;
while (K<N) {
/* use term */
do_something_with(term);
/* update term for new value of K */
K += 1;
term = -term * x*x / (2*K*(2*K-1));
}
If that seems unclear to you, you can first derive this program where the accumulators are explicit, and then combine the update step into a single variable like above. This program will still have problems with the factorial computation blowing up.
K = 0;
pow_minus_1_K = 1;
pow_x_2K = 1;
factorial_2K = 1;
while (K<N) {
/* compute term */
term = pow_minus_1_K * pow_x_2K/factorial_2K;
/* update accumulators for new value of K */
K += 1;
pow_minus_1_K = -pow_minus_1_K;
pow_x_2K *= x*x;
factorial_2K *= 2*K*(2*K-1);
}
Factorials are easy to calculate, after all n! is just the product of all numbers up to n. But there is a practical problem: Factorials overflow pretty quickly. A 32-bit int can hold 12!, a 64-bit int 20!.
Depending on how your series converges, you might overflow the valid range.
With approximation series like yours, it is usually better to find a means to represent term k by means of term k − 1. In your case:
term = pow(-1, k) * pow(x, 2*k) / fact(2*k)
you can represent a term as
term[k + 1] = -term[k] * pow(x, 2) / ((2*k - 1) * (2*k - 2))
and your series becomes:
double f(double x)
{
double term = 1.0;
double res = term;
int k = 0;
while (k < 100) {
double old = res;
term = -term * (x / (2*k + 1)) * (x / (2*k + 2));
res += term;
if (res == old) break;
k++;
}
return res;
}
This function will use at most 100 iterations to calculate the cosine. It stops when the term doesn't contribute to the result. In practice, it reaches the result with about 10 iterations, so in that case the regular factorial calculations would have been accurate enough. Still, calculating them over and over is wasteful.
There is no predefined function for factorial, but it can be recursively implemented as follows.
int factorial( int a )
{
if ( 0 == a )
return 1;
else
return a * factorial( a - 1 );
}
People who like the ? operator might implement the function as follows.
int factorial( int a )
{
return 0 == a ? 1 : ( a * factorial( a - 1 ) );
}
If a non-recursive formulation is desired, the implementation can be done as follows.
int factorial( int a )
{
int Result = 1;
for ( int i = a; i > 0; Result *= i, i-- );
return Result;
}
If for some reason recursive functions leave you scratching your head, you can also implement it without recursion:
/* calculate n factorial */
unsigned long long nfact (int n)
{
if (n <= 1) return 1;
unsigned long long s = n;
while (--n)
s *= n;
return s;
}
(note: it is up to you to you to implement a test for overflow, if desired)
I think using recursion for this problem is a good way to get started with recursion and understand the way it works, but it's not efficient enough since you're calling a function every time. If you want to know why, do a test and see how long it takes. Although I should say, the iterative method is not significantly better either.
From Code Complete by Steve McConnell:
Don't use recursion for factorials or Fibonacci numbers
One problem with computer-science textbooks is that they present silly
examples of recursion. The typical examples are computing a factorial
or computing a Fibonacci sequence. Recursion is a powerful tool, and
it's really dumb to use it in either of those cases. If a programmer
who worked for me used recursion to compute a factorial, I'd hire
someone else.
So when keep that in mind when going over the recursive versions that are posted here. Now, how to write one.
Basically you have a base case for when the number is less than 1, and a general recursive case. You generally have a base case and a recursive case in a recursive function. For a factorial, it would look something like this:
int factorial_rec(int number)
{
if (number == 0)
{
return 1;
}else
{
return number * factorial_rec(number - 1);
}
}
long fact(int num)
{
if(num==0)
return 1;
else
return num*fact(num-1);
}
Include the above code and call this method to get factorial of a number.
The code to find factorial of a given number using recursive algorithm can be as shown below :
#include<stdio.h>
int fact(int n)
{
if(!n)
return 1;
else
return (n*fact(n-1));
}
void main()
{
int n;
printf("Enter number : ");
scanf("%d",&n);
printf("\nFactorial of %d is : %d",n,fact(n));
}
#include<stdio.h>
long factorial(int n)
{
if (n == 0)
return 1;
else
return(n * factorial(n-1));
}
void main()
{
int number;
long fact;
printf("Enter a number: ");
scanf("%d", &number);
fact = factorial(number);
printf("Factorial of %d is %ld\n", number, fact);
return 0;
}
#include<stdio.h>
int main()
{
int i,fact=1,number;
printf("Enter a number: ");
scanf("%d",&number);
for(i=1;i<=number;i++){
fact=fact*i;
}
printf("Factorial of %d is: %d",number,fact);
return 0;
}
#include <stdio.h>
int main() {
int n, i;
unsigned long long fact = 1;
printf("Enter an integer: ");
scanf("%d", &n);
// shows error if the user enters a negative integer
if (n < 0)
printf("Error! Factorial of a negative number doesn't exist.");
else {
for (i = 1; i <= n; ++i) {
fact *= i;
}
printf("Factorial of %d = %llu", n, fact);
}
return 0;
}
This question already has answers here:
nth fibonacci number in sublinear time
(16 answers)
Closed 6 years ago.
I am a CSE student and preparing myself for programming contest.Now I am working on Fibonacci series. I have a input file of size about some Kilo bytes containing positive integers. Input formate looks like
3 5 6 7 8 0
A zero means the end of file. Output should like
2
5
8
13
21
my code is
#include<stdio.h>
int fibonacci(int n) {
if (n==1 || n==2)
return 1;
else
return fibonacci(n-1) +fibonacci(n-2);
}
int main() {
int z;
FILE * fp;
fp = fopen ("input.txt","r");
while(fscanf(fp,"%d", &z) && z)
printf("%d \n",fibonacci(z));
return 0;
}
The code works fine for sample input and provide accurate result but problem is for my real input set it is taking more time than my time limit. Can anyone help me out.
You could simply use a tail recursion version of a function that returns the two last fibonacci numbers if you have a limit on the memory.
int fib(int n)
{
int a = 0;
int b = 1;
while (n-- > 1) {
int t = a;
a = b;
b += t;
}
return b;
}
This is O(n) and needs a constant space.
You should probably look into memoization.
http://en.wikipedia.org/wiki/Memoization
It has an explanation and a fib example right there
You can do this by matrix multiplictation, raising the matrix to power n and then multiply it by an vector. You can raise it to power in logaritmic time.
I think you can find the problem here. It's in romanian but you can translate it with google translate. It's exactly what you want, and the solution it's listed there.
Your algorithm is recursive, and approximately has O(2^N) complexity.
This issue has been discussed on stackoverflow before:
Computational complexity of Fibonacci Sequence
There is also a faster implementation posted in that particular discussion.
Look in Wikipedia, there is a formula that gives the number in the Fibonacci sequence with no recursion at all
Use memoization. That is, you cache the answers to avoid unnecessary recursive calls.
Here's a code example:
#include <stdio.h>
int memo[10000]; // adjust to however big you need, but the result must fit in an int
// and keep in mind that fibonacci values grow rapidly :)
int fibonacci(int n) {
if (memo[n] != -1)
return memo[n];
if (n==1 || n==2)
return 1;
else
return memo[n] = fibonacci(n-1) +fibonacci(n-2);
}
int main() {
for(int i = 0; i < 10000; ++i)
memo[i] = -1;
fibonacci(50);
}
Nobody mentioned the 2 value stack array version, so I'll just do it for completeness.
// do not call with i == 0
uint64_t Fibonacci(uint64_t i)
{
// we'll only use two values on stack,
// initialized with F(1) and F(2)
uint64_t a[2] = {1, 1};
// We do not enter loop if initial i was 1 or 2
while (i-- > 2)
// A bitwise AND allows switching the storing of the new value
// from index 0 to index 1.
a[i & 1] = a[0] + a[1];
// since the last value of i was 0 (decrementing i),
// the return value is always in a[0 & 1] => a[0].
return a[0];
}
This is a O(n) constant stack space solution that will perform slightly the same than memoization when compiled with optimization.
// Calc of fibonacci f(99), gcc -O2
Benchmark Time(ns) CPU(ns) Iterations
BM_2stack/99 2 2 416666667
BM_memoization/99 2 2 318181818
The BM_memoization used here will initialize the array only once and reuse it for every other call.
The 2 value stack array version performs identically as a version with a temporary variable when optimized.
You can also use the fast doubling method of generating Fibonacci series
Link: fastest-way-to-compute-fibonacci-number
It is actually derived from the results of the matrix exponentiation method.
Use the golden-ratio
Build an array Answer[100] in which you cache the results of fibonacci(n).
Check in your fibonacci code to see if you have precomputed the answer, and
use that result. The results will astonish you.
Are you guaranteed that, as in your example, the input will be given to you in ascending order? If so, you don't even need memoization; just keep track of the last two results, start generating the sequence but only display the Nth number in the sequence if N is the next index in your input. Stop when you hit index 0.
Something like this:
int i = 0;
while ( true ) {
i++; //increment index
fib_at_i = generate_next_fib()
while ( next_input_index() == i ) {
println fib_at_i
}
I leave exit conditions and actually generating the sequence to you.
In C#:
static int fib(int n)
{
if (n < 2) return n;
if (n == 2) return 1;
int k = n / 2;
int a = fib(k + 1);
int b = fib(k);
if (n % 2 == 1)
return a * a + b * b;
else
return b * (2 * a - b);
}
Matrix multiplication, no float arithmetic, O(log N) time complexity assuming integer multiplication/addition is done in constant time.
Here goes python code
def fib(n):
x,y = 1,1
mat = [1,1,1,0]
n -= 1
while n>0:
if n&1==1:
x,y = x*mat[0]+y*mat[1], x*mat[2]+y*mat[3]
n >>= 1
mat[0], mat[1], mat[2], mat[3] = mat[0]*mat[0]+mat[1]*mat[2], mat[0]*mat[1]+mat[1]*mat[3], mat[0]*mat[2]+mat[2]*mat[3], mat[1]*mat[2]+mat[3]*mat[3]
return x
You can reduce the overhead of the if statement: Calculating Fibonacci Numbers Recursively in C
First of all, you can use memoization or an iterative implementation of the same algorithm.
Consider the number of recursive calls your algorithm makes:
fibonacci(n) calls fibonacci(n-1) and fibonacci(n-2)
fibonacci(n-1) calls fibonacci(n-2) and fibonacci(n-3)
fibonacci(n-2) calls fibonacci(n-3) and fibonacci(n-4)
Notice a pattern? You are computing the same function a lot more times than needed.
An iterative implementation would use an array:
int fibonacci(int n) {
int arr[maxSize + 1];
arr[1] = arr[2] = 1; // ideally you would use 0-indexing, but I'm just trying to get a point across
for ( int i = 3; i <= n; ++i )
arr[i] = arr[i - 1] + arr[i - 2];
return arr[n];
}
This is already much faster than your approach. You can do it faster on the same principle by only building the array once up until the maximum value of n, then just print the correct number in a single operation by printing an element of your array. This way you don't call the function for every query.
If you can't afford the initial precomputation time (but this usually only happens if you're asked for the result modulo something, otherwise they probably don't expect you to implement big number arithmetic and precomputation is the best solution), read the fibonacci wiki page for other methods. Focus on the matrix approach, that one is very good to know in a contest.
#include<stdio.h>
int g(int n,int x,int y)
{
return n==0 ? x : g(n-1,y,x+y);}
int f(int n)
{
return g(n,0,1);}
int main (void)
{
int i;
for(i=1; i<=10 ; i++)
printf("%d\n",f(i)
return 0;
}
In the functional programming there is a special algorithm for counting fibonacci. The algorithm uses accumulative recursion. Accumulative recursion are used to minimize the stack size used by algorithms. I think it will help you to minimize the time. You can try it if you want.
int ackFib (int n, int m, int count){
if (count == 0)
return m;
else
return ackFib(n+m, n, count-1);
}
int fib(int n)
{
return ackFib (0, 1, n+1);
}
use any of these: Two Examples of recursion, One with for Loop O(n) time and one with golden ratio O(1) time:
private static long fibonacciWithLoop(int input) {
long prev = 0, curr = 1, next = 0;
for(int i = 1; i < input; i++){
next = curr + prev;
prev = curr;
curr = next;
}
return curr;
}
public static long fibonacciGoldenRatio(int input) {
double termA = Math.pow(((1 + Math.sqrt(5))/2), input);
double termB = Math.pow(((1 - Math.sqrt(5))/2), input);
double factor = 1/Math.sqrt(5);
return Math.round(factor * (termA - termB));
}
public static long fibonacciRecursive(int input) {
if (input <= 1) return input;
return fibonacciRecursive(input - 1) + fibonacciRecursive(input - 2);
}
public static long fibonacciRecursiveImproved(int input) {
if (input == 0) return 0;
if (input == 1) return 1;
if (input == 2) return 1;
if (input >= 93) throw new RuntimeException("Input out of bounds");
// n is odd
if (input % 2 != 0) {
long a = fibonacciRecursiveImproved((input+1)/2);
long b = fibonacciRecursiveImproved((input-1)/2);
return a*a + b*b;
}
// n is even
long a = fibonacciRecursiveImproved(input/2 + 1);
long b = fibonacciRecursiveImproved(input/2 - 1);
return a*a - b*b;
}
using namespace std;
void mult(LL A[ 3 ][ 3 ], LL B[ 3 ][ 3 ]) {
int i,
j,
z;
LL C[ 3 ][ 3 ];
memset(C, 0, sizeof( C ));
for(i = 1; i <= N; i++)
for(j = 1; j <= N; j++) {
for(z = 1; z <= N; z++)
C[ i ][ j ] = (C[ i ][ j ] + A[ i ][ z ] * B[ z ][ j ] % mod ) % mod;
}
memcpy(A, C, sizeof(C));
};
void readAndsolve() {
int i;
LL k;
ifstream I(FIN);
ofstream O(FOUT);
I>>k;
LL A[3][3];
LL B[3][3];
A[1][1] = 1; A[1][2] = 0;
A[2][1] = 0; A[2][2] = 1;
B[1][1] = 0; B[1][2] = 1;
B[2][1] = 1; B[2][2] = 1;
for(i = 0; ((1<<i) <= k); i++) {
if( k & (1<<i) ) mult(A, B);
mult(B, B);
}
O<<A[2][1];
}
//1,1,2,3,5,8,13,21,33,...
int main() {
readAndsolve();
return(0);
}
public static int GetNthFibonacci(int n)
{
var previous = -1;
var current = 1;
int element = 0;
while (1 <= n--)
{
element = previous + current;
previous = current;
current = element;
}
return element;
}
This is similar to answers given before, but with some modifications. Memorization, as stated in other answers, is another way to do this, but I dislike code that doesn't scale as technology changes (size of an unsigned int varies depending on the platform) so the highest value in the sequence that can be reached may also vary, and memorization is ugly in my opinion.
#include <iostream>
using namespace std;
void fibonacci(unsigned int count) {
unsigned int x=0,y=1,z=0;
while(count--!=0) {
cout << x << endl; // you can put x in an array or whatever
z = x;
x = y;
y += z;
}
}
int main() {
fibonacci(48);// 48 values in the sequence is the maximum for a 32-bit unsigend int
return 0;
}
Additionally, if you use <limits> its possible to write a compile-time constant expression that would give you the largest index within the sequence that can be reached for any integral data type.
#include<stdio.h>
main()
{
int a,b=2,c=5,d;
printf("%d %d ");
do
{
d=b+c;
b=c;
c=d;
rintf("%d ");
}