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Here is the link to the problem.
The problem asks the number of solutions to the Diophantine equation of the form 1/x + 1/y = 1/z (where z = n!). Rearranging the given equation clearly tells that the answer is the number of factors of z2.
So the problem boils down to finding the number of factors of n!2 (n factorial squared).
My algorithm is as follows
Make a Boolean look up table for all primes <= n using Sieve of Eratosthenes algorithm.
Iterate over all primes P <= n and find its exponent in n!. I did this using step function formula. Let the exponent be K, then the exponent of P in n!2 will be 2K.
Using step 2 calculate number of factors with the standard formula.
For the worst case input of n = 106, my c code gives answer in 0.056s.
I guess the complexity is no way greater than O(n lg n).
But when I submitted the code on the site, I could pass only 3/15 test cases with the verdict on the rest as time limit exceeded.
I need some hints for optimizing this algorithm.
Code so far:
#include <stdio.h>
#include <string.h>
#define ULL unsigned long long int
#define MAXN 1000010
#define MOD 1000007
int isPrime[MAXN];
ULL solve(int N) {
int i, j, f;
ULL res = 1;
memset(isPrime, 1, MAXN * sizeof(int));
isPrime[0] = isPrime[1] = 0;
for (i = 2; i * i <= N; ++i)
if (isPrime[i])
for (j = i * i; j <= N; j += i)
isPrime[j] = 0;
for (i = 2; i <= N; ++i) {
if (isPrime[i]) {
for (j = i, f = 0; j <= N; j *= i)
f += N / j;
f = ((f << 1) + 1) % MOD;
res = (res * f) % MOD;
}
}
return res % MOD;
}
int main() {
int N;
scanf("%d", &N);
printf("%llu\n", solve(N));
return 0;
}
You have an int overflow here:
for (j = i, f = 0; j <= N; j *= i)
If 46340 < i < 65536 and for many larger i, in the second iteration j will be negative if overflow wraps around (it is undefined behaviour, so anything could happen).
Replace it with e.g.
for(j = N / i, f = 0; j > 0; j /= i) {
f += j;
}
It is, however, unlikely that the extra iterations due to the overflow would cause a "time limit exceeded", that will likely only cause wrong results.
So the generic advice is
Sieve only odd numbers, perhaps also eliminate multiples of 3 from the sieve. Eliminating the odd numbers from the sieve roughly halves the time needed to sieve.
Don't use an entire int for the flags, use bits or at least chars. That gives better cache locality and a further speedup.
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bool prime (long long int n) {
bool prime = 1;
if (n == 1) {
return 0;
}
else {
for (long long int i = 2; i <= n/2 ; i++) {
if (n % i == 0) {
prime = 0;
break ;
}
}
return prime;
}
}
This is my function to check if n is a prime or not. It works until I try a number with 12 digits, like n = 999999999989.
This is for a problem on codeforces; when I submit this function the website prints "Time limit exceeded".
Your code's time complexity is O(n/2) -> O(n).
It would take around 10000 second to check the primality of n if n is 10^12 (given 1 second can only do around 10^8 operation).
for (long long int i = 2; i <= n/2 ; i++) {
if (n % i == 0) {
prime = 0;
break ;
}
The trick here is that you don't need to check i from 2 to n/2. Instead, you can reduce it to just from 2 to sqrt(n). This work because since sqrt(n) * sqrt(n) is n, there shouldn't be any x and y so that x > sqrt(n); y > sqrt(n); x*y = n. Thus, if a divisor for n exist, it should be <= sqrt(n).
So you should change your loop to this
for (long long int i = 2; i*i <= n ; i++) {
if (n % i == 0) {
prime = 0;
break ;
}
}
The time complexity for this code is O(sqrt(n)) which should be enough for n
= 10^12.
P.S : sqrt(n) means square root of n
I should implement this summation in C ++. I have tried with this code, but with very high numbers up to 10 ^ 12 it takes too long.
The summation is:
For any positive integer k, let d(k) denote the number of positive divisors of k (including 1 and k itself).
For example, for the number 4: 1 has 1 divisor, 2 has two divisors, 3 has two divisors, and 4 has three divisors. So the result would be 8.
This is my code:
#include <iostream>
#include <algorithm>
using namespace std;
int findDivisors(long long n)
{
int c=0;
for(int j=1;j*j<=n;j++)
{
if(n%j==0)
{
c++;
if(j!=(n/j))
{
c++;
}
}
}
return c;
}
long long compute(long long n)
{
long long sum=0;
for(int i=1; i<=n; i++)
{
sum += (findDivisors(i));
}
return sum;
}
int main()
{
int n, divisors;
freopen("input.txt", "r", stdin);
freopen("output.txt", "w", stdout);
cin >> n;
cout << compute(n);
}
I think it's not just a simple optimization problem, but maybe I should change the algorithm entirely.
Would anyone have any ideas to speed it up? Thank you.
largest_prime_is_463035818's answer shows an O(N) solution, but the OP is trying to solve this problem
with very high numbers up to 1012.
The following is an O(N1/2) algorithm, based on some observations about the sum
n/1 + n/2 + n/3 + ... + n/n
In particular, we can count the number of terms with a specific value.
Consider all the terms n/k where k > n/2. There are n/2 of those and all are equal to 1 (integer division), so that their sum is n/2.
Similar considerations hold for the other dividends, so that we can write the following function
long long count_divisors(long long n)
{
auto sum{ n };
for (auto i{ 1ll }, k_old{ n }, k{ n }; i < k ; ++i, k_old = k)
{ // ^^^^^ it goes up to sqrt(n)
k = n / (i + 1);
sum += (k_old - k) * i;
if (i == k)
break;
sum += k;
}
return sum;
}
Here it is tested against the O(N) algorithm, the only difference in the results beeing the corner cases n = 0 and n = 1.
Edit
Thanks again to largest_prime_is_463035818, who linked the Wikipedia page about the divisor summatory function, where both an O(N) and an O(sqrt(N)) algorithm are mentioned.
An implementation of the latter may look like this
auto divisor_summatory(long long n)
{
auto sum{ 0ll };
auto k{ 1ll };
for ( ; k <= n / k; ++k )
{
sum += n / k;
}
--k;
return 2 * sum - k * k;
}
They also add this statement:
Finding a closed form for this summed expression seems to be beyond the techniques available, but it is possible to give approximations. The leading behavior of the series is given by
D(x) = xlogx + x(2γ - 1) + Δ(x)
where γ is the Euler–Mascheroni constant, and the error term is Δ(x) = O(sqrt(x)).
I used your brute force approach as reference to have test cases. The ones I used are
compute(12) == 35
cpmpute(100) == 482
Don't get confused by computing factorizations. There are some tricks one can play when factorizing numbers, but you actually don't need any of that. The solution is a plain simple O(N) loop:
#include <iostream>
#include <limits>
long long compute(long long n){
long long sum = n+1;
for (long long i=2; i < n ; ++i){
sum += n/i;
}
return sum;
}
int main()
{
std::cout << compute(12) << "\n";
std::cout << compute(100) << "\n";
}
Output:
35
482
Why does this work?
The key is in Marc Glisse's comment:
As often with this kind of problem, this sum actually counts pairs x,
y where x divides y, and the sum is arranged to count first all x
corresponding to a fixed y, but nothing says you have to keep it that
way.
I could stop here, because the comment already explains it all. Though, if it didn't click yet...
The trick is to realize that it is much simpler to count divisors of all numbers up to n rather than n-times counting divisors of individual numbers and take the sum.
You don't need to care about factorizations of eg 123123123 or 52323423 to count all divisors up to 10000000000. All you need is a change of perspective. Instead of trying to factorize numbers, consider the divisors. How often does the divisor 1 appear up to n? Simple: n-times. How often does the divisor 2 appear? Still simple: n/2 times, because every second number is divisible by 2. Divisor 3? Every 3rd number is divisible by 3. I hope you can see the pattern already.
You could even reduce the loop to only loop till n/2, because bigger numbers obviously appear only once as divisor. Though I didn't bother to go further, because the biggest change is from your O(N * sqrt(N)) to O(N).
Let's start off with some math and reduce the O(n * sq(n)) factorization to O(n * log(log(n))) and for counting the sum of divisors the overall complexity is O(n * log(log(n)) + n * n^(1/3)).
For instance:
In Codeforces himanshujaju explains how we can optimize the solution of finding divisors of a number.
I am simplifying it a little bit.
Let, n as the product of three numbers p, q, and r.
so assume p * q * r = n, where p <= q <= r.
The maximum value of p = n^(1/3).
Now we can loop over all prime numbers in a range [2, n^(1/3)]
and try to reduce the time complexity of prime factorization.
We will split our number n into two numbers x and y => x * y = n.
And x contains prime factors up to n^(1/3) and y deals with higher prime factors greater than n^(1/3).
Thus gcd(x, y) = 1.
Now define F(n) as the number of prime factors of n.
From multiplicative rules, we can say that
F(x * y) = F(x) * F(y), if gcd(x, y) = 1.
For finding F(n) => F(x * y) = F(x) * F(y)
So first find F(x) then F(y) will F(n/x)
And there will 3 cases to cover for y:
1. y is a prime number: F(y) = 2.
2. y is the square of a prime number: F(y) = 3.
3. y is a product of two distinct prime numbers: F(y) = 4.
So once we are done with finding F(x) and F(y), we are also done with finding F(x * y) or F(n).
In Cp-Algorithm there is also a nice explanation of how to count the number of divisors on a number. And also in GeeksForGeeks a nice coding example of how to count the number of divisors of a number in an efficient way. One can check the articles and can generate a nice solution to this problem.
C++ implementation
#include <bits/stdc++.h>
using namespace std;
const int maxn = 1e6 + 11;
bool prime[maxn];
bool primesquare[maxn];
int table[maxn]; // for storing primes
void SieveOfEratosthenes()
{
for(int i = 2; i < maxn; i++){
prime[i] = true;
}
for(int i = 0; i < maxn; i++){
primesquare[i] = false;
}
// 1 is not a prime number
prime[1] = false;
for(int p = 2; p * p < maxn; p++){
// If prime[p] is not changed, then
// it is a prime
if(prime[p] == true){
// Update all multiples of p
for(int i = p * 2; i < maxn; i += p){
prime[i] = false;
}
}
}
int j = 0;
for(int p = 2; p < maxn; p++) {
if (prime[p]) {
// Storing primes in an array
table[j] = p;
// Update value in primesquare[p * p],
// if p is prime.
if(p < maxn / p) primesquare[p * p] = true;
j++;
}
}
}
// Function to count divisors
int countDivisors(int n)
{
// If number is 1, then it will have only 1
// as a factor. So, total factors will be 1.
if (n == 1)
return 1;
// ans will contain total number of distinct
// divisors
int ans = 1;
// Loop for counting factors of n
for(int i = 0;; i++){
// table[i] is not less than cube root n
if(table[i] * table[i] * table[i] > n)
break;
// Calculating power of table[i] in n.
int cnt = 1; // cnt is power of prime table[i] in n.
while (n % table[i] == 0){ // if table[i] is a factor of n
n = n / table[i];
cnt = cnt + 1; // incrementing power
}
// Calculating the number of divisors
// If n = a^p * b^q then total divisors of n
// are (p+1)*(q+1)
ans = ans * cnt;
}
// if table[i] is greater than cube root of n
// First case
if (prime[n])
ans = ans * 2;
// Second case
else if (primesquare[n])
ans = ans * 3;
// Third case
else if (n != 1)
ans = ans * 4;
return ans; // Total divisors
}
int main()
{
SieveOfEratosthenes();
int sum = 0;
int n = 5;
for(int i = 1; i <= n; i++){
sum += countDivisors(i);
}
cout << sum << endl;
return 0;
}
Output
n = 4 => 8
n = 5 => 10
Complexity
Time complexity: O(n * log(log(n)) + n * n^(1/3))
Space complexity: O(n)
Thanks, #largest_prime_is_463035818 for pointing out my mistake.
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I have recently learned the FFT algorithm.
I applied it to the problem of fast multiplication of very large natural number following this pseudocode,
Let A be array of length m, w be primitive m-th root of unity.
Goal: produce DFT F(A): evaluation of A at 1, w, w^2,...,w^{m-1}.
FFT(A, m, w)
{
if (m==1) return vector (a_0)
else {
A_even = (a_0, a_2, ..., a_{m-2})
A_odd = (a_1, a_3, ..., a_{m-1})
F_even = FFT(A_even, m/2, w^2) //w^2 is a primitive m/2-th root of unity
F_odd = FFT(A_odd, m/2, w^2)
F = new vector of length m
x = 1
for (j=0; j < m/2; ++j) {
F[j] = F_even[j] + x*F_odd[j]
F[j+m/2] = F_even[j] - x*F_odd[j]
x = x * w
}
return F
}
It works great but I found a better code that does the same job without recursion and also runs much faster.
I have tried to figure out how it works line by line, however, I failed.
I would really appreciate if you can explain me in detail what is happening those first two for loop (not the math part)
Below is the new code
typedef complex<double> base;
void fft(vector<base> &a, bool invert)
{
int n = a.size();
for (int i = 1, j = 0; i < n; i++){
int bit = n >> 1;
for (; j >= bit; bit >>= 1) j -= bit;
j += bit;
if (i < j) swap(a[i], a[j]);
}
for (int len = 2; len <= n; len <<= 1){
double ang = 2 * M_PI / len * (invert ? -1 : 1);
base wlen(cos(ang), sin(ang));
for (int i = 0; i < n; i += len){
base w(1);
for (int j = 0; j < len / 2; j++){
base u = a[i + j], v = a[i + j + len / 2] * w;
a[i + j] = u + v;
a[i + j + len / 2] = u - v;
w *= wlen;
}
}
}
if (invert)
{
for (int i = 0; i < n; i++)
a[i] /= n;
}
}
Cooley–Tukey FFT implementation has beed described hundreds of times.
Wiki page part with non-recursive method.
The first loop is bit reversal part - code repacks source array, swapping element at i-th index with index of reversed bits of i (so for length=8 index 6=110b is swapped with index 3=011b, and index 5=101b remains at the same place).
This reordering allows to treat array in-place, making calculations on pairs, separated by 1,2,4,8... indexes (len/2 step here) with corresponding trigonometric coefficients.
P.S. Your answer contains onlinejudge tag, so such compact implementation is quite good for you purposes. But for real work it is worth to use some highly-optimized library like fftw etc
Is there any way to improve the running time for this program? I get time limit exceed error from the online judge, and it seems like my program is running slow?
So, this is the question for this program: http://www.spoj.com/problems/PRIME1/
My code (language c):
#include <stdio.h>
void FindPrime (int m, int n)
{
int i, prime = 1;
if (m <= n)
{
for (i = m - 1; i > 1; i--)
{
if (m % i == 0)
{
prime = 0;
break;
}
}
if (prime == 1 && m != 1)
printf ("%d\n", m);
FindPrime (m + 1, n);
}
}
int main ()
{
int num1, num2, i, cases;
scanf ("%d", &cases);
while (cases != 0)
{
scanf ("%d %d", &num1, &num2);
FindPrime (num1, num2);
printf ("\n");
cases--;
}
return 0;
}
To solve this question you need to learn "Sieve of Eratosthenes".
First, get the idea of how it works from here. But, this is not enough to solve this question. Since, the complexity of the algorithm is O(n.log(log(n))). Therefore, if we put n = 1000000000. It will surely fail to execute.
Now, time to optimize it. Read it from here. But, we are done yet.
(Please read this section after you are done with the above two) Since we are to find the prime numbers is the range [m,n]. So, first create a list of prime numbers (let's call it primeList) between the range of 2 to 32000 using sieve of Eratosthenes (sqrt(10^9) = 31622.7, which is less then 32000). Now, check for every number k in the range of [m,n]
3.1. If the number k is in the range of 2-32000, and the number is in primeList. Print it.
3.2. If the number k > 32000, and is not divisible by all the numbers which are <= sqrt(k) and also in primeList. Print it. Else, ignore or don't print it. ( mind it '1' is not prime number).
You may check my solution. But, it is implemented slightly different than i explained although the concept applied is same.
Your code it calculating/listing the prime numbers between to numbers m & n cases number of times. Now you algorithm takes O(n) time for each value of m & hence total time taken by your code for a single case is O(n x m) or O(n^2) times..So in total the time taken is cases * O(n^2).. This is bad..Use some better algorithm to ease the complexity..
Check this modified version of Sieve of Eratosthenes
#include <stdio.h>
#define SIZE (int)(sizeof(boolean) / sizeof(int))
int main(){
int up,low;
int i,j;
printf("\nEnter the upper limit: ");
scanf("%d", &up);
printf("\nEnter the lower limit: ");
scanf("%d", &low);
int boolean[up];
int list[up];
for(i = 0; i < SIZE; i++){
boolean[i] = 1;
list[i] = 2 + i;
}
for(i = 0; i <= up; i++){
if (boolean[i] == 1)
for(j = i +1; j < SIZE; j++)
if(list[j] % list[i] == 0)
boolean[j] = 0;
}
for(i = 0; i < SIZE; i++)
if(boolean[i] == 1 && list[i] >= low && list[i] <= up)
printf("%d ", list[i]);
printf("\n");
return 0;
}
This will not visit one number more than once & hence will reduce the complexity in logarithmic scale.
The problem is to find the n-th Catalan number mod m, where m is NOT prime, m = (10^14 + 7). Here are the list of methods that I have tried: (max N = 10,000)
Dynamic programming for table look-up, too slow
Use Catalan formula ncr(2*n, n)/(n + 1), again it wasn't fast enough due to the ncr function, can't speed up using exponentiation squaring because m is not prime.
Hardcode a table of pre-generated Catalans, but it failed due to the file size limit.
Recurrence relation C(i,k) = C(i-1,k-1) + C(i-1,k), this is way too slow
So I wonder is there any other faster algorithm to find the n-th Catalan number that I'm not aware of?
Using Dynamic Programming
void generate_catalan_numbers() {
catalan[1] = 1;
for (int i = 2; i <= MAX_NUMBERS; i++) {
for (int j = 1; j <= i - 1; j++) {
catalan[i] = (catalan[i] + ((catalan[j]) * catalan[i - j]) % MODULO) % MODULO;
}
catalan[i] = catalan[i] % MODULO;
}
}
Using original formula
ull n_choose_r(ull n, ull r) {
if (n < r)
return 0;
if (r > n/2) {
r = n - r;
}
ull result = 1;
ull common_divisor;
for (int i = 1; i <= r; ++i) {
common_divisor = gcd(result, i);
result /= common_divisor;
result *= (n - i + 1) / (i / common_divisor);
}
return result;
}
Using recurrence relation
ull n_choose_r_relation(ull n, ull r) {
for (int i = 0; i <= n + 1; ++i) {
for (int k = 0; k <= r && k <= i; ++k) {
if (k == 0 || k == i) {
ncr[i][k] = 1;
}
else {
ncr[i][k] = (ncr[i - 1][k - 1] + ncr[i - 1][k]) % MODULO;
}
}
}
return ncr[n][r];
}
From an answer I wrote just as this question about computation of nCr got closed, which ended up in the comments instead:
I'm not sure this is the absolute fastest, but it should be efficient enough. The key is that modulo multiplication decomposes, but division doesn't, so one first must reduce the fraction, as follows:
Since n <= 10000, it's very possible to build an array of size 2*n.
Use the Sieve of Eratosthenes to find and store pairs of factors for all composite numbers up to 20000). This step only needs to be done once regardless of how many Catalan numbers are to be calculated.
Make another table of size 2*n which represents the exponent of each factor.
Now, iterate the product in the Catalan formula .
Break each factor into prime factors using the sieve table, incrementing the exponent table for each term in the numerator and decrementing it for each term in the denominator.
No entry will ever end up negative.
Now, use modulo arithmetic to multiply together the non-cancelled factors.
No division operations are required at any point. Nor any fractions.
Demonstration of my method applied to multi-nCr: http://ideone.com/Weeg6
To use this for Catalan numbers, you can use this instead of the loops inside calc_combinations:
for( unsigned k = 2; k <= N; ++k ) {
factor<+1>(k+N);
factor<-1>(k);
}
The code then looks like this: http://ideone.com/ZZApk
Solution
#include <utility>
#include <vector>
std::vector< std::pair<int, int> > factor_table;
void fill_sieve( int n )
{
factor_table.resize(n+1);
for( int i = 1; i <= n; ++i )
factor_table[i] = std::pair<int, int>(i, 1);
for( int j = 2, j2 = 4; j2 <= n; (j2 += j), (j2 += ++j) ) {
if (factor_table[j].second == 1) {
int i = j;
int ij = j2;
while (ij <= n) {
factor_table[ij] = std::pair<int, int>(j, i);
++i;
ij += j;
}
}
}
}
std::vector<unsigned> powers;
template<int dir>
void factor( int num )
{
while (num != 1) {
powers[factor_table[num].first] += dir;
num = factor_table[num].second;
}
}
void calc_catalan(unsigned N)
{
powers.resize(0);
powers.resize(2*N+1);
for( unsigned k = 2; k <= N; ++k ) {
factor<+1>(k+N);
factor<-1>(k);
}
}
Test Driver
#include <iostream>
#include <cmath>
int main(void)
{
fill_sieve(20000);
unsigned N = 9913;
unsigned long long M = 1000000000007LL;
calc_catalan(N);
unsigned long long result = 1;
for( unsigned i = 0; i < powers.size(); ++i ) {
while (powers[i]--) {
result *= i;
result %= M;
}
}
std::cout << "Catalan(" << N << ") modulo " << M << " = " << result << "\n\n";
}
Completed demo: http://ideone.com/FDWfB
Here's another related question, which I answered with code and demonstration: Number of combinations (N choose R) in C++
Easy, peasy. Compute the prime factors of the binomial coefficient. A simple task using a sieve. I won't get into the rest of it, but a powermod computation is trivial, and you don't even need a divide.
For N = 10000, I get 42224403014400 in short order.
But, if you want the full number itself, the 10000'th Catalan number itself is ...
22453781249338521563359358425736057870110358621936588777329371383585
443658870053449099810271911432021020990539379958970114932732650095370271
397751300183876130693653440780258549445459994177372998459176454278220288
679699783327649549651476024591222065426709156831181207130089121989402216
517545144106669143509197596949973192167548893412063804651413496597406903
967719298471463870452875276986356795262033484770727452974197655810423629
386184662262278329466750526865120502476640878488187299740404235631962632
335108916990663560351330901464515744357084282208286669901241545533951877
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