I want to calculate cos(nx) = p/q Using recursion and memoization so i tried Chebyshev Method for Recursive Method it works for small inputs of n but i want to do it for larger inputs like 10^18 etc. How should i approach it to calculate cos(nx) in p/q Form?
For larger Values of n i am getting Memory Problem How do i fix that?
cos(x) = a/b Known
#include <bits/stdc++.h>
using namespace std;
map<long, long> numerator;
map<long, long> denominator;
#define MODULO 1000000007
long a, b, n;
int main() {
cin >> a >> b;
cin >> n;
numerator[0] = 1;
numerator[1] = a;
denominator[0] = 1;
denominator[1] = b;
for (long i = 2; i <= n; ++i) {
numerator[i] = (long) (2 * a * numerator[i - 1] - b*numerator[i - 2]) % MODULO;
denominator[i] = (denominator[i - 1] * denominator[i - 2]) % MODULO;
}
cout << "numerator of cos(nx) = " << numerator[n] << " denominator = " << denominator[n] << endl;
}
lol Thats a contests question you're asking for. Shame on you. That's Codechef's February Challenge's Question. How low can you fall for some rating. smh
This is my code:
#include<cmath>
#include<cstdio>
#include<vector>
#include<iostream>
#include<algorithm>
using namespace std;
int main() {
int t;long long a, b;long long x; //declartion
cin>>t; //1≤T≤1001≤T≤100
if(t<1||t>100)
exit(0);
for(int i=0;i<t;i++){
long long c=0;
cin>>a>>b;
if(a>b||a<1||a>pow(10,9)||b<1) //1≤A≤B≤109
exit(0);
for(long long y=a;y<=b;y++){
x= floor(sqrt(y));
if(pow(x,2)==y){
c++;
}
}cout<<c<<endl;
}
return 0;`
}
Watson gives two integers (AA and BB) to Sherlock and asks if he can count the number of square integers between AA and BB (both inclusive).
Please tell me why I am getting error time?
[From comments]
Your code appears to run slower than the allowed time line. You can use the following algorithm to speed up.
1. sz = 0, arr[sqrt(1000 * 1000 * 1000) + 5]
2. While sz * sz < (1000 * 1000 * 1000)
2.1 arr[sz] = sz * sz
2.2 sz = sz + 1
3. Read T, repeat for all T
3.1 Read aa and bb
3.2 Use binary search to find upperbound of aa and bb in arr.
3.3 Print the difference of indices
If I boil down to following lines of code in C++:
int ai = isqrt(aa), bi = isqrt(bb);
return bi - ai + 1;
You can find the algorithm for isqrt # Methods_of_computing_square_roots
int isqrt(int num) {
int res = 0;
int bit = 1 << 30;
while (bit > num)
bit >>= 2;
while (bit != 0) {
if (num >= res + bit) {
num -= res + bit;
res = (res >> 1) + bit;
}
else
res >>= 1;
bit >>= 2;
}
return res;
}
I have made a recursive function in c++ which deals with very large integers.
long long int findfirst(int level)
{
if(level==1)
return 1;
else if(level%2==0)
return (2*findfirst(--level));
else
return (2*findfirst(--level)-1);
}
when the input variable(level) is high,it reaches the limit of long long int and gives me wrong output.
i want to print (output%mod) where mod is 10^9+7(^ is power) .
int main()
{
long long int first = findfirst(143)%1000000007;
cout << first;
}
It prints -194114669 .
Normally online judges problem don't require the use of large integers (normally meaning almost always), if your solution need large integers probably is not the best solution to solve the problem.
Some notes about modular arithmetic
if a1 = b1 mod n and a2 = b2 mod n then:
a1 + a2 = b1 + b2 mod n
a1 - a2 = b1 - b2 mod n
a1 * a2 = b1 * b2 mod n
That mean that modular arithmetic is transitive (a + b * c) mod n could be calculated as (((b mod n) * (c mod n)) mod n + (a mod n)) mod n, I know there a lot of parenthesis and sub-expression but that is to avoid integer overflow as much as we can.
As long as I understand your program you don't need recursion at all:
#include <iostream>
using namespace std;
const long long int mod_value = 1000000007;
long long int findfirst(int level) {
long long int res = 1;
for (int lev = 1; lev <= level; lev++) {
if (lev % 2 == 0)
res = (2*res) % mod_value;
else
res = (2*res - 1) % mod_value;
}
return res;
}
int main() {
for (int i = 1; i < 143; i++) {
cout << findfirst(i) << endl;
}
return 0;
}
If you need to do recursion modify you solution to:
long long int findfirst(int level) {
if (level == 1)
return 1;
else if (level % 2 == 0)
return (2 * findfirst(--level)) % mod_value;
else
return (2 * findfirst(--level) - 1) % mod_value;
}
Where mod_value is the same as before:
Please make a good study of modular arithmetic and apply in the following online challenge (the reward of discovery the solution yourself is to high to let it go). Most of the online challenge has a mathematical background.
If the problem is (as you say) it overflows long long int, then use an arbitrary precision Integer library. Examples are here.
I want to find (n choose r) for large integers, and I also have to find out the mod of that number.
long long int choose(int a,int b)
{
if (b > a)
return (-1);
if(b==0 || a==1 || b==a)
return(1);
else
{
long long int r = ((choose(a-1,b))%10000007+(choose(a-1,b- 1))%10000007)%10000007;
return r;
}
}
I am using this piece of code, but I am getting TLE. If there is some other method to do that please tell me.
I don't have the reputation to comment yet, but I wanted to point out that the answer by rock321987 works pretty well:
It is fast and correct up to and including C(62, 31)
but cannot handle all inputs that have an output that fits in a uint64_t. As proof, try:
C(67, 33) = 14,226,520,737,620,288,370 (verify correctness and size)
Unfortunately, the other implementation spits out 8,829,174,638,479,413 which is incorrect. There are other ways to calculate nCr which won't break like this, however the real problem here is that there is no attempt to take advantage of the modulus.
Notice that p = 10000007 is prime, which allows us to leverage the fact that all integers have an inverse mod p, and that inverse is unique. Furthermore, we can find that inverse quite quickly. Another question has an answer on how to do that here, which I've replicated below.
This is handy since:
x/y mod p == x*(y inverse) mod p; and
xy mod p == (x mod p)(y mod p)
Modifying the other code a bit, and generalizing the problem we have the following:
#include <iostream>
#include <assert.h>
// p MUST be prime and less than 2^63
uint64_t inverseModp(uint64_t a, uint64_t p) {
assert(p < (1ull << 63));
assert(a < p);
assert(a != 0);
uint64_t ex = p-2, result = 1;
while (ex > 0) {
if (ex % 2 == 1) {
result = (result*a) % p;
}
a = (a*a) % p;
ex /= 2;
}
return result;
}
// p MUST be prime
uint32_t nCrModp(uint32_t n, uint32_t r, uint32_t p)
{
assert(r <= n);
if (r > n-r) r = n-r;
if (r == 0) return 1;
if(n/p - (n-r)/p > r/p) return 0;
uint64_t result = 1; //intermediary results may overflow 32 bits
for (uint32_t i = n, x = 1; i > r; --i, ++x) {
if( i % p != 0) {
result *= i % p;
result %= p;
}
if( x % p != 0) {
result *= inverseModp(x % p, p);
result %= p;
}
}
return result;
}
int main() {
uint32_t smallPrime = 17;
uint32_t medNum = 3001;
uint32_t halfMedNum = medNum >> 1;
std::cout << nCrModp(medNum, halfMedNum, smallPrime) << std::endl;
uint32_t bigPrime = 4294967291ul; // 2^32-5 is largest prime < 2^32
uint32_t bigNum = 1ul << 24;
uint32_t halfBigNum = bigNum >> 1;
std::cout << nCrModp(bigNum, halfBigNum, bigPrime) << std::endl;
}
Which should produce results for any set of 32-bit inputs if you are willing to wait. To prove a point, I've included the calculation for a 24-bit n, and the maximum 32-bit prime. My modest PC took ~13 seconds to calculate this. Check the answer against wolfram alpha, but beware that it may exceed the 'standard computation time' there.
There is still room for improvement if p is much smaller than (n-r) where r <= n-r. For example, we could precalculate all the inverses mod p instead of doing it on demand several times over.
nCr = n! / (r! * (n-r)!) {! = factorial}
now choose r or n - r in such a way that any of them is minimum
#include <cstdio>
#include <cmath>
#define MOD 10000007
int main()
{
int n, r, i, x = 1;
long long int res = 1;
scanf("%d%d", &n, &r);
int mini = fmin(r, (n - r));//minimum of r,n-r
for (i = n;i > mini;i--) {
res = (res * i) / x;
x++;
}
printf("%lld\n", res % MOD);
return 0;
}
it will work for most cases as required by programming competitions if the value of n and r are not too high
Time complexity :- O(min(r, n - r))
Limitation :- for languages like C/C++ etc. there will be overflow if
n > 60 (approximately)
as no datatype can store the final value..
The expansion of nCr can always be reduced to product of integers. This is done by canceling out terms in denominator. This approach is applied in the function given below.
This function has time complexity of O(n^2 * log(n)). This will calculate nCr % m for n<=10000 under 1 sec.
#include <numeric>
#include <algorithm>
int M=1e7+7;
int ncr(int n, int r)
{
r=min(r,n-r);
int A[r],i,j,B[r];
iota(A,A+r,n-r+1); //initializing A starting from n-r+1 to n
iota(B,B+r,1); //initializing B starting from 1 to r
int g;
for(i=0;i<r;i++)
for(j=0;j<r;j++)
{
if(B[i]==1)
break;
g=__gcd(B[i], A[j] );
A[j]/=g;
B[i]/=g;
}
long long ans=1;
for(i=0;i<r;i++)
ans=(ans*A[i])%M;
return ans;
}
Cheers,
I know you can get the amount of combinations with the following formula (without repetition and order is not important):
// Choose r from n
n! / r!(n - r)!
However, I don't know how to implement this in C++, since for instance with
n = 52
n! = 8,0658175170943878571660636856404e+67
the number gets way too big even for unsigned __int64 (or unsigned long long). Is there some workaround to implement the formula without any third-party "bigint" -libraries?
Here's an ancient algorithm which is exact and doesn't overflow unless the result is to big for a long long
unsigned long long
choose(unsigned long long n, unsigned long long k) {
if (k > n) {
return 0;
}
unsigned long long r = 1;
for (unsigned long long d = 1; d <= k; ++d) {
r *= n--;
r /= d;
}
return r;
}
This algorithm is also in Knuth's "The Art of Computer Programming, 3rd Edition, Volume 2: Seminumerical Algorithms" I think.
UPDATE: There's a small possibility that the algorithm will overflow on the line:
r *= n--;
for very large n. A naive upper bound is sqrt(std::numeric_limits<long long>::max()) which means an n less than rougly 4,000,000,000.
From Andreas' answer:
Here's an ancient algorithm which is exact and doesn't overflow unless the result is to big for a long long
unsigned long long
choose(unsigned long long n, unsigned long long k) {
if (k > n) {
return 0;
}
unsigned long long r = 1;
for (unsigned long long d = 1; d <= k; ++d) {
r *= n--;
r /= d;
}
return r;
}
This algorithm is also in Knuth's "The Art of Computer Programming, 3rd Edition, Volume 2: Seminumerical Algorithms" I think.
UPDATE: There's a small possibility that the algorithm will overflow on the line:
r *= n--;
for very large n. A naive upper bound is sqrt(std::numeric_limits<long long>::max()) which means an n less than rougly 4,000,000,000.
Consider n == 67 and k == 33. The above algorithm overflows with a 64 bit unsigned long long. And yet the correct answer is representable in 64 bits: 14,226,520,737,620,288,370. And the above algorithm is silent about its overflow, choose(67, 33) returns:
8,829,174,638,479,413
A believable but incorrect answer.
However the above algorithm can be slightly modified to never overflow as long as the final answer is representable.
The trick is in recognizing that at each iteration, the division r/d is exact. Temporarily rewriting:
r = r * n / d;
--n;
For this to be exact, it means if you expanded r, n and d into their prime factorizations, then one could easily cancel out d, and be left with a modified value for n, call it t, and then the computation of r is simply:
// compute t from r, n and d
r = r * t;
--n;
A fast and easy way to do this is to find the greatest common divisor of r and d, call it g:
unsigned long long g = gcd(r, d);
// now one can divide both r and d by g without truncation
r /= g;
unsigned long long d_temp = d / g;
--n;
Now we can do the same thing with d_temp and n (find the greatest common divisor). However since we know a-priori that r * n / d is exact, then we also know that gcd(d_temp, n) == d_temp, and therefore we don't need to compute it. So we can divide n by d_temp:
unsigned long long g = gcd(r, d);
// now one can divide both r and d by g without truncation
r /= g;
unsigned long long d_temp = d / g;
// now one can divide n by d/g without truncation
unsigned long long t = n / d_temp;
r = r * t;
--n;
Cleaning up:
unsigned long long
gcd(unsigned long long x, unsigned long long y)
{
while (y != 0)
{
unsigned long long t = x % y;
x = y;
y = t;
}
return x;
}
unsigned long long
choose(unsigned long long n, unsigned long long k)
{
if (k > n)
throw std::invalid_argument("invalid argument in choose");
unsigned long long r = 1;
for (unsigned long long d = 1; d <= k; ++d, --n)
{
unsigned long long g = gcd(r, d);
r /= g;
unsigned long long t = n / (d / g);
if (r > std::numeric_limits<unsigned long long>::max() / t)
throw std::overflow_error("overflow in choose");
r *= t;
}
return r;
}
Now you can compute choose(67, 33) without overflow. And if you try choose(68, 33), you'll get an exception instead of a wrong answer.
The following routine will compute the n-choose-k, using the recursive definition and memoization. The routine is extremely fast and accurate:
inline unsigned long long n_choose_k(const unsigned long long& n,
const unsigned long long& k)
{
if (n < k) return 0;
if (0 == n) return 0;
if (0 == k) return 1;
if (n == k) return 1;
if (1 == k) return n;
typedef unsigned long long value_type;
value_type* table = new value_type[static_cast<std::size_t>(n * n)];
std::fill_n(table,n * n,0);
class n_choose_k_impl
{
public:
n_choose_k_impl(value_type* table,const value_type& dimension)
: table_(table),
dimension_(dimension)
{}
inline value_type& lookup(const value_type& n, const value_type& k)
{
return table_[dimension_ * n + k];
}
inline value_type compute(const value_type& n, const value_type& k)
{
if ((0 == k) || (k == n))
return 1;
value_type v1 = lookup(n - 1,k - 1);
if (0 == v1)
v1 = lookup(n - 1,k - 1) = compute(n - 1,k - 1);
value_type v2 = lookup(n - 1,k);
if (0 == v2)
v2 = lookup(n - 1,k) = compute(n - 1,k);
return v1 + v2;
}
value_type* table_;
value_type dimension_;
};
value_type result = n_choose_k_impl(table,n).compute(n,k);
delete [] table;
return result;
}
Remember that
n! / ( n - r )! = n * ( n - 1) * .. * (n - r + 1 )
so it's way smaller than n!. So the solution is to evaluate n* ( n - 1 ) * ... * ( n - r + 1) instead of first calculating n! and then dividing it .
Of course it all depends on the relative magnitude of n and r - if r is relatively big compared to n, then it still won't fit.
Well, I have to answer to my own question. I was reading about Pascal's triangle and by accident noticed that we can calculate the amount of combinations with it:
#include <iostream>
#include <boost/cstdint.hpp>
boost::uint64_t Combinations(unsigned int n, unsigned int r)
{
if (r > n)
return 0;
/** We can use Pascal's triange to determine the amount
* of combinations. To calculate a single line:
*
* v(r) = (n - r) / r
*
* Since the triangle is symmetrical, we only need to calculate
* until r -column.
*/
boost::uint64_t v = n--;
for (unsigned int i = 2; i < r + 1; ++i, --n)
v = v * n / i;
return v;
}
int main()
{
std::cout << Combinations(52, 5) << std::endl;
}
Getting the prime factorization of the binomial coefficient is probably the most efficient way to calculate it, especially if multiplication is expensive. This is certainly true of the related problem of calculating factorial (see Click here for example).
Here is a simple algorithm based on the Sieve of Eratosthenes that calculates the prime factorization. The idea is basically to go through the primes as you find them using the sieve, but then also to calculate how many of their multiples fall in the ranges [1, k] and [n-k+1,n]. The Sieve is essentially an O(n \log \log n) algorithm, but there is no multiplication done. The actual number of multiplications necessary once the prime factorization is found is at worst O\left(\frac{n \log \log n}{\log n}\right) and there are probably faster ways than that.
prime_factors = []
n = 20
k = 10
composite = [True] * 2 + [False] * n
for p in xrange(n + 1):
if composite[p]:
continue
q = p
m = 1
total_prime_power = 0
prime_power = [0] * (n + 1)
while True:
prime_power[q] = prime_power[m] + 1
r = q
if q <= k:
total_prime_power -= prime_power[q]
if q > n - k:
total_prime_power += prime_power[q]
m += 1
q += p
if q > n:
break
composite[q] = True
prime_factors.append([p, total_prime_power])
print prime_factors
Using a dirty trick with a long double, it is possible to get the same accuracy as Howard Hinnant (and probably more):
unsigned long long n_choose_k(int n, int k)
{
long double f = n;
for (int i = 1; i<k+1; i++)
f /= i;
for (int i=1; i<k; i++)
f *= n - i;
unsigned long long f_2 = std::round(f);
return f_2;
}
The idea is to divide first by k! and then to multiply by n(n-1)...(n-k+1). The approximation through the double can be avoided by inverting the order of the for loop.
Improves Howard Hinnant's answer (in this question) a little bit:
Calling gcd() per loop seems a bit slow.
We could aggregate the gcd() call into the last one, while making the most use of the standard algorithm from Knuth's book "The Art of Computer Programming, 3rd Edition, Volume 2: Seminumerical Algorithms":
const uint64_t u64max = std::numeric_limits<uint64_t>::max();
uint64_t choose(uint64_t n, uint64_t k)
{
if (k > n)
throw std::invalid_argument(std::string("invalid argument in ") + __func__);
if (k > n - k)
k = n - k;
uint64_t r = 1;
uint64_t d;
for (d = 1; d <= k; ++d) {
if (r > u64max / n)
break;
r *= n--;
r /= d;
}
if (d > k)
return r;
// Let N be the original n,
// n is the current n (when we reach here)
// We want to calculate C(N,k),
// Currently we already calculated the r value so far:
// r = C(N, n) = C(N, N-n) = C(N, d-1)
// Note that N-n = d-1
// In addition we know the following identity formula:
// C(N,k) = C(N,d-1) * C(N-d+1, k-d+1) / C(k, k-d+1)
// = C(N,d-1) * C(n, k-d+1) / C(k, k-d+1)
// Using this formula, we effectively reduce the calculation,
// while recursively use the same function.
uint64_t b = choose(n, k-d+1);
if (b == u64max) {
return u64max; // overflow
}
uint64_t c = choose(k, k-d+1);
if (c == u64max) {
return u64max; // overflow
}
// Now, the combinatorial should be r * b / c
// We can use gcd() to calculate this:
// We Pick b for gcd: b < r almost (if not always) in all cases
uint64_t g = gcd(b, c);
b /= g;
c /= g;
r /= c;
if (r > u64max / b)
return u64max; // overflow
return r * b;
}
Note that the recursive depth is normally 2 (I don't really see a case goes to 3, the combinatorial reducing is quite decent.), i.e. calling choose() for 3 times, for non-overflow cases.
Replace uint64_t with unsigned long long if you prefer it.
One of SHORTEST way :
int nChoosek(int n, int k){
if (k > n) return 0;
if (k == 0) return 1;
return nChoosek(n - 1, k) + nChoosek(n - 1, k - 1);
}
If you want to be 100% sure that no overflows occur so long as the final result is within the numeric limit, you can sum up Pascal's Triangle row-by-row:
for (int i=0; i<n; i++) {
for (int j=0; j<=i; j++) {
if (j == 0) current_row[j] = 1;
else current_row[j] = prev_row[j] + prev_row[j-1];
}
prev_row = current_row; // assume they are vectors
}
// result is now in current_row[r-1]
However, this algorithm is much slower than the multiplication one. So perhaps you could use multiplication to generate all the cases you know that are 'safe' and then use addition from there. (.. or you could just use a BigInt library).