How to get the result 2^100 * 3^3 in modulo 1000000007 - c

I have a question, how to get a result of (2^100)*(3^5) in modulo 10^9 + 7? The program will ask the user to input the power (2^a) and 3^b, after that, the output will show the result of 2^a * 3^b.
I tried to convert all the big numbers into modulo, and times the modulo. But, it doesnt work for 2*100 * 3^5
#include "stdio.h"
int main()
{
long long int testcase,b,c,N,a;
long long int pow2,pow3 = 1;
long long int m = 1000000007;
// input the power
scanf("%lld",&a); getchar();
scanf("%lld",&b); getchar();
// power of 2 (2^a)
for(int i = 1; i <= a; i++){
pow2 = pow2 * 2;
}
// power of 3 (3^b)
for(int j = 1; j <= b; j++){
pow3 = pow3 * 3;
}
// convert the big numbers into modulo
long long int i = 1;
i = (1*pow2) % m ;
long long int j = 1;
j = (1*pow3) % m;
// the result of first modulo times second modulo
printf("%lld\n", i*j);
// doesnt work for 2^100 * 3^5
return 0;
}
For a = 2 and b = 5 its gives the output of 972 (which is correct)
for a = 100 and b = 3 its gives 0 output.

Firstly, pow2 is uninitialized and therefore the behaviour is undefined. If initialized to 1, then the problem is that 2^100 does not fit in the long long int. The best fix is to take the modulo as often as possible.
// power of 2 (2^a)
for(int i = 1; i <= a; i++){
pow2 *= 2;
pow2 %= m;
}
// power of 3 (3^b)
for(int j = 1; j <= b; j++){
pow3 *= 3;
pow3 %= m;
}
Notice that this is still suboptimal - it is possible to calculate much larger powers by using exponentiation by squaring.
Finally you must note that the last product must be mod 1000000007 too, otherwise the result is larger than expected:
printf("%lld\n", i * j % m);

Related

Failed to reuse variable in C

I'm trying to code a program that can tell apart real and fake credit card numbers using Luhn's algorithm in C, which is
Multiply every other digit by 2, starting with the number’s
second-to-last digit, and then add those products’ digits together.
Add the sum to the sum of the digits that weren’t multiplied by 2.
If the total’s last digit is 0 (or, put more formally, if the total
modulo 10 is congruent to 0), the number is valid!
Then I coded something like this (I already declared all the functions at the top and included all the necessary libraries)
//Luhn's Algorithm
int luhn(long z)
{
int c;
return c = (sumall(z)-sumodd(z)) * 2 + sumaodd(z);
}
//sum of digits in odd position starting from the end
int sumodd(long x)
{
int a;
while(x)
{
a = a + x % 10;
x /= 100;
}
return a;
}
//sum of all digits
int sumall(long y)
{
int b;
while(y)
{
b = b + y % 10;
y /= 10;
}
return b;
}
But somehow it always gives out the wrong answer even though there's no error or bug detected. I came to notice that it works fine when my variable z stands alone, but when it's used multiple times in the same line of code with different functions, their values get messed up (in function luhn). I'm writing this to ask for any fix I can make to make my code run correctly as I intended.
I'd appreciate any help as I'm very new to this, and I'm not a native English speaker so I may have messed up some technical terms, but I hope you'd be able to understand my concerns.
sumall is wrong.
It should be sumeven from:
Add the sum to the sum of the digits that weren’t multiplied by 2.
Your sumall is summing all digits instead of the non-odd (i.e. even) digits.
You should do the * 2 inside sumodd as it should not be applied to the other [even] sum. And, it should be applied to the individual digits [vs the total sum].
Let's start with a proper definition from https://en.wikipedia.org/wiki/Luhn_algorithm
The check digit is computed as follows:
If the number already contains the check digit, drop that digit to form the "payload." The check digit is most often the last digit.
With the payload, start from the rightmost digit. Moving left, double the value of every second digit (including the rightmost digit).
Sum the digits of the resulting value in each position (using the original value where a digit did not get doubled in the previous step).
The check digit is calculated by 10 − ( s mod ⁡ 10 )
Note that if we have a credit card of 9x where x is the check digit, then the payload is 9.
The correct [odd] sum for that digit is: 9 * 2 --> 18 --> 1 + 8 --> 9
But, sumodd(9x) * 2 --> 9 * 2 --> 18
Here's what I came up with:
// digsum -- calculate sum of digits
static inline int
digsum(int digcur)
{
int sum = 0;
for (; digcur != 0; digcur /= 10)
sum += digcur % 10;
return sum;
}
// luhn -- luhn's algorithm using digits array
int
luhn(long z)
{
char digits[16] = { 0 };
// get check digit and remove from "payload"
int check_expected = z % 10;
z /= 10;
// split into digits (we use little-endian)
int digcnt = 0;
for (digcnt = 0; z != 0; ++digcnt, z /= 10)
digits[digcnt] = z % 10;
int sum = 0;
for (int digidx = 0; digidx < digcnt; ++digidx) {
int digcur = digits[digidx];
if ((digidx & 1) == 0)
sum += digsum(digcur * 2);
else
sum += digcur;
}
int check_actual = 10 - (sum % 10);
return (check_actual == check_expected);
}
// luhn -- luhn's algorithm using long directly
int
luhn2(long z)
{
// get check digit and remove from "payload"
int check_expected = z % 10;
z /= 10;
int sum = 0;
for (int digidx = 0; z != 0; ++digidx, z /= 10) {
int digcur = z % 10;
if ((digidx & 1) == 0)
sum += digsum(digcur * 2);
else
sum += digcur;
}
int check_actual = 10 - (sum % 10);
return (check_actual == check_expected);
}
You've invoked undefined behavior by not initializing a few local variables in your functions, for instance you can remove your undefined behaviour in sumodd() by initializing a to zero like so:
//sum of digits in odd position starting from the end
int sumodd(long x)
{
int a = 0; //Initialize
while(x)
{
a += x % 10; //You can "a += b" instead of "a = a + b"
x /= 100;
}
return a;
}
It's also important to note that long is only required to be a minimum of 4-bytes wide, so it is not guaranteed to be wide enough to represent a decimal-16-digit-integer. Using long long solves this problem.
Alternatively you may find this problem much easier to solve by treating your credit card number as a char[] instead of an integer type altogether, for instance if we assume a 16-digit credit card number:
int luhn(long long z){
char number[16]; //Convert CC number to array of digits and store them here
for(int c = 0; c < 16; ++c){
number[c] = z % 10; //Last digit is at number[0], first digit is at number[15]
z /= 10;
}
int sum = 0;
for(int c = 0; c < 16; c += 2){
sum += number[c] + number[c + 1] * 2; //Sum the even digits and the doubled odd digits
}
return sum;
}
...and you could skip the long long to char[] translation part altogether if you treat the credit card number as an array of digits in the whole program
This expression:
(sumall(z)-sumodd(z)) * 2 + sumall(z);
Should be:
((sumall(z)-sumodd(z)) * 2 + sumodd(z))%10;
Based on your own definition.
But how about:
(sumall(z) * 2 - sumodd(z))%10
If you're trying to be smart and base off sumall(). You don't need to call anything twice.
Also you don't initialise your local variables. You must assign variables values before using them in C.
Also you don't need the local variable c in the luhn() function. It's harmless but unnecessary.
As others mention in a real-world application we can't recommend enough that such 'codes' are held in a character array. The amount of grief caused by people using integer types to represent digit sequence 'codes' and identifiers is vast. Unless a variable represents a numerical quantity of something, don't represent it as an arithmetic type. More issue has been caused in my career by that error than people trying to use double to represent monetary amounts.
#include <stdio.h>
//sum of digits in odd position starting from the end
int sumodd(long x)
{
int a=0;
while(x)
{
a = a + x % 10;
x /= 100;
}
return a;
}
//sum of all digits
int sumall(long y)
{
int b=0;
while(y)
{
b = b + y % 10;
y /= 10;
}
return b;
}
//Luhn's Algorithm
int luhn(long z)
{
return (sumall(z)*2-sumodd(z))%10;
}
int check_luhn(long y,int expect){
int result=luhn(y);
if(result==expect){
return 0;
}
return 1;
}
int check_sumodd(long y,int expect){
int result=sumodd(y);
if(result==expect){
return 0;
}
return 1;
}
int check_sumall(long y,int expect){
int result=sumall(y);
if(result==expect){
return 0;
}
return 1;
}
int main(void) {
int errors=0;
errors+=check_sumall(1,1);
errors+=check_sumall(12,3);
errors+=check_sumall(123456789L,45);
errors+=check_sumall(4273391,4+2+7+3+3+9+1);
errors+=check_sumodd(1,1);
errors+=check_sumodd(91,1);
errors+=check_sumodd(791,8);
errors+=check_sumodd(1213191,1+1+1+1);
errors+=check_sumodd(4273391,15);
errors+=check_luhn(1234567890,((9+7+5+3+1)*2+(0+8+6+4+2))%10);
errors+=check_luhn(9264567897,((9+7+5+6+9)*2+(7+8+6+4+2))%10);
if(errors!=0){
printf("*ERRORS*\n");
}else{
printf("Success\n");
}
return 0;
}

How to Optimise my code that computes the sum of all from less than 2 million

I've tried this problem from Project Euler where I need to calculate the sum of all primes until two million.
This is the solution I've come up with -
#include <stdio.h>
int main() {
long sum = 5; // Already counting 2 and 3 in my sum.
int i = 5; // Checking from 5
int count = 0;
while (i <= 2000000) {
count = 0;
for (int j = 3; j <= i / 2; j += 2) {
// Checking if i (starting from 5) is divisible from 3
if (i % j == 0) { // to i/2 and only checking for odd values of j
count = 1;
}
}
if (count == 0) {
sum += i;
}
i += 2;
}
printf("%ld ", sum);
}
It takes around 480 secs to run and I was wondering if there was a better solution or tips to improve my program.
________________________________________________________
Executed in 480.95 secs fish external
usr time 478.54 secs 0.23 millis 478.54 secs
sys time 1.28 secs 6.78 millis 1.28 secs
With two little modifications your code becomes magnitudes faster:
#include <stdio.h>
#include <math.h>
int main() {
long long sum = 5; // we need long long, long might not be enough
// depending on your platform
int i = 5;
int count = 0;
while (i <= 2000000) {
count = 0;
int limit = sqrt(i); // determine upper limit once and for all
for (int j = 3; j <= limit; j += 2) { // use upper limit sqrt(i) instead if i/2
if (i % j == 0) {
count = 1;
break; // break out from loop as soon
// as number is not prime
}
}
if (count == 0) {
sum += i;
}
i += 2;
}
printf("%lld ", sum); // we need %lld for long long
}
All explanations are in the comments.
But there are certainly better and even faster ways to do this.
I ran this on my 10 year old MacPro and for the 20 million first primes it took around 30 seconds.
This program computes near instantly (even in Debug...) the sum for 2 millions, just need one second for 20 millions (Windows 10, 10 years-old i7 # 3.4 GHz, MSVC 2019).
Note: Didn't had time to set up my C compiler, it's why there is a cast on the malloc.
The "big" optimization is to store square values AND prime numbers, so absolutely no impossible divisor is tested. Since there is no more than 1/10th of primes within a given integer interval (heuristic, a robust code should test that and realloc the primes array when needed), the time is drastically cut.
#include <stdio.h>
#include <malloc.h>
#define LIMIT 2000000ul // Computation limit.
typedef struct {
unsigned long int p ; // Store a prime number.
unsigned long int sq ; // and its square.
} prime ;
int main() {
prime* primes = (prime*)malloc((LIMIT/10)*sizeof(*primes)) ; // Store found primes. Can quite safely use 1/10th of the whole computation limit.
unsigned long int primes_count=1 ;
unsigned long int i = 3 ;
unsigned long long int sum = 0 ;
unsigned long int j = 0 ;
int is_prime = 1 ;
// Feed the first prime, 2.
primes[0].p = 2 ;
primes[0].sq = 4 ;
sum = 2 ;
// Parse all numbers up to LIMIT, ignoring even numbers.
// Also reset the "is_prime" flag at each loop.
for (i = 3 ; i <= LIMIT ; i+=2, is_prime = 1 ) {
// Parse all previously found primes.
for (j = 0; j < primes_count; j++) {
// Above sqrt(i)? Break, i is a prime.
if (i<primes[j].sq)
break ;
// Found a divisor? Not a prime (and break).
if ((i % primes[j].p == 0)) {
is_prime = 0 ;
break ;
}
}
// Add the prime and its square to the array "primes".
if (is_prime) {
primes[primes_count].p = i ;
primes[primes_count++].sq = i*i ;
// Compute the sum on-the-fly
sum += i ;
}
}
printf("Sum of all %lu primes: %llu\n", primes_count, sum);
free(primes) ;
}
Your program can easily be improved by stopping the inner loop earlier:
when i exceeds sqrt(j).
when a divisor has been found.
Also note that type long might not be large enough for the sum on all architectures. long long is recommended.
Here is a modified version:
#include <stdio.h>
int main() {
long long sum = 5; // Already counting 2 and 3 in my sum.
long i = 5; // Checking from 5
while (i <= 2000000) {
int count = 0;
for (int j = 3; j * j <= i; j += 2) {
// Checking if i (starting from 5) is divisible from 3
if (i % j == 0) { // to i/2 and only checking for odd values of j
count = 1;
break;
}
}
if (count == 0) {
sum += i;
}
i += 2;
}
printf("%lld\n", sum);
}
This simple change drastically reduces the runtime! It is more than 1000 times faster for 2000000:
chqrlie> time ./primesum
142913828922
real 0m0.288s
user 0m0.264s
sys 0m0.004s
Note however that trial division is much less efficient than the classic sieve of Eratosthenes.
Here is a simplistic version:
#include <stdio.h>
#include <stdlib.h>
int main() {
long max = 2000000;
long long sum = 0;
// Allocate an array of indicators initialized to 0
unsigned char *composite = calloc(1, max + 1);
// For all numbers up to sqrt(max)
for (long i = 2; i * i <= max; i++) {
// It the number is a prime
if (composite[i] == 0) {
// Set all multiples as composite. Multiples below the
// square of i are skipped because they have already been
// set as multiples of a smaller prime.
for (long j = i * i; j <= max; j += i) {
composite[j] = 1;
}
}
}
for (long i = 2; i <= max; i++) {
if (composite[i] == 0)
sum += i;
}
printf("%lld\n", sum);
free(composite);
return 0;
}
This code is another 20 times faster for 2000000:
chqrlie> time ./primesum-sieve
142913828922
real 0m0.014s
user 0m0.007s
sys 0m0.002s
The sieve approach can be further improved in many ways for larger boundaries.

Is it possible to increment the modulo operator in later loop iterations?

I am trying to construct a simple program which adds together the digits of a long number. I attempted to do this by using a loop employing the modulo operator and some basic arithmetic. I want to increment the modulo operator by multiplying it by ten on each iteration of the loop in order to reach the next digit. I want to check if my code is correct, however, I receive errors pertaining to the lines involving the modulo operations and I'm not quite sure why.
This was my attempted construction:
{
long i = 0;
long b;
int m = 1;
do
{
long number = get_long("Number?\n");
long a = number % m;
b = number - a;
long c = b % m x 10;
long d = c / m;
{
i = i + d;
}
{
m = m x 10
}
}
while (b > 0);
printf("%ld\n", i);
}
Edit:
I made the basic error of writing "x" instead of "*". However, having fixed this, I no longer receive errors, but the program simply returns "0". Any diagnosis would be appreciated.
int main(void)
{
long i = 0;
long b;
int m = 10;
long number = get_long("Number?\n");
do
{
long a = number % m;
b = number - a;
long c = b % m * 10;
long d = c / m;
{
i = i + d;
}
{
m = m * 10;
}
}
while (b > 0);
printf("%ld\n", i);
}
For your revised code:
long c = b % m * 10;
this line will evaluate (b % m) and then multiply it by 10 because of the order of operations.
I presume what you actually want is:
long c = b % (m * 10);
Secondly, the following line determines which digit you start at:
int m = 10;
and this line determines how many digits between the ones you include in your total:
m = m * 10;
So for this configuration, it will start at the 2nd digit from the right and add every digit.
So for the number 1234, you'd get 3 + 2 + 1 = 6.
If you want to add every digit, you could set:
int m = 10;
and you'd get 4 + 3 + 2 + 1 = 10.
Alternatively, if you had used:
m = m * 10;
you'd have 3 + 1 = 4.
First, you're likely getting errors due to these lines:
long c = b % m x 10;
m = m x 10
This is because x is not a valid operator.
The multiplication operator is *:
long c = b % m * 10;
m = m * 10;
As for your approach, I would suggest, instead of changing the modulo operand, you simply divide the original number by 10 to shift it one digit each operation.
For example:
#include <stdio.h>
int main()
{
int sumofdigits = 0;
int num = 12345;
while(num > 0) {
sumofdigits += num % 10;
num /= 10;
}
printf("%d", sumofdigits);
return 0;
}
The reduced-sum of the digits of a number is the same as that number modulo 9.
Example:
#include <stdio.h>
int main(void) {
int number = 57283;
printf("%d \n", number%9);
// 5 + 7 + 2 + 8 + 3 == 25 ==> 2 + 5 == 7
// 57283 % 9 == 7
return 0;
}
If you want to use loops to get the reduced sum:
int sum_of_digits(int num)
{
int sum;
do
{
sum = 0;
while(num)
{
sum += num%10;
num /= 10;
}
num = sum;
} while (sum >9);
return sum;
}
But if you only want the simple sum of digits (one pass only):
int sum_of_digits(int num)
{
int sum = 0;
while(num)
{
sum += num%10;
num /= 10;
}
return sum;
}
You have to find the sum of the digits of a variable of type long by the two operators modulo (%) and division (/), you start with the operator modulo to find the remainder of the division (the digits) then, you add this degit to the sum, then you do the division / 10 to overwrite (the summed digit) until the number is equal to 0 like this:
int main()
{
long number=0,m=0;
printf("Give a number :");
scanf("%ld",&number);
long s=0,temp=number;
while(number != 0)
{
m=number%10;
s+=m;
number/=10;
}
printf("\n%The sum of the digits of the Number %ld is : %ld\n",temp,s);
}

Optimizing calculating combination and avoiding overflows

I am solving a programming problem which is stuck at calculating nCr efficiently and at the same time avoiding overflows. I have made the following trivial simplification but am just curious about if there are any more sophisticated simplifications available out there.
(n)!/(n-k)!*k! = n*(n-1)*.....*(max(n-k+1, k))/(min(n-k, k-1))
Can there be any more simplification possible considering different cases for k as even or odd, just suggesting a way.
Any comment is appreciated.
I found an interesting solution here: http://blog.plover.com/math/choose.html
unsigned choose(unsigned n, unsigned k) {
unsigned r = 1;
unsigned d;
if (k > n) return 0;
for (d=1; d <= k; d++) {
r *= n--;
r /= d;
}
return r;
}
This avoids overflows (or at least limits the problem) by performing multiplication and division alternatively.
E.g. for n = 8, k = 4:
result = 1;
result *= 8;
result /= 1;
result *= 7;
result /= 2;
result *= 6;
result /= 3;
result *= 5;
result /= 4;
done
I had to solve this problem, too. What I did was use the fact that there are the same number of multiplications as divisions and bundled them together, taking one multiplication and one division at a time. It comes out as an integer at the end, but I use double for the intermediate terms and then round to the nearest integer at the end.
// Return the number of combinations of 'n choose k'
unsigned int binomial(unsigned int n, unsigned int k) {
unsigned int higher_idx;
unsigned int lower_idx;
if(k > n-k) {
higher_idx = k;
lower_idx = n - k;
} else {
higher_idx = n - k;
lower_idx = k;
}
double product = 1.0;
double factor;
unsigned int idx;
for(idx=n; idx>higher_idx; idx--) {
factor = (double)idx / double(lower_idx - (n - idx));
product *= factor;
}
return (unsigned int)(product + 0.5);
}

Print large base 256 array in base 10 in c

I have an array of unsigned chars in c I am trying to print in base 10, and I am stuck. I think this will be better explained in code, so, given:
unsigned char n[3];
char[0] = 1;
char[1] = 2;
char[2] = 3;
I would like to print 197121.
This is trivial with small base 256 arrays. One can simply 1 * 256 ^ 0 + 2 * 256 ^ 1 + 3 * 256 ^ 2.
However, if my array was 100 bytes large, then this quickly becomes a problem. There is no integral type in C that is 100 bytes large, which is why I'm storing numbers in unsigned char arrays to begin with.
How am I supposed to efficiently print this number out in base 10?
I am a bit lost.
There's no easy way to do it using only the standard C library. You'll either have to write the function yourself (not recommended), or use an external library such as GMP.
For example, using GMP, you could do:
unsigned char n[100]; // number to print
mpz_t num;
mpz_import(num, 100, -1, 1, 0, 0, n); // convert byte array into GMP format
mpz_out_str(stdout, 10, num); // print num to stdout in base 10
mpz_clear(num); // free memory for num
When I saw this question, I purpose to solve it, but at that moment I was very busy.
This last weekend I've could gain some prize hours of free time so I considered my pending challenge.
First of all, I suggest you to considered above response. I never use GMP library but I'm sure that it's better solution than a handmade code.
Also, you could be interest to analyze code of bc calculator; it can works with big numbers and I used to test my own code.
Ok, if you are still interested in a code do it by yourself (only with support C language and Standard C library) may be I can give you something.
Before all, a little bit theory. In basic numeric theory (modular arithmetic level) theres is an algorithm that inspire me to arrive at one solution; Multiply and Power algorithm to solve a^N module m:
Result := 1;
for i := k until i = 0
if n_i = 1 then Result := (Result * a) mod m;
if i != 0 then Result := (Result * Result) mod m;
end for;
Where k is number of digits less one of N in binary representation, and n_i is i binary digit. For instance (N is exponent):
N = 44 -> 1 0 1 1 0 0
k = 5
n_5 = 1
n_4 = 0
n_3 = 1
n_2 = 1
n_1 = 0
n_0 = 0
When we make a module operation, as an integer division, we can lose part of the number, so we only have to modify algorithm to don't miss relevant data.
Here is my code (take care that it is an adhoc code, strong dependency of may computer arch. Basically I play with data length of C language so, be carefully because my data length could not be the same):
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <math.h>
enum { SHF = 31, BMASK = 0x1 << SHF, MODULE = 1000000000UL, LIMIT = 1024 };
unsigned int scaleBigNum(const unsigned short scale, const unsigned int lim, unsigned int *num);
unsigned int pow2BigNum(const unsigned int lim, unsigned int *nsrc, unsigned int *ndst);
unsigned int addBigNum(const unsigned int lim1, unsigned int *num1, const unsigned int lim2, unsigned int *num2);
unsigned int bigNum(const unsigned short int base, const unsigned int exp, unsigned int **num);
int main(void)
{
unsigned int *num, lim;
unsigned int *np, nplim;
int i, j;
for(i = 1; i < LIMIT; ++i)
{
lim = bigNum(i, i, &num);
printf("%i^%i == ", i, i);
for(j = lim - 1; j > -1; --j)
printf("%09u", num[j]);
printf("\n");
free(num);
}
return 0;
}
/*
bigNum: Compute number base^exp and store it in num array
#base: Base number
#exp: Exponent number
#num: Pointer to array where it stores big number
Return: Array length of result number
*/
unsigned int bigNum(const unsigned short int base, const unsigned int exp, unsigned int **num)
{
unsigned int m, lim, mem;
unsigned int *v, *w, *k;
//Note: mem has the exactly amount memory to allocate (dinamic memory version)
mem = ( (unsigned int) (exp * log10( (float) base ) / 9 ) ) + 3;
v = (unsigned int *) malloc( mem * sizeof(unsigned int) );
w = (unsigned int *) malloc( mem * sizeof(unsigned int) );
for(m = BMASK; ( (m & exp) == 0 ) && m; m >>= 1 ) ;
v[0] = (m) ? 1 : 0;
for(lim = 1; m > 1; m >>= 1)
{
if( exp & m )
lim = scaleBigNum(base, lim, v);
lim = pow2BigNum(lim, v, w);
k = v;
v = w;
w = k;
}
if(exp & 0x1)
lim = scaleBigNum(base, lim, v);
free(w);
*num = v;
return lim;
}
/*
scaleBigNum: Make an (num[] <- scale*num[]) big number operation
#scale: Scalar that multiply big number
#lim: Length of source big number
#num: Source big number (array of unsigned int). Update it with new big number value
Return: Array length of operation result
Warning: This method can write in an incorrect position if we don't previous reallocate num (if it's necessary). bigNum method do it for us
*/
unsigned int scaleBigNum(const unsigned short scale, const unsigned int lim, unsigned int *num)
{
unsigned int i;
unsigned long long int n, t;
for(n = 0, t = 0, i = 0; i < lim; ++i)
{
t = (n / MODULE);
n = ( (unsigned long long int) scale * num[i] );
num[i] = (n % MODULE) + t; // (n % MODULE) + t always will be smaller than MODULE
}
num[i] = (n / MODULE);
return ( (num[i]) ? lim + 1 : lim );
}
/*
pow2BigNum: Make a (dst[] <- src[] * src[]) big number operation
#lim: Length of source big number
#src: Source big number (array of unsigned int)
#dst: Destination big number (array of unsigned int)
Return: Array length of operation result
Warning: This method can write in an incorrect position if we don't previous reallocate num (if it's necessary). bigNum method do it for us
*/
unsigned int pow2BigNum(const unsigned int lim, unsigned int *src, unsigned int *dst)
{
unsigned int i, j;
unsigned long long int n, t;
unsigned int k, c;
for(c = 0, dst[0] = 0, i = 0; i < lim; ++i)
{
for(j = i, n = 0; j < lim; ++j)
{
n = ( (unsigned long long int) src[i] * src[j] );
k = i + j;
if(i != j)
{
t = 2 * (n % MODULE);
n = 2 * (n / MODULE);
// (i + j)
dst[k] = ( (k > c) ? ((c = k), 0) : dst[k] ) + (t % MODULE);
++k; // (i + j + 1)
dst[k] = ( (k > c) ? ((c = k), 0) : dst[k] ) + ( (t / MODULE) + (n % MODULE) );
++k; // (i + j + 2)
dst[k] = ( (k > c) ? ((c = k), 0) : dst[k] ) + (n / MODULE);
}
else
{
dst[k] = ( (k > c) ? ((c = k), 0) : dst[k] ) + (n % MODULE);
++k; // (i + j)
dst[k] = ( (k > c) ? ((c = k), 0) : dst[k] ) + (n / MODULE);
}
for(k = i + j; k < (lim + j); ++k)
{
dst[k + 1] += (dst[k] / MODULE);
dst[k] %= MODULE;
}
}
}
i = lim << 1;
return ((dst[i - 1]) ? i : i - 1);
}
/*
addBigNum: Make a (num2[] <- num1[] + num2[]) big number operation
#lim1: Length of source num1 big number
#num1: First source operand big number (array of unsigned int). Should be smaller than second
#lim2: Length of source num2 big number
#num2: Second source operand big number (array of unsigned int). Should be equal or greater than first
Return: Array length of operation result or 0 if num1[] > num2[] (dosen't do any op)
Warning: This method can write in an incorrect position if we don't previous reallocate num2
*/
unsigned int addBigNum(const unsigned int lim1, unsigned int *num1, const unsigned int lim2, unsigned int *num2)
{
unsigned long long int n;
unsigned int i;
if(lim1 > lim2)
return 0;
for(num2[lim2] = 0, n = 0, i = 0; i < lim1; ++i)
{
n = num2[i] + num1[i] + (n / MODULE);
num2[i] = n % MODULE;
}
for(n /= MODULE; n; ++i)
{
num2[i] += n;
n = (num2[i] / MODULE);
}
return (lim2 > i) ? lim2 : i;
}
To compile:
gcc -o bgn <name>.c -Wall -O3 -lm //Math library if you wants to use log func
To check result, use direct output as and input to bc. Easy shell script:
#!/bin/bash
select S in ` awk -F '==' '{print $1 " == " $2 }' | bc`;
do
0;
done;
echo "Test Finished!";
We have and array of unsigned int (4 bytes) where we store at each int of array a number of 9 digits ( % 1000000000UL ); hence num[0] we will have the first 9 digits, num[1] we will have digit 10 to 18, num[2]...
I use convencional memory to work but an improvement can do it with dinamic memory. Ok, but how length It could be the array? (or how many memory we need to allocate?). Using bc calculator (bc -l with mathlib) we can determine how many digits has a number:
l(a^N) / l(10) // Natural logarith to Logarithm base 10
If we know digits, we know amount integers we needed:
( l(a^N) / (9 * l(10)) ) + 1 // Truncate result
If you work with value such as (2^k)^N you can resolve it logarithm with this expression:
( k*N*l(2)/(9*l(10)) ) + 1 // Truncate result
to determine the exactly length of integer array. Example:
256^800 = 2^(8*800) ---> l(2^(8*800))/(9*l(10)) + 1 = 8*800*l(2)/(9*l(10)) + 1
The value 1000000000UL (10^9) constant is very important. A constant like 10000000000UL (10^10) dosen't work because can produce and indetected overflow (try what's happens with number 16^16 and 10^10 constant) and a constant more little such as 1000000000UL (10^8) are correct but we need to reserve more memory and do more steps. 10^9 is key constant for unsigned int of 32 bits and unsigned long long int of 64 bits.
The code has two parts, Multiply (easy) and Power by 2 (more hard). Multiply is just multiplication and scale and propagate the integer overflow. It take the principle of associative property in math to do exactly the inverse principle, so if k(A + B + C) we want kA + kB + kC where number will be k*A*10^18 + k*B*10^9 + kC. Obiously, kC operation can generate a number bigger than 999 999 999, but never more bigger than 0xFF FF FF FF FF FF FF FF. A number bigger than 64 bits can never occur in a multiplication because C is an unsigned integer of 32 bits and k is a unsigned short of 16 bits. In worts case, we will have this number:
k = 0x FF FF;
C = 0x 3B 9A C9 FF; // 999999999
n = k*C = 0x 3B 9A | 8E 64 36 01;
n % 1000000000 = 0x 3B 99 CA 01;
n / 1000000000 = 0x FF FE;
After Mul kB we need to add 0x FF FE from last multiplication of C ( B = kB + (C / module) ), and so on (we have 18 bits arithmetic offset, enough to guarantee correct values).
Power is more complex but is in essencial, the same problem (multiplication and add), so I give some tricks about code power:
Data types are important, very important
If you try to multiplication an unsigned integer with unsigned integer, you get another unsigned integer. Use explicit cast to get unsigned long long int and don't lose data.
Always use unsigned modifier, dont forget it!
Power by 2 can directly modify 2 index ahead of current index
gdb is your friend
I've developed another method that add big numbers. These last I don't prove so much but I think it works well. Don't be cruels with me if it has a bug.
...and that's all!
PD1: Developed in a
Intel(R) Pentium(R) 4 CPU 1.70GHz
Data length:
unsigned short: 2
unsigned int: 4
unsigned long int: 4
unsigned long long int: 8
Numbers such as 256^1024 it spend:
real 0m0.059s
user 0m0.033s
sys 0m0.000s
A bucle that's compute i^i where i goes to i = 1 ... 1024:
real 0m40.716s
user 0m14.952s
sys 0m0.067s
For numbers such as 65355^65355, spent time is insane.
PD2: My response is so late but I hope my code it will be usefull.
PD3: Sorry, explain me in english is one of my worst handicaps!
Last update: I just have had an idea that with same algorithm but other implementation, improve response and reduce amount memory to use (we can use the completely bits of unsigned int). The secret: n^2 = n * n = n * (n - 1 + 1) = n * (n - 1) + n.
(I will not do this new code, but if someone are interested, may be after exams... )
I don't know if you still need a solution, but I wrote an article about this problem. It shows a very simple algorithm which can be used to convert an arbitrary long number with base X to a corresponding number of base Y. The algorithm is written in Python, but it is really only a few lines long and doesn't use any Python magic. I needed such an algorithm for a C implementation, too, but decided to describe it using Python for two reasons. First, Python is very readable by anyone who understands algorithms written in a pseudo programming language and, second, I am not allowed to post the C version, because it I did it for my company. Just have a look and you will see how easy this problem can be solved in general. An implementation in C should be straight forward...
Here is a function that does what you want:
#include <math.h>
#include <stddef.h> // for size_t
double getval(unsigned char *arr, size_t len)
{
double ret = 0;
size_t cur;
for(cur = 0; cur < len; cur++)
ret += arr[cur] * pow(256, cur);
return ret;
}
That looks perfectly readable to me. Just pass the unsigned char * array you want to convert and the size. Note that it won't be perfect - for arbitrary precision, I suggest looking into the GNU MP BigNum library, as has been suggested already.
As a bonus, I don't like your storing your numbers in little-endian order, so here's a version if you want to store base-256 numbers in big-endian order:
#include <stddef.h> // for size_t
double getval_big_endian(unsigned char *arr, size_t len)
{
double ret = 0;
size_t cur;
for(cur = 0; cur < len; cur++)
{
ret *= 256;
ret += arr[cur];
}
return ret;
}
Just things to consider.
It may be too late or too irrelevant to make this suggestion, but could you store each byte as two base 10 digits (or one base 100) instead of one base 256? If you haven't implemented division yet, then that implies all you have is addition, subtraction, and maybe multiplication; those shouldn't be too hard to convert. Once you've done that, printing it would be trivial.
As I was not satisfied with the other answers provided, I decided to write an alternative solution myself:
#include <stdlib.h>
#define BASE_256 256
char *largenum2str(unsigned char *num, unsigned int len_num)
{
int temp;
char *str, *b_256 = NULL, *cur_num = NULL, *prod = NULL, *prod_term = NULL;
unsigned int i, j, carry = 0, len_str = 1, len_b_256, len_cur_num, len_prod, len_prod_term;
//Get 256 as an array of base-10 chars we'll use later as our second operand of the product
for ((len_b_256 = 0, temp = BASE_256); temp > 0; len_b_256++)
{
b_256 = realloc(b_256, sizeof(char) * (len_b_256 + 1));
b_256[len_b_256] = temp % 10;
temp = temp / 10;
}
//Our first operand (prod) is the last element of our num array, which we'll convert to a base-10 array
for ((len_prod = 0, temp = num[len_num - 1]); temp > 0; len_prod++)
{
prod = realloc(prod, sizeof(*prod) * (len_prod + 1));
prod[len_prod] = temp % 10;
temp = temp / 10;
}
while (len_num > 1) //We'll stay in this loop as long as we still have elements in num to read
{
len_num--; //Decrease the length of num to keep track of the current element
//Convert this element to a base-10 unsigned char array
for ((len_cur_num = 0, temp = num[len_num - 1]); temp > 0; len_cur_num++)
{
cur_num = (char *)realloc(cur_num, sizeof(char) * (len_cur_num + 1));
cur_num[len_cur_num] = temp % 10;
temp = temp / 10;
}
//Multiply prod by 256 and save that as prod_term
len_prod_term = 0;
prod_term = NULL;
for (i = 0; i < len_b_256; i++)
{ //Repeat this loop 3 times, one for each element in {6,5,2} (256 as a reversed base-10 unsigned char array)
carry = 0; //Set the carry to 0
prod_term = realloc(prod_term, sizeof(*prod_term) * (len_prod + i)); //Allocate memory to save prod_term
for (j = i; j < (len_prod_term); j++) //If we have digits from the last partial product of the multiplication, add it here
{
prod_term[j] = prod_term[j] + prod[j - i] * b_256[i] + carry;
if (prod_term[j] > 9)
{
carry = prod_term[j] / 10;
prod_term[j] = prod_term[j] % 10;
}
else
{
carry = 0;
}
}
while (j < (len_prod + i)) //No remaining elements of the former prod_term, so take only into account the results of multiplying mult * b_256
{
prod_term[j] = prod[j - i] * b_256[i] + carry;
if (prod_term[j] > 9)
{
carry = prod_term[j] / 10;
prod_term[j] = prod_term[j] % 10;
}
else
{
carry = 0;
}
j++;
}
if (carry) //A carry may be present in the last term. If so, allocate memory to save it and increase the length of prod_term
{
len_prod_term = j + 1;
prod_term = realloc(prod_term, sizeof(*prod_term) * (len_prod_term));
prod_term[j] = carry;
}
else
{
len_prod_term = j;
}
}
free(prod); //We don't need prod anymore, prod will now be prod_term
prod = prod_term;
len_prod = len_prod_term;
//Add prod (formerly prod_term) to our current number of the num array, expressed in a b-10 array
carry = 0;
for (i = 0; i < len_cur_num; i++)
{
prod[i] = prod[i] + cur_num[i] + carry;
if (prod[i] > 9)
{
carry = prod[i] / 10;
prod[i] -= 10;
}
else
{
carry = 0;
}
}
while (carry && (i < len_prod))
{
prod[i] = prod[i] + carry;
if (prod[i] > 9)
{
carry = prod[i] / 10;
prod[i] -= 10;
}
else
{
carry = 0;
}
i++;
}
if (carry)
{
len_prod++;
prod = realloc(prod, sizeof(*prod) * len_prod);
prod[len_prod - 1] = carry;
carry = 0;
}
}
str = malloc(sizeof(char) * (len_prod + 1)); //Allocate memory for the return string
for (i = 0; i < len_prod; i++) //Convert the numeric result to its representation as characters
{
str[len_prod - 1 - i] = prod[i] + '0';
}
str[i] = '\0'; //Terminate our string
free(b_256); //Free memory
free(prod);
free(cur_num);
return str;
}
The idea behind it all derives from simple math. For any base-256 number, its base-10 representation can be calculated as:
num[i]*256^i + num[i-1]*256^(i-1) + (···) + num[2]*256^2 + num[1]*256^1 + num[0]*256^0
which expands to:
(((((num[i])*256 + num[i-1])*256 + (···))*256 + num[2])*256 + num[1])*256 + num[0]
So all we have to do is to multiply, step-by step, each element of the number array by 256 and add to it the next element, and so on... That way we can get the base-10 number.

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