I'm looking for a way (preferably recursive) to add two integers with their msb aligned.
For example: 125 + 25 = 375.
I tried to reverse the digits to effectively align them but the carrying would be all wrong. ie. 526 (625) + 05 (50) = 531.
1) Calculate number of digits of both numbers using a while / 10 loop
2) Get the difference
3) Multiply smallest number by 10 ^ difference
4) Add them together
you will need to include math.h for this. Assuming m and n are natural numbers, the below works by multiplying the smaller number by 10 (if needed) until it has the same number of digits as the larger, then adding.
int funkyAdd (int m, int n)
{
if ((m<=0)||(n<=0)){return -1;}
int smaller=std::min(m,n);
int larger=std::max(m,n);
while (floor(log10(smaller))<floor(log10(larger))){smaller*=10;};
return (smaller+larger);
}
Related
I have a question, which is to find the modulo 11 of a large number. The number is stored in a string whose maximum length is 1000. I want to code it in c++. How should i go about it?
I tried doing it with long long int, but its impossible that it can handle the corner case value.
A number written in decimal positional system as a_na_{n-1}...a_0 is the number
a_n*10^n+a_{n-1}*10^{n-1}+...+a_0
Note first that this number and the number
a_0-a_{1}+a_{2}+...+(-1)^{n}a_n
which is the sum of its digits with alternating signs have the same remainder after division by 11. You can check that by subtracting both numbers and noting that the result is a multiple of 11.
Based on this, if you are given a string consisting of the decimal representation of a number, then you can compute the remainder modulo 11 like this:
int remainder11(const std::string& s) {
int result{0};
bool even{true};
for (int i = s.length() - 1; i > -1; --i) {
result += (even ? 1 : -1) * ((int)(s[i] - '0'));
even = !even;
}
return ((result % 11) + 11) % 11;
}
Ok, here is the magic (math) trick.
First imagine you have a decimal number that consists only of 1s.
Say 111111, for example. It is obvious that 111111 % 11 is 0. (Since you can always write it as the sum of a series of 11*10^n). This can be generalized to all integers consists purely of even numbers of ones. (e.g. 11, 1111, 11111111). For those with odd number of ones, just subtract one from it and you will get a 10 times some number that consists of odd numbers of one (e.g 111=1+11*10), so their modulo to 11 would be 1.
A decimal number can be always written as the form of
where a0 is the least significant digit and an is the most significant digit. Note that 10^n can be written as 10^n - 1 + 1, and 10^n - 1 is a number consists of n nines. If n is even, then you will get 9 times some even number of ones, and its modulo to 11 is always 0. If n is odd, then we get 9 times some odd number of ones, and its modulo to 11 is always 9. And don't forget we've still got a +1 after 10^n - 1 + 1 so we need to add a to the result.
We are very close to our results now: we just have to add things up and do a final modulo to 11. The pseudo-code would be like:
Initialize sum to 0.
Initialize index to 0.
For every digit d from the least to most significant:
If the index is even, sum += d
Otherwise, sum += 10 * d
++index
sum %= 11
Return sum % 11
Suppose I have two numbers(minimum and maximum) . `
for example (0 and 9999999999)
maximum could be so huge. now I also have some other number. it could be between those minimum and maximum number. Let's say 15. now What I need to do is get all the multiples of 15(15,30,45 and so on, until it reaches the maximum number). and for each these numbers, I have to count how many 1 bits there are in their binary representations. for example, 15 has 4(because it has only 4 1bits).
The problem is, I need a loop in a loop to get the result. first loop is to get all multiples of that specific number(in our example it was 15) and then for each multiple, i need another loop to count only 1bits. My solution takes so much time. Here is how I do it.
unsigned long long int min = 0;
unsigned long long int max = 99999999;
unsigned long long int other_num = 15;
unsigned long long int count = 0;
unsigned long long int other_num_helper = other_num;
while(true){
if(other_num_helper > max) break;
for(int i=0;i<sizeof(int)*4;i++){
int buff = other_num_helper & 1<<i;
if(buff != 0) count++; //if bit is not 0 and is anything else, then it's 1bits.
}
other_num_helper+=other_num;
}
cout<<count<<endl;
Look at the bit patterns for the numbers between 0 and 2^3
000
001
010
011
100
101
110
111
What do you see?
Every bit is one 4 times.
If you generalize, you find that the numbers between 0 and 2^n have n*2^(n-1) bits set in total.
I am sure you can extend this reasoning for arbitrary bounds.
Here's how I do it for a 32 bit number.
std::uint16_t bitcount(
std::uint32_t n
)
{
register std::uint16_t reg;
reg = n - ((n >> 1) & 033333333333)
- ((n >> 2) & 011111111111);
return ((reg + (reg >> 3)) & 030707070707) % 63;
}
And the supporting comments from the program:
Consider a 3 bit number as being 4a + 2b + c. If we shift it right 1 bit, we have 2a + b. Subtracting this from the original gives 2a + b + c. If we right-shift the original 3-bit number by two bits, we get a, and so with another subtraction we have a + b + c, which is the number of bits in the original number.
The first assignment statement in the routine computes 'reg'. Each digit in the octal representation is simply the number of 1’s in the corresponding three bit positions in 'n'.
The last return statement sums these octal digits to produce the final answer. The key idea is to add adjacent pairs of octal digits together and then compute the remainder modulus 63.
This is accomplished by right-shifting 'reg' by three bits, adding it to 'reg' itself and ANDing with a suitable mask. This yields a number in which groups of six adjacent bits (starting from the LSB) contain the number of 1’s among those six positions in n. This number modulo 63 yields the final answer. For 64-bit numbers, we would have to add triples of octal digits and use modulus 1023.
I want to count the nth positive root of p for example we have n=2 and p=16 the answer is 4 because
4^2 = 16. I want to do this for huge numbers (1 <= n <= 200, 1 <= p < 10^101). I don't know how should I do it as fast as possible.
Example:
n=2 p=16 Answer 4
n=7 p=4357186184021382204544 Answer 1234
There are arbitrary precision math packages out there, if you have to come up with your own algorithm.
But you might try this: Get p into a double any way you can (a double can handle 10^101.) Then use math.h::pow(p, 1.0/n), and that answer will be close to the right integer (round it?). But this will fail if p is more than 15 digits, and n is too small, e.g., p = 10^100, n=2 gives a 50 digit answer, which is too big an integer for double to represent exactly.
Get 101 digit p into double: cut the number (string) into 10 digit chunks, multiply each by 10 to the appropriate power, and add them up.
Try Newton's method as described here:
http://en.wikipedia.org/wiki/Nth_root_algorithm
Take log of p, divide by n, and take the anti-log:
nthRoot(p, n) := Math.Power(10, Math.Log(p) / n)
Not sure whether you're specifically dealing with integers or what but that is the psuedo-code for it.
I have to check, if given number is divisible by 7, which is usualy done just by doing something like n % 7 == 0, but the problem is, that given number can have up to 100000000, which doesn't fit even in long long.
Another constrain is, that I have only few kilobytes of memory available, so I can't use an array.
I'm expecting the number to be on stdin and output to be 1/0.
This is an example
34123461273648125348912534981264376128345812354821354127346821354982135418235489162345891724592183459321864592158
0
It should be possible to do using only about 7 integer variables and cin.get(). It should be also done using only standard libraries.
you can use a known rule about division by 7 that says:
group each 3 digits together starting from the right and start subtracting and adding them alternativly, the divisibility of the result by 7 is the same as the original number:
ex.:
testing 341234612736481253489125349812643761283458123548213541273468213
549821354182354891623458917245921834593218645921580
(580-921+645-218+593-834+921-245+917-458+623-891+354-182
+354-821+549-213+468-273+541-213+548-123+458-283+761-643
+812-349+125-489+253-481+736-612+234-341
= 1882 )
% 7 != 0 --> NOK!
there are other alternatives to this rule, all easy to implement.
Think about how you do division on paper. You look at the first digit or two, and write down the nearest multiple of seven, carry down the remainder, and so on. You can do that on any abritrary length number because you don't have to load the whole number into memory.
Most of the divisibility by seven rules work on a digit level, so you should have no problem applying them on your string.
You can compute the value of the number modulo 7.
That is, for each digit d and value n so far compute n = (10 * n + d) % 7.
This has the advantage of working independently of the divisor 7 or the base 10.
You can compute the value of the number modulo 7.
That is, for each digit d and value n so far compute n = (10 * n + d) % 7.
This has the advantage of working independently of the divisor 7 or the base 10.
I solved this problem exactly the same way on one of programming contests. Here is the fragment of code you need:
int sum = 0;
while (true) {
char ch;
cin>>ch;
if (ch<'0' || ch>'9') break; // Reached the end of stdin
sum = sum*10; // The previous sum we had must be multiplied
sum += (int) ch;
sum -= (int) '0'; // Remove the code to get the value of the digit
sum %= 7;
}
if (sum==0) cout<<"1";
else cout<<"0";
This code is working thanks to simple rules of modular arithmetics. It also works not just for 7, but for any divisor actually.
I'd start by subtracting some big number which is divisible by 7.
Examples of numbers which are divisible by 7 include 700, 7000, 70000, 140000000, 42000000000, etc.
In the particular example you gave, try subtracting 280000000000(some number of zeros)0000.
Even easier to implement, repeatedly subtract the largest possible number like 70000000000(some number of zeros)0000.
Because I recently did work dealing with breaking up numbers, I will hint that to get specific numbers - which is what you will need with some of the other answers - think about integer division and using the modulus to get digits out of it.
If you had a smaller number, say 123, how would you get the 1, the 2, and the 3 out of it? Especially since you're working in base 10...
N = abc
There is a simple algorithm to verify if a three-digit number is a multiple of 7:
Substitute a by x and add it to bc, being x the tens of a two-digit number multiple of 7 whose hundreds is a.
N = 154; x = 2; 2 + 54 = 56; 7|56 and 7|154
N = 931; x = 4; 4 + 31 = 35; 7|35 and 7|931
N = 665; x = 5; 5 + 65 = 70; 7|70 and 7|665
N = 341; x = 6; 6 + 41 = 47; 7ł47 and 7ł341
If N is formed by various periods the inverse additive of the result of one period must be added to the sum of the next period, this way:
N = 341.234
6 + 41 = 47; - 41 mod 7 ≡ 1; 1 + 4 + 34 = 39; 7ł39 and 7łN
N = 341.234.612.736.481
The result for 341.234 is 39. Continuing from this result we have:
-39 mod 7 ≡ 3; 3 + 5 + 6 + 1 + 2 + 1 = 18; - 18 mod 7 ≡ 3; 3 + 0 + 36 = 39; - 39 mod 7 ≡ 3;
3 + 1 + 81 = 85; 7ł85 and 7łN
This rule may be applied entirely through mental calculation and is very quick.
It was derived from another rule that I created in 2.005. It works for numbers of any magnitude and for divisibility by 13.
At first Take That Big Number in string And then sum every digit of string. at last check if(sum%7==0)
Code:
#include <bits/stdc++.h>
using namespace std;
int main()
{
long long int n,i,j,sum,k;
sum=0;
string s;
cin>>s;
for(i=0;i<s.length();i++)
{
sum=sum+(s[i]-'0');
}
if(sum%7==0)
{
printf("Yes\n");
}
else
{
printf("No\n");
}
return 0;
}
I need some division algorithm which can handle big integers (128-bit).
I've already asked how to do it via bit shifting operators. However, my current implementation seems to ask for a better approach
Basically, I store numbers as two long long unsigned int's in the format
A * 2 ^ 64 + B with B < 2 ^ 64.
This number is divisible by 24 and I want to divide it by 24.
My current approach is to transform it like
A * 2 ^ 64 + B A B
-------------- = ---- * 2^64 + ----
24 24 24
A A mod 24 B B mod 24
= floor( ---- ) * 2^64 + ---------- * 2^64 + floor( ---- ) + ----------
24 24.0 24 24.0
However, this is buggy.
(Note that floor is A / 24 and that mod is A % 24. The normal divisions are stored in long double, the integers are stored in long long unsigned int.
Since 24 is equal to 11000 in binary, the second summand shouldn't change something in the range of the fourth summand since it is shifted 64 bits to the left.
So, if A * 2 ^ 64 + B is divisible by 24, and B is not, it shows easily that it bugs since it returns some non-integral number.
What is the error in my implementation?
The easiest way I can think of to do this is to treat the 128-bit numbers as four 32-bit numbers:
A_B_C_D = A*2^96 + B*2^64 + C*2^32 + D
And then do long division by 24:
E = A/24 (with remainder Q)
F = Q_B/24 (with remainder R)
G = R_C/24 (with remainder S)
H = S_D/24 (with remainder T)
Where X_Y means X*2^32 + Y.
Then the answer is E_F_G_H with remainder T. At any point you only need division of 64-bit numbers, so this should be doable with integer operations only.
Could this possibly be solved with inverse multiplication? The first thing to note is that 24 == 8 * 3 so the result of
a / 24 == (a >> 3) / 3
Let x = (a >> 3) then the result of the division is 8 * (x / 3). Now it remains to find the value of x / 3.
Modular arithmetic states that there exists a number n such that n * 3 == 1 (mod 2^128). This gives:
x / 3 = (x * n) / (n * 3) = x * n
It remains to find the constant n. There's an explanation on how to do this on wikipedia. You'll also have to implement functionality to multiply to 128 bit numbers.
Hope this helps.
/A.B.
You shouldn't be using long double for your "normal divisions" but integers there as well. long double doesn't have enough significant figures to get the answer right (and anyway the whole point is to do this with integer operations, correct?).
Since 24 is equal to 11000 in binary, the second summand shouldn't change something in the range of the fourth summand since it is shifted 64 bits to the left.
Your formula is written in real numbers. (A mod 24) / 24 can have an arbitrary number of decimals (1/24 is for instance 0.041666666...) and can therefore interfere with the fourth term in your decomposition, even once multiplied by 2^64.
The property that Y*2^64 does not interfere with the lower weight binary digits in an addition only works when Y is an integer.
Don't.
Go grab a library to do this stuff - you'll be incredibly thankful you chose to when debugging weird errors.
Snippets.org had a C/C++ BigInt library on it's site a while ago, Google also turned up the following: http://mattmccutchen.net/bigint/