So, I started learning C++ recently. This code is trying to add the sum of the squares of each numbers digits. For example: 243: 2*2 + 4*4 + 3*3 = 29.
int sumOfSquareDigits(int n) //BUG WITH INPUT OF 10, 100, 1000, etc.
{
int digits = findDigits(n);
int number;
int remainder;
int *allDigits = new int[digits];
for (int i = 0; i < digits; i++) { //assigns digits to array
if (i + 1 == digits){ //sees if there is a ones value left
allDigits[i] = n;
}
else {
remainder = (n % findPower10(digits - (i + 1)));
number = ((n - remainder) / findPower10(digits - (i + 1)));
allDigits[i] = number; //records leftmost digit
n = n - (allDigits[i] * findPower10(digits - (i + 1))); //gets rid of leftmost number and starts over
}
}
int result = 0;
for (int i = 0; i < digits; i++) { //finds sum of squared digits
result = result + (allDigits[i] * allDigits[i]);
}
delete [] allDigits;
return result;
}
int findDigits(int n) //finds out how many digits the number has
{
int digits = 0;
int test;
do {
digits++;
test = findPower10(digits);
} while (n > test);
return digits;
}
int findPower10(int n) { //function for calculating powers of 10
int result = 1;
for (int i = 0; i < n; i++)
result = result * 10;
return result;
}
And after running the code, I've figured out that it (barely) mostly works. I've found that whenever a user inputs a value of 10, 100, 1000, etc. it always returns a value of 100. I'd like to solve this only using the iostream header.
Sorry if my code isn't too readable or organized! It would also be helpful if there are any shortcuts to my super long code, thanks!
The problem is in the findDigits function. For the values 10, 100, 1000 etc, it calculates the number of the digits minus one. This happens because of the comparison in the loop, you are stopping when n is less or equal to test, but in these cases n is equal test and you should run the next iteration.
So, you should change the line 33:
} while (n > test);
to:
} while (n >= test);
Now, it should work just fine. But it will not work for negative numbers (I don't know this is required, but the solution bellow works for that case too).
I came up with a much simpler solution:
int sumOfSquareDigits(int n)
{
// Variable to mantain the total sum of the squares
int sum = 0;
// This loop will change n until it is zero
while (n != 0) {
/// The current digit we will calculate the square is the rightmost digit,
// so we just get its value using the mod operator
int current = n % 10;
// Add its square to the sum
sum += current*current;
// You divide n by 10, this 'removes' one digit of n
n = n / 10;
}
return sum;
}
I found the problem challenging managed to reduce your code to the following lines:
long long sumOfSquareDigits(long long i) {
long long sum(0L);
do {
long long r = i % 10;
sum += (r * r);
} while(i /= 10);
return sum;
}
Haven't test it thoroughly but I think it works OK.
Related
I have correctly written the program for getting the superdigit of a large number (long long) but can't seem to pass some cases due to timeout and abort calls. Please suggest some optimizations to improve the runtime of my program:
int superDigit(long long m) {
int d=countDigit(m);
if(d==1){
return m;
}
long s=sumDigit(m);
return superDigit(s);
}
//utility functions to calculate digit count and sum of digits
int countDigit(long long n)
{
int count = 0;
while (n != 0) {
n = n / 10;
++count;
}
return count;
}
long sumDigit(long long n)
{
long sum = 0;
while (n != 0) {
sum += n % 10;
n = n / 10;
}
return sum;
}
Theory: A superdigit is defined by the following rules:
If x has only 1 digit, then its super digit is x
Otherwise, the super digit of x is equal to the super digit of the sum of the digits of x
For example:
super_digit(9875): 9+8+7+5 = 29 ,then
super_digit(29): 2 + 9 = 11 ,then
super_digit(11): 1 + 1 = 2 ,then
super_digit(2): = 2
Only looping over the digits once per superDigit call and avoiding recursion should make it faster. Something like this:
long long superDigit(long long m) {
long long sum;
while(true) {
sum = 0;
while(m != 0) {
sum += m % 10;
m /= 10;
}
if(sum >= 10)
m = sum;
else
break;
}
return sum;
}
If you need support for repeated sequences, like 593 10 times (which is usually too big for a long long) you could add a wrapper like this:
long long superDigit(long long m, int times) {
long long r = superDigit(m) * times;
if(r >= 10) r = superDigit(r);
return r;
}
For numbers small enough to fit in a long long, you can check that it works. Example:
superDigit(148148148) == superDigit(148, 3)
If you need support for large numbers that are not repeated sequences, you could add yet another overload, taking the number as a std::string:
long long superDigit(const std::string& m) {
long long sum = 0;
for(auto d : m) sum += d - '0';
if(sum >= 10) return superDigit(sum);
return sum;
}
And you can check that it's also getting the same result as one of the previous overloads:
superDigit(593, 10) == superDigit("593593593593593593593593593593")
I think you are getting abort call for value of m! If the value of m is 0, then the recursion will continue lifetime. And if the value of m can be negative then take care the problem for negative values too.
Please check it!
int superDigit(long long m) {
if(m<=9)return m; // handling case 0
int d=countDigit(m);
if(d==1){
return m;
}
long s=sumDigit(m);
return superDigit(s);
}
Your code has a problem with a '0'. It gets into an endless loop that is terminated if the call stack overflows (if your compiler does not eliminated the tail recursion).
The digit count helper function is completely unnecessary
int superDigit(long long m) {
if(m<10){
return m;
}else{
int s = 0;
do {
s += m % 10;
m = m / 10;
}while (m > 0);
return superDigit(s);
}
}
You can eliminate the recursion by yourself by putting the whole thing into a loop.
int superDigit(long long m) {
while (m >9){
int s = 0;
do {
s += m % 10;
m = m / 10;
}while (m > 0);
m = s;
}
return m;
}
But recursion looks a bit more self explaining and modern compiler should be able to eliminate the tail recursion either.
I'm making a simple program to calculate the number of pairs in an array that are divisible by 3 array length and values are user determined.
Now my code is perfectly fine. However, I just want to check if there is a faster way to calculate it which results in less compiling time?
As the length of the array is 10^4 or less compiler takes less than 100ms. However, as it gets more to 10^5 it spikes up to 1000ms so why is this? and how to improve speed?
#include <iostream>
using namespace std;
int main()
{
int N, i, b;
b = 0;
cin >> N;
unsigned int j = 0;
std::vector<unsigned int> a(N);
for (j = 0; j < N; j++) {
cin >> a[j];
if (j == 0) {
}
else {
for (i = j - 1; i >= 0; i = i - 1) {
if ((a[j] + a[i]) % 3 == 0) {
b++;
}
}
}
}
cout << b;
return 0;
}
Your algorithm has O(N^2) complexity. There is a faster way.
(a[i] + a[j]) % 3 == ((a[i] % 3) + (a[j] % 3)) % 3
Thus, you need not know the exact numbers, you need to know their remainders of division by three only. Zero remainder of the sum can be received with two numbers with zero remainders (0 + 0) and with two numbers with remainders 1 and 2 (1 + 2).
The result will be equal to r[1]*r[2] + r[0]*(r[0]-1)/2 where r[i] is the quantity of numbers with remainder equal to i.
int r[3] = {};
for (int i : a) {
r[i % 3]++;
}
std::cout << r[1]*r[2] + (r[0]*(r[0]-1)) / 2;
The complexity of this algorithm is O(N).
I've encountered this problem before, and while I don't find my particular solution, you could improve running times by hashing.
The code would look something like this:
// A C++ program to check if arr[0..n-1] can be divided
// in pairs such that every pair is divisible by k.
#include <bits/stdc++.h>
using namespace std;
// Returns true if arr[0..n-1] can be divided into pairs
// with sum divisible by k.
bool canPairs(int arr[], int n, int k)
{
// An odd length array cannot be divided into pairs
if (n & 1)
return false;
// Create a frequency array to count occurrences
// of all remainders when divided by k.
map<int, int> freq;
// Count occurrences of all remainders
for (int i = 0; i < n; i++)
freq[arr[i] % k]++;
// Traverse input array and use freq[] to decide
// if given array can be divided in pairs
for (int i = 0; i < n; i++)
{
// Remainder of current element
int rem = arr[i] % k;
// If remainder with current element divides
// k into two halves.
if (2*rem == k)
{
// Then there must be even occurrences of
// such remainder
if (freq[rem] % 2 != 0)
return false;
}
// If remainder is 0, then there must be two
// elements with 0 remainder
else if (rem == 0)
{
if (freq[rem] & 1)
return false;
}
// Else number of occurrences of remainder
// must be equal to number of occurrences of
// k - remainder
else if (freq[rem] != freq[k - rem])
return false;
}
return true;
}
/* Driver program to test above function */
int main()
{
int arr[] = {92, 75, 65, 48, 45, 35};
int k = 10;
int n = sizeof(arr)/sizeof(arr[0]);
canPairs(arr, n, k)? cout << "True": cout << "False";
return 0;
}
That works for a k (in your case 3)
But then again, this is not my code, but the code you can find in the following link. with a proper explanation. I didn't just paste the link since it's bad practice I think.
I have a problem:
You are given a sequence, in the form of a string with characters ‘0’, ‘1’, and ‘?’ only. Suppose there are k ‘?’s. Then there are 2^k ways to replace each ‘?’ by a ‘0’ or a ‘1’, giving 2^k different 0-1 sequences (0-1 sequences are sequences with only zeroes and ones).
For each 0-1 sequence, define its number of inversions as the minimum number of adjacent swaps required to sort the sequence in non-decreasing order. In this problem, the sequence is sorted in non-decreasing order precisely when all the zeroes occur before all the ones. For example, the sequence 11010 has 5 inversions. We can sort it by the following moves: 11010 →→ 11001 →→ 10101 →→ 01101 →→ 01011 →→ 00111.
Find the sum of the number of inversions of the 2^k sequences, modulo 1000000007 (10^9+7).
For example:
Input: ??01
-> Output: 5
Input: ?0?
-> Output: 3
Here's my code:
#include <iostream>
#include <stdio.h>
#include <stdlib.h>
#include <string>
#include <string.h>
#include <math.h>
using namespace std;
void ProcessSequences(char *input)
{
int c = 0;
/* Count the number of '?' in input sequence
* 1??0 -> 2
*/
for(int i=0;i<strlen(input);i++)
{
if(*(input+i) == '?')
{
c++;
}
}
/* Get all possible combination of '?'
* 1??0
* -> ??
* -> 00, 01, 10, 11
*/
int seqLength = pow(2,c);
// Initialize 2D array of integer
int **sequencelist, **allSequences;
sequencelist = new int*[seqLength];
allSequences = new int*[seqLength];
for(int i=0; i<seqLength; i++){
sequencelist[i] = new int[c];
allSequences[i] = new int[500000];
}
//end initialize
for(int count = 0; count < seqLength; count++)
{
int n = 0;
for(int offset = c-1; offset >= 0; offset--)
{
sequencelist[count][n] = ((count & (1 << offset)) >> offset);
// cout << sequencelist[count][n];
n++;
}
// cout << std::endl;
}
/* Change '?' in former sequence into all possible bits
* 1??0
* ?? -> 00, 01, 10, 11
* -> 1000, 1010, 1100, 1110
*/
for(int d = 0; d<seqLength; d++)
{
int seqCount = 0;
for(int e = 0; e<strlen(input); e++)
{
if(*(input+e) == '1')
{
allSequences[d][e] = 1;
}
else if(*(input+e) == '0')
{
allSequences[d][e] = 0;
}
else
{
allSequences[d][e] = sequencelist[d][seqCount];
seqCount++;
}
}
}
/*
* Sort each sequences to increasing mode
*
*/
// cout<<endl;
int totalNum[seqLength];
for(int i=0; i<seqLength; i++){
int num = 0;
for(int j=0; j<strlen(input); j++){
if(j==strlen(input)-1){
break;
}
if(allSequences[i][j] > allSequences[i][j+1]){
int temp = allSequences[i][j];
allSequences[i][j] = allSequences[i][j+1];
allSequences[i][j+1] = temp;
num++;
j = -1;
}//endif
}//endfor
totalNum[i] = num;
}//endfor
/*
* Sum of all Num of Inversions
*/
int sum = 0;
for(int i=0;i<seqLength;i++){
sum = sum + totalNum[i];
}
// cout<<"Output: "<<endl;
int out = sum%1000000007;
cout<< out <<endl;
} //end of ProcessSequences method
int main()
{
// Get Input
char seq[500000];
// cout << "Input: "<<endl;
cin >> seq;
char *p = &seq[0];
ProcessSequences(p);
return 0;
}
the results were right for small size input, but for bigger size input I got time CPU time limit > 1 second. I also got exceeded memory size. How to make it faster and optimal memory use? What algorithm should I use and what better data structure should I use?, Thank you.
Dynamic programming is the way to go. Imagine You are adding the last character to all sequences.
If it is 1 then You get XXXXXX1. Number of swaps is obviously the same as it was for every sequence so far.
If it is 0 then You need to know number of ones already in every sequence. Number of swaps would increase by the amount of ones for every sequence.
If it is ? You just add two previous cases together
You need to calculate how many sequences are there. For every length and for every number of ones (number of ones in the sequence can not be greater than length of the sequence, naturally). You start with length 1, which is trivial, and continue with longer. You can get really big numbers, so You should calculate modulo 1000000007 all the time. The program is not in C++, but should be easy to rewrite (array should be initialized to 0, int is 32bit, long in 64bit).
long Mod(long x)
{
return x % 1000000007;
}
long Calc(string s)
{
int len = s.Length;
long[,] nums = new long[len + 1, len + 1];
long sum = 0;
nums[0, 0] = 1;
for (int i = 0; i < len; ++i)
{
if(s[i] == '?')
{
sum = Mod(sum * 2);
}
for (int j = 0; j <= i; ++j)
{
if (s[i] == '0' || s[i] == '?')
{
nums[i + 1, j] = Mod(nums[i + 1, j] + nums[i, j]);
sum = Mod(sum + j * nums[i, j]);
}
if (s[i] == '1' || s[i] == '?')
{
nums[i + 1, j + 1] = nums[i, j];
}
}
}
return sum;
}
Optimalization
The code above is written to be as clear as possible and to show dynamic programming approach. You do not actually need array [len+1, len+1]. You calculate column i+1 from column i and never go back, so two columns are enough - old and new. If You dig more into it, You find out that row j of new column depends only on row j and j-1 of the old column. So You can go with one column if You actualize the values in the right direction (and do not overwrite values You would need).
The code above uses 64bit integers. You really need that only in j * nums[i, j]. The nums array contain numbers less than 1000000007 and 32bit integer is enough. Even 2*1000000007 can fit into 32bit signed int, we can make use of it.
We can optimize the code by nesting loop into conditions instead of conditions in the loop. Maybe it is even more natural approach, the only downside is repeating the code.
The % operator is, as every dividing, quite expensive. j * nums[i, j] is typically far smaller that capacity of 64bit integer, so we do not have to do modulo in every step. Just watch the actual value and apply when needed. The Mod(nums[i + 1, j] + nums[i, j]) can also be optimized, as nums[i + 1, j] + nums[i, j] would always be smaller than 2*1000000007.
And finally the optimized code. I switched to C++, I realized there are differences what int and long means, so rather make it clear:
long CalcOpt(string s)
{
long len = s.length();
vector<long> nums(len + 1);
long long sum = 0;
nums[0] = 1;
const long mod = 1000000007;
for (long i = 0; i < len; ++i)
{
if (s[i] == '1')
{
for (long j = i + 1; j > 0; --j)
{
nums[j] = nums[j - 1];
}
nums[0] = 0;
}
else if (s[i] == '0')
{
for (long j = 1; j <= i; ++j)
{
sum += (long long)j * nums[j];
if (sum > std::numeric_limits<long long>::max() / 2) { sum %= mod; }
}
}
else
{
sum *= 2;
if (sum > std::numeric_limits<long long>::max() / 2) { sum %= mod; }
for (long j = i + 1; j > 0; --j)
{
sum += (long long)j * nums[j];
if (sum > std::numeric_limits<long long>::max() / 2) { sum %= mod; }
long add = nums[j] + nums[j - 1];
if (add >= mod) { add -= mod; }
nums[j] = add;
}
}
}
return (long)(sum % mod);
}
Simplification
Time limit still exceeded? There is probably better way to do it. You can either
get back to the beginning and find out mathematically different way to calculate the result
or simplify actual solution using math
I went the second way. What we are doing in the loop is in fact convolution of two sequences, for example:
0, 0, 0, 1, 4, 6, 4, 1, 0, 0,... and 0, 1, 2, 3, 4, 5, 6, 7, 8, 9,...
0*0 + 0*1 + 0*2 + 1*3 + 4*4 + 6*5 + 4*6 + 1*7 + 0*8...= 80
The first sequence is symmetric and the second is linear. It this case, the sum of convolution can be calculated from sum of the first sequence which is = 16 (numSum) and number from second sequence corresponding to the center of the first sequence, which is 5 (numMult). numSum*numMult = 16*5 = 80. We replace the whole loop with one multiplication if we are able to update those numbers in each step, which fortulately seems the case.
If s[i] == '0' then numSum does not change and numMult does not change.
If s[i] == '1' then numSum does not change, only numMult increments by 1, as we shift the whole sequence by one position.
If s[i] == '?' we add original and shiftet sequence together. numSum is multiplied by 2 and numMult increments by 0.5.
The 0.5 means a bit problem, as it is not the whole number. But we know, that the result would be whole number. Fortunately in modular arithmetics in this case exists inversion of two (=1/2) as a whole number. It is h = (mod+1)/2. As a reminder, inversion of 2 is such a number, that h*2=1 modulo mod. Implementation wisely it is easier to multiply numMult by 2 and divide numSum by 2, but it is just a detail, we would need 0.5 anyway. The code:
long CalcOptSimpl(string s)
{
long len = s.length();
long long sum = 0;
const long mod = 1000000007;
long numSum = (mod + 1) / 2;
long long numMult = 0;
for (long i = 0; i < len; ++i)
{
if (s[i] == '1')
{
numMult += 2;
}
else if (s[i] == '0')
{
sum += numSum * numMult;
if (sum > std::numeric_limits<long long>::max() / 4) { sum %= mod; }
}
else
{
sum = sum * 2 + numSum * numMult;
if (sum > std::numeric_limits<long long>::max() / 4) { sum %= mod; }
numSum = (numSum * 2) % mod;
numMult++;
}
}
return (long)(sum % mod);
}
I am pretty sure there exists some simple way to get this code, yet I am still unable to see it. But sometimes path is the goal :-)
If a sequence has N zeros with indexes zero[0], zero[1], ... zero[N - 1], the number of inversions for it would be (zero[0] + zero[1] + ... + zero[N - 1]) - (N - 1) * N / 2. (you should be able to prove it)
For example, 11010 has two zeros with indexes 2 and 4, so the number of inversions would be 2 + 4 - 1 * 2 / 2 = 5.
For all 2^k sequences, you can calculate the sum of two parts separately and then add them up.
1) The first part is zero[0] + zero[1] + ... + zero[N - 1]. Each 0 in the the given sequence contributes index * 2^k and each ? contributes index * 2^(k-1)
2) The second part is (N - 1) * N / 2. You can calculate this using a dynamic programming (maybe you should google and learn this first). In short, use f[i][j] to present the number of sequence with j zeros using the first i characters of the given sequence.
Given a natural number n (1 <= n <= 500000), please output the summation of all its proper divisors.
Definition: A proper divisor of a natural number is the divisor that is strictly less than the number.
e.g. number 20 has 5 proper divisors: 1, 2, 4, 5, 10, and the divisor summation is: 1 + 2 + 4 + 5 + 10 = 22.
<<--This is a challenge i am trying to do and i am using recursion
int find_sum(std::vector <int> nums,long int sum,int num_now,long int j)
{
if(j<nums[num_now])
{
if(nums[num_now]%j==0)
{
sum=sum+j;
}
return find_sum(nums,sum,num_now,j+1);
}
else
{
return sum;
}
}
sum is the sum of all divisors,nums is the vector i stored number in,num_now is current member in vector,int j is 1 i use it to search for dividers,sadly using this i cant use numbers like 500000 it give's me error,is there any better way to do it or have i made a mistake somewhere.
--Thank you for your time
Here is a recursive way to solve your problem:
int find_sum(int x, int i)
{
if(i == 0)
return 0;
if(x % i == 0)
return i + find_sum(x, (i-1));
return find_sum(x, (i-1));
}
You need to call find_sum(N, N-1); in order to find sum of dividers of N (i must be less than given N because of strict inequality).
In your case it would be find_sum(20, 19);
e.g. my function returns:
71086 for N = 50000
22 for N = 20
0 for N = 1
I don't see the reason why you need to use recursion for solving this problem. I would prefer a more staightforward way to solve it.
long CalculateSumOfDivisors(int number)
{
long sum = 0;
for(int i=1; i<number; i++)
{
// If the remainder of num/i is zero
// then i divides num. So we add it to the
// current sum.
if(number%i==0)
{
sum+=i;
}
}
return sum;
}
Furthermore, we could write a more optimal algorithm, if we note the following:
Let that we have a number n and d is the smallest divisor of n that is greater of 1. (Apparently if the number n is a prime number there is any such a divisor). Then the larget divisor of n is the number n/d.
Based on this we can formulate a more optimal algorithm.
long CalculateSumOfDivisors(int number)
{
int smallestDivisor = FindSmallestDivisor(number);
if(smallestDivisor==1) return 1;
long sum = smallestDivisor;
// Calculate the possible greatest divisor.
int possibleGreatestDivisor = (int)floor(number/smallestDivisor);
for(int i=smallestDivisor+1; i<=possibleGreatestDivisor; i++)
{
if(number%i==0)
{
sum+=i;
}
}
return sum;
}
int FindSmallestDivisor(int number)
{
int smallestDivisor = 1;
for(int i=2; i<number; i++)
{
if(number%i==0)
{
smallestDivisor = i;
break;
}
}
return smallestDivisor;
}
I tried writing code with main function asking user to give the it wants to get sum of. here is the code , hope it helps.
#include<iostream>
using namespace std;
int Sum(int min, int max, int &val, int &sum){
if(min >= max)
return 0;
for ( ; min < max; min++){
if ( val%min == 0){
sum += min + val/min;
return Sum(++min,val/min, val,sum);
}
}
return 0;
}
int main(){
int s=1;
int val;
cout <<"Enter Val to sum:";
cin >> val;
Sum(2,val,val,s);
cout <<"Sum is :"<<s<<endl;
return 0;
}
Here Sum function is used recursively and passed parameters as shown in the code.
Hope it helps.
I don't think you should use recursion.
Instead start by looping from 1..N-1
When you find a divisor adjust the end value for the loop. Example if 2 is a divisor then you know N/2 is also a divisor. And just as important you know there can be no further divisors in the range ]N/2:N[. Likewise if 3 is a divisor then you know N/3 is also a divisor and you know there are no more divisors in the range ]N/3:N[.
Following that concept you can reduced the number of loops significantly for most numbers.
Something like:
long find_sum(int num)
{
long sum = 0;
int max = num;
int i = 1;
while(i < max)
{
if(num % i == 0)
{
sum += i; // Add i to the sum
max = num / i; // Decrement max for performance
if (max != i && max != num)
{
sum += max; // Add max when max isn't equal i
}
}
i++;
}
return sum;
}
Example:
num = 10
sum = 0
i = 1 -> sum = 1, max = 10
i = 2 -> sum = 1+2+5, max = 5
i = 3 -> sum = 1+2+5, max = 5
i = 4 -> sum = 1+2+5, max = 5
i = 5 -> return 8 (1+2+5)
num = 64
sum = 0
i = 1 -> sum = 1, max = 64
i = 2 -> sum = 1+2+32, max = 32
i = 3 -> sum = 1+2+32, max = 32
i = 4 -> sum = 1+2+32+4+16, max = 16
i = 5 -> sum = 1+2+32+4+16, max = 16
i = 6 -> sum = 1+2+32+4+16, max = 16
i = 7 -> sum = 1+2+32+4+16, max = 16
i = 8 -> sum = 1+2+32+4+16+8, max = 8
i = 9 -> return (1+2+32+4+16+8)
The number of loops are kept down by changing max whenever a new divisor is found.
The sequence of triangle numbers is
generated by adding the natural
numbers. So the 7th triangle number
would be 1 + 2 + 3 + 4 + 5 + 6 + 7 =
28. The first ten terms would be:
1, 3, 6, 10, 15, 21, 28, 36, 45, 55,
...
Let us list the factors of the first
seven triangle numbers:
1: 1
3: 1,3
6: 1,2,3,6
10: 1,2,5,10
15: 1,3,5,15
21: 1,3,7,21
28: 1,2,4,7,14,28
We can see that 28 is the first
triangle number to have over five
divisors.
Given an integer n, display the first
triangle number having at least n
divisors.
Sample Input: 5
Output 28
Input Constraints: 1<=n<=320
I was obviously able to do this question, but I used a naive algorithm:
Get n.
Find triangle numbers and check their number of factors using the mod operator.
But the challenge was to show the output within 4 seconds of input. On high inputs like 190 and above it took almost 15-16 seconds. Then I tried to put the triangle numbers and their number of factors in a 2d array first and then get the input from the user and search the array. But somehow I couldn't do it: I got a lot of processor faults. Please try doing it with this method and paste the code. Or if there are any better ways, please tell me.
Here's a hint:
The number of divisors according to the Divisor function is the product of the power of each prime factor plus 1. For example, let's consider the exponential prime representation of 28:
28 = 22 * 30 * 50 * 71 * 110...
The product of each exponent plus one is: (2+1)*(0+1)*(0+1)*(1+1)*(0+1)... = 6, and sure enough, 28 has 6 divisors.
Now, consider that the nth triangular number can be computed in closed form as n(n+1)/2. We can multiply numbers written in the exponential prime form simply by adding up the exponents at each position. Dividing by two just means decrementing the exponent on the two's place.
Do you see where I'm going with this?
Well, you don't go into a lot of detail about what you did, but I can give you an optimization that can be used, if you didn't think of it...
If you're using the straightforward method of trying to find factors of a number n, by using the mod operator, you don't need to check all the numbers < n. That obviously would take n comparisons...you can just go up to floor(sqrt(n)). For each factor you find, just divide n by that number, and you'll get the conjugate value, and not need to find it manually.
For example: say n is 15.
We loop, and try 1 first. Yep, the mod checks out, so it's a factor. We divide n by the factor to get the conjugate value, so we do (15 / 1) = 15...so 15 is a factor.
We try 2 next. Nope. Then 3. Yep, which also gives us (15 / 3) = 5.
And we're done, because 4 is > floor(sqrt(n)). Quick!
If you didn't think of it, that might be something you could leverage to improve your times...overall you go from O(n) to O(sqrt (n)) which is pretty good (though for numbers this small, constants may still weigh heavily.)
I was in a programming competition way back in school where there was some similar question with a run time limit. the team that "solved" it did as follows:
1) solve it with a brute force slow method.
2) write a program to just print out the answer (you found using the slow method), which will run sub second.
I thought this was bogus, but they won.
see Triangular numbers: a(n) = C(n+1,2) = n(n+1)/2 = 0+1+2+...+n. (Formerly M2535 N1002)
then pick the language you want implement it in, see this:
"... Python
import math
def diminishing_returns(val, scale):
if val < 0:
return -diminishing_returns(-val, scale)
mult = val / float(scale)
trinum = (math.sqrt(8.0 * mult + 1.0) - 1.0) / 2.0
return trinum * scale
..."
First, create table with two columns: Triangle_Number Count_of_Factors.
Second, derive from this a table with the same columns, but consisting only of the 320 rows of the lowest triangle number with a distinct number of factors.
Perform your speedy lookup to the second table.
If you solved the problem, you should be able to access the thread on Project Euler in which people post their (some very efficient) solutions.
If you're going to copy and paste a problem, please cite the source (unless it was your teacher who stole it); and I second Wouter van Niferick's comment.
Well, at least you got a good professor. Performance is important.
Since you have a program that can do the job, you can precalculate all of the answers for 1 .. 320.
Store them in an array, then simply subscript into the array to get the answer. That will be very fast.
Compile with care, winner of worst code of the year :D
#include <iostream>
bool isPrime( unsigned long long number ){
if( number != 2 && number % 2 == 0 )
return false;
for( int i = 3;
i < static_cast<unsigned long long>
( sqrt(static_cast<double>(number)) + 1 )
; i += 2 ){
if( number % i == 0 )
return false;
}
return true;
}
unsigned int p;
unsigned long long primes[1024];
void initPrimes(){
primes[0] = 2;
primes[1] = 3;
unsigned long long number = 5;
for( unsigned int i = 2; i < 1024; i++ ){
while( !isPrime(number) )
number += 2;
primes[i] = number;
number += 2;
}
return;
}
unsigned long long nextPrime(){
unsigned int ret = p;
p++;
return primes[ret];
}
unsigned long long numOfDivs( unsigned long long number ){
p = 0;
std::vector<unsigned long long> v;
unsigned long long prime = nextPrime(), divs = 1, i = 0;
while( number >= prime ){
i = 0;
while( number % prime == 0 ){
number /= prime;
i++;
}
if( i )
v.push_back( i );
prime = nextPrime();
}
for( unsigned n = 0; n < v.size(); n++ )
divs *= (v[n] + 1);
return divs;
}
unsigned long long nextTriNumber(){
static unsigned long long triNumber = 1, next = 2;
unsigned long long retTri = triNumber;
triNumber += next;
next++;
return retTri;
}
int main()
{
initPrimes();
unsigned long long n = nextTriNumber();
unsigned long long divs = 500;
while( numOfDivs(n) <= divs )
n = nextTriNumber();
std::cout << n;
std::cin.get();
}
def first_triangle_number_with_over_N_divisors(N):
n = 4
primes = [2, 3]
fact = [None, None, {2:1}, {3:1}]
def num_divisors (x):
num = 1
for mul in fact[x].values():
num *= (mul+1)
return num
while True:
factn = {}
for p in primes:
if p > n//2: break
r = n // p
if r * p == n:
factn = fact[r].copy()
factn[p] = factn.get(p,0) + 1
if len(factn)==0:
primes.append(n)
factn[n] = 1
fact.append(factn)
(x, y) = (n-1, n//2) if n % 2 == 0 else (n, (n-1)//2)
numdiv = num_divisors(x) * num_divisors(y)
if numdiv >= N:
print('Triangle number %d: %d divisors'
%(x*y, numdiv))
break
n += 1
>>> first_triangle_number_with_over_N_divisors(500)
Triangle number 76576500: 576 divisors
Dude here is ur code, go have a look. It calculates the first number that has divisors greater than 500.
void main() {
long long divisors = 0;
long long nat_num = 0;
long long tri_num = 0;
int tri_sqrt = 0;
while (1) {
divisors = 0;
nat_num++;
tri_num = nat_num + tri_num;
tri_sqrt = floor(sqrt((double)tri_num));
long long i = 0;
for ( i=tri_sqrt; i>=1; i--) {
long long remainder = tri_num % i;
if ( remainder == 0 && tri_num == 1 ) {
divisors++;
}
else if (remainder == 0 && tri_num != 1) {
divisors++;
divisors++;
}
}
if (divisors >100) {
cout <<"No. of divisors: "<<divisors<<endl<<tri_num<<endl;
}
if (divisors > 500)
break;
}
cout<<"Final Result: "<<tri_num<<endl;
system("pause");
}
Boojum's answer motivated me to write this little program. It seems to work well, although it does use a brute force method of computing primes. It's neat how all the natural numbers can be broken down into prime number components.
#include <stdio.h>
#include <stdlib.h>
#include <iostream>
#include <iomanip>
#include <vector>
//////////////////////////////////////////////////////////////////////////////
typedef std::vector<size_t> uint_vector;
//////////////////////////////////////////////////////////////////////////////
// add a prime number to primes[]
void
primeAdd(uint_vector& primes)
{
size_t n;
if (primes.empty())
{
primes.push_back(2);
return;
}
for (n = *(--primes.end()) + 1; ; ++n)
{
// n is even -> not prime
if ((n & 1) == 0) continue;
// look for a divisor in [2,n)
for (size_t i = 2; i < n; ++i)
{
if ((n % i) == 0) continue;
}
// found a prime
break;
}
primes.push_back(n);
}
//////////////////////////////////////////////////////////////////////////////
void
primeFactorize(size_t n, uint_vector& primes, uint_vector& f)
{
f.clear();
for (size_t i = 0; n > 1; ++i)
{
while (primes.size() <= i) primeAdd(primes);
while (f.size() <= i) f.push_back(0);
while ((n % primes[i]) == 0)
{
++f[i];
n /= primes[i];
}
}
}
//////////////////////////////////////////////////////////////////////////////
int
main(int argc, char** argv)
{
// allow specifying number of TN's to be evaluated
size_t lim = 1000;
if (argc > 1)
{
lim = atoi(argv[1]);
}
if (lim == 0) lim = 1000;
// prime numbers
uint_vector primes;
// factors of (n), (n + 1)
uint_vector* f = new uint_vector();
uint_vector* f1 = new uint_vector();
// sum vector
uint_vector sum;
// prime factorize (n)
size_t n = 1;
primeFactorize(n, primes, *f);
// iterate over triangle-numbers
for (; n <= lim; ++n)
{
// prime factorize (n + 1)
primeFactorize(n + 1, primes, *f1);
while (f->size() < f1->size()) f->push_back(0);
while (f1->size() < f->size()) f1->push_back(0);
size_t numTerms = f->size();
// compute prime factors for (n * (n + 1) / 2)
sum.clear();
size_t i;
for (i = 0; i < numTerms; ++i)
{
sum.push_back((*f)[i] + (*f1)[i]);
}
--sum[0];
size_t numFactors = 1, tn = 1;
for (i = 0; i < numTerms; ++i)
{
size_t exp = sum[i];
numFactors *= (exp + 1);
while (exp-- != 0) tn *= primes[i];
}
std::cout
<< n << ". Triangle number "
<< tn << " has " << numFactors << " factors."
<< std::endl;
// prepare for next iteration
f->clear();
uint_vector* tmp = f;
f = f1;
f1 = tmp;
}
delete f;
delete f1;
return 0;
}