How to display an array dynamically - c++

I need to create a function that displays the following:
if number is between 0 - 5 then display values 1, 2, 3, 4, 5
if number is between 5 - 10 then display values 2, 4, 6, 8, 10
if number is between 10 - 50 then display values 10, 20, 30, 40, 50
if number is between 50 - 100 then display values 20, 40, 60, 80, 100
if number is between 100 - 500 then display values 100, 200, 300, 400, 500
if number is between 500 - 1000 then display values 200, 400, 600, 800, 1000
if number is between 1000 - 5000 then display values 1000, 2000, 3000, 4000, 5000
and so on...
I'm thinking of working with 2 arrays and then multiply with 10.
int *MyFunct(int number) {
int a[5] = { 1, 2, 3, 4, 5 };
int b[5] = { 2, 4, 6, 8, 10 };
if (number >= 0 && number <= 5) {
return a;
}
else if (number > 5 && number <= 10) {
return b;
}
else if (number > 10 && number <= 50) {
a[1] *= 10;
a[2] *= 10;
a[3] *= 10;
a[4] *= 10;
a[5] *= 10;
}
.
.
.
}
Is there any possibility to do this dynamically or simpler?

You can keep your first 2 arrays. You can do this in 3 steps.
Check if number is between 10^n and 5*(10^n). If it is, use the first array. If not, use the second array.
After that multiply each number by 10^n for some n such that 10^n < number.
This can be done by a for loop to check

I would start with something like that:
std::vector<unsigned int> MyFunct(unsigned int number) {
std::vector<unsigned int> numbers = { 1,2,3,4,5 };
unsigned int factor = 1;
while(number >= 10)
{
number /= 10;
factor *= 10;
}
if(number >= 5)
{
factor *= 2;
}
for(unsigned int i = 0; i < numbers.size(); ++i)
{
numbers[i] *= factor;
}
return numbers;
}
You could also work with logarithm of base 10.

You must first note that you cannot return an automatic array. For this use case, the simplest is to just use static ones.
Then your algorithm can be reworded as:
start with the array [1, 2, 3, 4, 5]
if the number is less than the last number of the array, return the array
else multiply the array alternatively by 2 and 5
In C++ it gives:
int *MyFunc(int n) {
static const int init[] = {1, 2, 3, 4, 5}; // the initial array
static int result[5];
int& max = result[4]; // alias for the last value
// copy init to result:
for (int i=0; i<5; i++) result[i] = init[i];
// find the range of n
for (;;) {
if (n <= max) {
break;
}
// multiply alternatively by 2 and by 5
for (int i=0; i<5; i++) result[i] *= 2;
if (n <= max) {
break;
}
for (int i=0; i<5; i++) result[i] *= 5;
}
return result;
}
Simple and compact...

Here's a variant that does what you say it should do – display those outputs – rather than return an array.
It does not use any arrays at all.
(Note that the problem as stated contains overlapping intervals. I have assumed that the intervals are actually 0-5, 6-10, 11-50, 51-100, 101-500, 501-1000, and >1000.)
int factor(int x)
{
if (x > 1000)
{
return 1000;
}
if (x > 500)
{
return 200;
}
if (x > 100)
{
return 100;
}
if (x > 50)
{
return 20;
}
if (x > 10)
{
return 10;
}
if (x > 5)
{
return 2;
}
return 1;
}
void display(int x)
{
auto f = factor(x);
for (int i = 1; i <= 5; ++i)
{
std::cout << f * i << " ";
}
std::cout << std::endl;
}
int main(int argc, char* argv[])
{
std::vector<int> test = { 1, 6, 11, 52, 103, 504, 1005 };
for (auto i: test)
{
display(i);
}
}
Output:
1 2 3 4 5
2 4 6 8 10
10 20 30 40 50
20 40 60 80 100
100 200 300 400 500
200 400 600 800 1000
1000 2000 3000 4000 5000
And a variation of factor that uses a table instead of a long chain of conditionals:
int factor(int x)
{
struct interval { int limit; int factor; };
interval intervals[] = {{1000, 1000},
{500, 200},
{100, 100},
{50, 20},
{10, 10},
{5, 2}};
for (auto i: intervals)
{
if (x > i.limit)
{
return i.factor;
}
}
return 1;
}

Related

Ribbon shape using for loop in C++

I've been trying all day creating different for loop combinations in c++ and I can't seem to get the right one.
I want my output to look like this:
Ribbon
How can you display this without using arrays?
EDIT: I tried like this but I can't replicate it on the opposite end. This has been so far the closest output I've got.
for(int i = 0; i < 6; i++)
{
cout<<"*";
for(int j = 5; j > i; j--)
{
cout<<" ";
}
for(int k = 0; k <= i; k++)
{
cout<<"*";
}
cout<<endl;
}
OUTPUT:
Fail ribbon
You have nine lines; let's number them 0 to 8. Line number n contains:
1 + (4 - abs(4 - n)) asterisks (1, 2, 3, 4, 5, 4, 3, 2, 1)
2 * abs (4 - n) spaces (8, 6, 4, 2, 0, 2, 4, 6, 8)
1 + (4 - abs(4 - n)) asterisks (1, 2, 3, 4, 5, 4, 3, 2, 1)
One option is to increment the number of stars on each row, then go back down once you reached the midpoint.
void printChar(char c, int count)
{
for (int i = 0; i < count; i++)
std::cout << c;
}
int main()
{
const int len = 10;
int stars = 0;
while (++stars <= len / 2)
{
int spaces = len - stars * 2;
printChar('*', stars);
printChar(' ', spaces);
printChar('*', stars);
std::cout << "\n";
}
stars--;
while (--stars > 0)
{
int spaces = len - stars * 2;
printChar('*', stars);
printChar(' ', spaces);
printChar('*', stars);
std::cout << "\n";
}
return 0;
}

Fibonacci Sum of Large Numbers(Only Last Digit to be Printed)

I have been trying to come out with a solution regarding the problem of finding the last digit of the sum of large n Fibonacci series.
I have been able to pass several test cases with large n. But I'm stuck at the following case where n = 832564823476. I know it can be solved using Pisano's period but I'm unable to come out with a efficient algo. Any help would be great. Thanks.
My code that I have implemented is as follows-
#include <iostream>
using namespace std;
int calc_fib(int n) {
int fib[n+1];
fib[0]=0;
fib[1]=1;
int res = 1;
for(int i = 2; i<=n;i++){
fib[i] = (fib[i-1]%10 + fib[i-2]%10)%10;
res = res + fib[i];
}
return (res%10);
}
int main() {
int n = 0;
std::cin >> n;
std::cout << calc_fib(n) << '\n';
return 0;
}
SOLVED IT
Works on all range of inputs. It works on the following algorithm.
The idea is to notice that the last digits of fibonacci numbers also occur in sequences of length 60 (from the previous problem: since pisano peiod of 10 is 60). Irrespective of how large n is, its last digit is going to have appeared somewhere within the sequence.
Two Things apart from edge case of 10 as last digit.
Sum of nth Fibonacci series = F(n+2) -1
Then pisano period of module 10 = let n+2 mod (60) = m then find F(m) mod(10)-1
Code as follows;
#include <iostream>
using namespace std;
long long calc_fib(long long n) {
n = (n+2)%60;
int fib[n+1];
fib[0]=0;
fib[1]=1;
int res = 1;
for(int i = 2; i<=n;i++){
fib[i] = (fib[i-1]%10 + fib[i-2]%10)%10;
// res = res + fib[i];
}
// cout<<fib[n]<<"\n";
if(fib[n] == 0){
return 9;
}
return (fib[n]%10-1);
}
int main() {
long long n = 0;
std::cin >> n;
std::cout << calc_fib(n) << '\n';
return 0;
}
Actually it's even easier than Niall answer
int get_fibonacci_sum_last_digit(long long n) {
const int kPisanoSize = 60;
int rest = n % kPisanoSize;
int preparedNumbers[kPisanoSize] = {0, 1, 2, 4, 7, 2, 0, 3, 4, 8, 3,
2, 6, 9, 6, 6, 3, 0, 4, 5, 0, 6, 7, 4, 2, 7, 0, 8, 9, 8, 8, 7,
6, 4, 1, 6, 8, 5, 4, 0, 5, 6, 2, 9, 2, 2, 5, 8, 4, 3, 8, 2, 1,
4, 6, 1, 8, 0, 9, 0};
return preparedNumbers[rest];
}
If you only need to output the last digit as you said, I think you can just make use of the Pisano Period you mentioned, as for modular 10, the cycle length is only 60 and you can just pre-make an array of that 60 digits.
If you want to compute by yourself, I think you can use Matrix Exponentiation which gives you O(lg N) complexity, when calculating the matrix exponents, keep storing the temporary result modular 10. See the Matrices section for your reference.
For your function removing the array.
#include "stdafx.h"
#include <iostream>
using namespace std;
int calc_fib(long long int n) {
int fibzero = 0;
int fibone = 1;
int fibnext;
long long int res = 1;
for (long long int i = 2; i <= n; i++) {
fibnext = (fibone + fibzero) % 10;
fibzero = fibone;
fibone = fibnext;
res = res + fibnext;
}
return (res % 10);
}
int main()
{
long long int n = 0;
std::cin >> n;
std::cout << calc_fib(n) << '\n';
return 0;
}
Last digit of Fibonacci sum repeats after 60 elements.
Here the period is 60 [0-59].
So to get the last digit of n'th sum of number is the last digit of n%60'th sum of
number
#include <iostream>
#include <vector>
#include <algorithm>
int get_last_digit(int n){
std::vector<int> last_digits(60);
long long a = 0, b = 1;
last_digits[0] = 0;
last_digits[1] = 1;
long long temp, sum = 1;
// Fill last_digits vector with the first 60 sums last digits
for (int i = 2; i < 60; i++) {
temp = a+b;
a = b;
b = temp;
sum += temp;
last_digits[i] = sum%10;
}
// Now return n%60'th element
return last_digits[n%60];
}
int main(int argc, char const *argv[]) {
int n;
std::cin>>n;
std::cout << get_last_digit(n);
return 0;
}
A neat way to solve the problem (I use java). The logic is to utilize the pisano period of 10. To write down the corresponding relationship between Sum(F(n)) = F(n+2) + 1 can help a lot. tip: create a fibonacci sequence alone.
private static long getFibonacciSum(long n) {
n = (n + 2) % 60;
long[] fib = new long[(int) n + 1];
long cor;
fib[0] = 0;
fib[1] = 1;
for (int i = 2; i <= n; i++) {
fib[i] = (fib[i - 1] + fib[i - 2]) % 10;
}
if (fib[(int) n] == 0) cor = 9;
else cor = fib[(int) n] - 1;
return cor;
}

c++ Increasing for loop increment logarithmically

I want to loop though integers like this:
1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, ..., 100, 200, ..., 1000, 2000, ...
I have code to do this (shown below) however it is cumbersome and not programmed generally to deal with different stopping limits:
int MAX = 10000;
for (int i = 1; i <= MAX; i++) {
cout << i << endl;
if (i >= 10 && i < 100) {
i += 9;
}
else if (i >= 100 && i < 1000) {
i+= 99;
}
else if (i >= 1000 && i < 10000) {
i += 999;
}
}
As you can see, this is very situation specified as mentioned previously - so I'd like to know of a way to code this in a more general way, as for my requirements MAX will be of the order of 10^9 so using code like above is far too impractical.
Try this code. It is more general:
int MAX = 1000000;
for (int i = 1, increment = 1, counter = 1; i <= MAX; i += increment) {
cout << i << endl;
if (counter == 10) {
increment *= 10;
counter = 1;
}
++counter;
}

Find the sum of digits of a sequence of integers

I made up my mind to write a little piece of code that gets two integers, lets say M and N ( M <= N ) and sum the digits of all the integers between them, inclusive. So for example if M = 1 and N = 9, DigitSum will equal to 45. If M = 10 and N = 11 the sum will be (1 + 0 (10) + 1 + 1 (11) = 3).
Here is my code so far (Done the for loop instead of the return):
#include <iostream>
#include <vector>
using namespace std;
// the partial digits sums digitSum[i] = the sum of the digits between 0 and i
int digitSum[] = {0, 1, 3, 6, 10, 15, 21, 28, 36, 45};
int pow_of_ten[] = {1, 10, 100, 1000, 10000, 100000, 1000000, 10000000, 100000000, 1000000000};
// the sums of all the digits in the numbers from 1 to (10^(i) - 1) where i is the index in the array
long subsums[] = {0, 45, 20 * 45, 300 * 45, 4000 * 45, 50000 * 45, 600000 * 45, 7000000 * 45, 80000000 * 45,
900000000 * 45};
//Calculates the sum of all digits between 0 and M inclusive
long Digit_Sum(int M) {
if (M < 10) {
return digitSum[M];
}
long result = 0;
int same = M;
int counter = 0;
int lastdigit = 0;
while (same > 0) {
if (same < 10) {
lastdigit = same;
break;
}
same /= 10;
counter ++;
}
for(;counter >= 0; counter --) {
result += (subsums[counter] + M % pow_of_ten[counter] + 1) * lastdigit;
result += digitSum[lastdigit - 1] * pow_of_ten[counter];
if (counter == 0) {
break;
}
lastdigit = (M / pow_of_ten[counter - 1]) % 10;
}
return result;
}
int main() {
int M;
int N;
vector<long> sums;
while (true) {
cin >> M >> N;
if (M == 0 && N == 0) {
break;
}
sums.push_back(Digit_Sum(N) - Digit_Sum(M - 1));
}
for (vector<long>::iterator it = sums.begin(); it != sums.end(); ++it) {
cout << *it << endl;
}
}
For most cases this works well but an Online judge says it is wrong. I looked at other solutions that work but no one hard-coded the values in arrays the way I did. May this cause a partial problem, any ideas?
You can easily just create a for-loop to greatly simplify this code.
There is no need to go through all that effort.
for (Initialization Action, Boolean Expression, Update_Action)
Re deletion below: sorry, I have a bit influenza and mizread N as M. :(
I think a main error is M-1 in
sums.push_back(Digit_Sum(N) - Digit_Sum(M - 1));
Also noting that <when corrected that formula will only work for single-digit numbers. My comment earlier about using a simple formula was based on misunderstanding your problem description, in view of that formula and your examples. Both indicated single digit numbers only.
However, the complexity of the code appears unreasonably high. Consider this, assuming non-negative integers as input, and assuming m is always less than or equal to n:
#include <iostream>
#include <stdexcept>
using namespace std;
bool throwX() { throw std::runtime_error( "Ouch." ); }
auto main() -> int
{
for( ;; )
{
int m, n;
cin >> m >> n || throwX();
if( m == 0 && n == 0 ) { break; }
int sum = 0;
for( int i = m; i <= n; ++i )
{
for( int v = i; v != 0; v /= 10 )
{
sum += v % 10;
}
}
cout << sum << endl;
}
}
It needs not be more complicated than that.
Tested and working to spec, sans console input:
#include <iostream>
#include <string>
using namespace std;
void sum_a_to_b(const int & a, const int & b)
{
if (a <= b && a >= 0)
{
long long sum = 0;
for (int i = a; i <= b; i++)
{
sum += i;
}
cout << "Sum of digits from " << a << " through " << b << " is " << sum << ".\n";
}
}
int main()
{
sum_a_to_b(5, 6);
sum_a_to_b(1, 9);
}

Find path with sum of numbers is maximum

I'm trying to find path with sum of numbers is maximum. It's only allowed to move right and down through the matrix.
I've coded it but it doesn't give me the maximum sum, and I can't figure out why it does so!.
Thanks in advance.
Here's my code
/*Given grid of positive numbers, strat from (0,0) ad end at (n,n).
Move only to RIGHT and DOWN. Find path with sum of numbers is maximum. */
#include<iostream>
using namespace std;
int grid[2][3] = { { 5, 1, 2 }, { 6, 7, 8 } };
int max(int x, int y){
if (x >= y){
return x;
}
else if (x < y){
return y;
}
}
bool valid(int r, int c){
if (r + 1 == 2 || c + 1 == 3)
return false;
else
return true;
}
int maxPathSum(int row, int column){
if (!valid(row, column))
return 0;
if (row == 1 && column == 2) //base condition
return grid[row][column];
int path1 = maxPathSum(row, column + 1); //Right
int path2 = maxPathSum(row + 1, column); //Down
return grid[row][column] + max(path1, path2);
}
int main()
{
cout << maxPathSum(0, 0) << endl;
return 0;
}
the correct answer should be 26, but the output is 6.
Your function Valid should be
bool valid (int r, int c)
{
return r < 2 && c < 3;
}
and then you got 26 (Live example).
BTW, you may use dynamic programming for this problem.
You can also use dynamic programming to solve the problem
Here is the code:
#include <bits/stdc++.h>
using namespace std;
int grid[2][3] = { { 5, 1, 2 }, { 6, 7, 8 } };
int dp[3][4];
int main()
{
for(int i=0;i<4;i++)
dp[0][i] = 0;
for(int i=0;i<3;i++)
dp[i][0] = 0;
for(int i=1;i<3;i++)
{
for(int j=1;j<4;j++)
{
dp[i][j] = grid[i-1][j-1] + max(dp[i][j-1], dp[i-1][j]);
}
}
cout << dp[2][3];
return 0;
}
Live example
Apart from DP, you can also use simple (n,m) Matrix based solution. The good part is this approach wont need recursion as DP does which can cause memory issues if matrix is bigger and space complexity is just O(n x m) i.e. input array itself. And the time complexity is also O(n x m). Following code in java illustrate the approach -
package com.company.dynamicProgramming;
import static java.lang.Integer.max;
public class MaxSumPathInMatrix {
public static void main (String[] args)
{
int mat[][] = { { 10, 10, 2, 0, 20, 4 },
{ 1, 0, 0, 30, 2, 5 },
{ 200, 10, 4, 0, 2, 0 },
{ 1, 0, 2, 20, 0, 4 }
};
System.out.println(findMaxSum2(mat));
}
/*
Given a matrix of N * M. Find the maximum path sum in matrix.
Find the one path having max sum - originating from (0,0) with traversal to either right or down till (N-1, M-1)
*/
static int findMaxSum2(int mat[][])
{
int M = mat[0].length;
int N = mat.length;
for (int i = 0; i < N; i++)
{
for (int j = 0; j < M; j++)
{
if(i==0 && j!=0){
mat[i][j]+=mat[i][j-1];
}
else if(i!=0 && j==0){
mat[i][j]+=mat[i-1][j];
}
else if (i!=0 && j!=0){
mat[i][j]+= max(mat[i-1][j], mat[i][j-1]);
}
}
}
return mat[N-1][M-1];
}
}
Run it as -
251
Process finished with exit code 0
Further Even if you are using Dynamic Programming(DP) then use Memoization concept to reduce the time complexity.. Here is the code with DP plus memoization along complexity calculation -
package com.company.dynamicProgramming;
import java.util.HashMap;
import java.util.Map;
import static java.lang.Integer.max;
public class MaxSumPathInMatrix {
static int complexity = 0;
public static void main (String[] args)
{
int mat[][] = { { 10, 10, 2, 0, 20, 4 },
{ 1, 0, 0, 30, 2, 5 },
{ 200, 10, 4, 0, 2, 0 },
{ 1, 0, 2, 20, 0, 4 }
};
System.out.println("Max Sum : " + findMaxSum2_dp(mat, 0, 0, new HashMap<>()));
System.out.println("Time complexity : " +complexity);
}
/*
~~~> solve via ~dp~ and ~memoization~
Given a matrix of N * M. Find the maximum path sum in matrix.
Find the one path having max sum - originating from (0,0) with traversal to either right or down till (m-1, n-1)
*/
static int findMaxSum2_dp(int mat[][], int i, int j, Map<String, Integer> memo){
int M = mat[0].length;
int N = mat.length;
Integer sum = memo.get(i+"-"+j);
if(sum!= null){
return sum;
}
complexity++;
if(i==N-1 && j<M-1){
mat[i][j] += findMaxSum2_dp(mat, i, j+1, memo);
memo.put(i+"-"+j, mat[i][j]);
return mat[i][j];
}
else if(i<N-1 && j==M-1){
mat[i][j] += findMaxSum2_dp(mat, i+1, j, memo);
memo.put(i+"-"+j, mat[i][j]);
return mat[i][j];
}
else if (i<N-1 && j<M-1){
int s1 = findMaxSum2_dp(mat, i+1, j, memo);
int s2 = findMaxSum2_dp(mat, i, j+1, memo);
mat[i][j] += max(s1, s2);
memo.put(i+"-"+j, mat[i][j]);
return mat[i][j];
}
return mat[N-1][M-1] += max(mat[N-1][M-2], mat[N-2][M-1]);
}
}
Two important points to note in above code -
I am storing max sum of any sub matrix [i][j] in a store(HashMap), whenever it's max sum is ready. And in further steps if this sub matrix [i][j] reappears then I take it from store instead of processing again. As a illustration - you can see [N-1][M-1] appears 2 times in below diagram of recursion -
[N][M] = max([N][M-1]) , [N-1][M]
/ \
/ \
/ \
[N][M-1] = max ([N-1][M-1], [N][M-2]) [N-1][M] = max ([N-2][M], [N-1][M-1])
Connected with Point 1 : I have provisioned a complexity variable which I increment if I have to calculate max sum for matrix [i][j] i.e. wont find in the store. If you see the result it shows 25 in 6x4 matrix i.e. the time complexity is just O(NxM).