I am doing an assignment where I must use nested loops in order to add up the squares and cubes of integers from 1 to N (N being whatever the user inputs). For example, if the user input the number 5, the program is supposed to do "1²+2²+3²+4²+5²" and output the sum of those numbers, as well "1³+2³+3³+4³+5³" and output the sum of those numbers.
However, I am having trouble figuring out how to code it in a way that I receive the proper output? This is what I wrote. Scanners were already added.
int limitNum = input.nextInt();
double squareNums:
double sumofSq = 0;
double cubedNums;
double sumofCubes = 0;
for(int s = 1; s <= limitNum; s++)
{
for(int c = 1; c <= limitNum; c++)
{
cubedNums = Math.pow(c, 3);
sumofCubes = sumofCubes + cubedNums;
}
squareNums= Math.pow(s, 2);
sumofSq = sumofSq + squareNums;
}
But currently, when I run this program, the sum of the squares output correctly, but the sum of the cubes is always some big number. For example if 5 is used, sumofSq would output 55.0, but sumofCubes would output 1125.0.
There is no point using a nested loop as this would result in complexity of O(n²). A single loop would be sufficient and be in complexity class O(n).
public class Application {
public static void main(String[] args) {
var squareSum = 0d;
var cubeSum = 0d;
var upperBound = 5;
for(var i = 1; i <= upperBound; i++){
squareSum += Math.pow(i, 2);
cubeSum += Math.pow(i, 3);
}
System.out.printf("""
Sum of first n squares: %s
Sum of first n cubes: %s
""", (int)squareSum, (int)cubeSum);
}
}
In fact there is no need to loop at all => constant computation time no matter the size of the input O(1). There is a well known formula which tells you the sum of the first n squares.
n(n+1)(2n+1)
------------
6
Please see this for a proof.
The same holds true for the first n cubes.
n²(n+1)²
--------
4
Please see this for a proof.
The following program will therefore return the same result.
public class Application {
public static void main(String[] args) {
var upperBound = 5;
System.out.printf("""
Sum of first n squares: %s
Sum of first n cubes: %s
""", sumOfFirstNSquares(upperBound), sumOfFirstNCubes(upperBound));
}
public static int sumOfFirstNSquares(int n){
return (n * (n+1) * (2 * n + 1)) / 6;
}
public static int sumOfFirstNCubes(int n){
return ((n * n) * (n+1) * (n+1)) / 4;
}
}
In fact there is no need to loop at all => constant computation time no matter the size of the input O(1). There is a well known formula which tells you the sum of the first n squares.
java
Related
The Challenge:
For example, what is the probability of getting the sum of 15 when using 3 six-sided dice. This can be for example by getting 5-5-5 or 6-6-3 or 3-6-6 or many more options.
A brute force solution for 2 dice - with complexity of 6^2:
Assuming we had only 2 six-sided dice, we can write a very basic code like that:
public static void main(String[] args) {
System.out.println(whatAreTheOdds(7));
}
public static double whatAreTheOdds(int wantedSum){
if (wantedSum < 2 || wantedSum > 12){
return 0;
}
int wantedFound = 0;
int totalOptions = 36;
for (int i = 1; i <= 6; i++) {
for (int j = 1; j <= 6; j++) {
int sum = i+j;
if (sum == wantedSum){
System.out.println("match: " + i + " " + j );
wantedFound +=1;
}
}
}
System.out.println("combinations count:" + wantedFound);
return (double)wantedFound / totalOptions;
}
And the output for 7 will be:
match: 1 6
match: 2 5
match: 3 4
match: 4 3
match: 5 2
match: 6 1
combination count:6
0.16666666666666666
The question is how to generalize the algorithm to support N dice:
public static double whatAreTheOdds(int wantedSum, int numberOfDices)
Because we can't dynamically create nested for loops, we must come with a different approach.
I thought of something like that:
public static double whatAreTheOdds(int sum, int numberOfDices){
int sum;
for (int i = 0; i < numberOfDices; i++) {
for (int j = 1; j <= 6; j++) {
}
}
}
but failed to come up with the right algorithm.
Another challenge here is - is there a way to do it efficiently, and not in a complexity of 6^N?
Here is a recursive solution with memoization to count the combinations.
import java.util.Arrays;
import java.lang.Math;
class Dices {
public static final int DICE_FACES = 6;
public static void main(String[] args) {
System.out.println(whatAreTheOdds(40, 10));
}
public static double whatAreTheOdds(int sum, int dices) {
if (dices < 1 || sum < dices || sum > DICE_FACES * dices) return 0;
long[][] mem = new long[dices][sum];
for (long[] mi : mem) {
Arrays.fill(mi, 0L);
}
long n = whatAreTheOddsRec(sum, dices, mem);
return n / Math.pow(DICE_FACES, dices);
}
private static long whatAreTheOddsRec(int sum, int dices, long[][] mem) {
if (dices <= 1) {
return 1;
}
long n = 0;
int dicesRem = dices - 1;
int minFace = Math.max(sum - DICE_FACES * dicesRem, 1);
int maxFace = Math.min(sum - dicesRem, DICE_FACES);
for (int i = minFace; i <= maxFace; i++) {
int sumRem = sum - i;
long ni = mem[dicesRem][sumRem];
if (ni <= 0) {
ni = whatAreTheOddsRec(sumRem, dicesRem, mem);
mem[dicesRem][sumRem] = ni;
}
n += ni;
}
return n;
}
}
Output:
0.048464367913724195
EDIT: For the record, the complexity of this algorithm is still O(6^n), this answer just aims to give a possible implementation for the general case that is better than the simplest implementation, using memoization and search space prunning (exploring only feasible solutions).
As Alex's answer notes, there is a combinatorial formula for this:
In this formula, p is the sum of the numbers rolled (X in your question), n is the number of dice, and s is the number of sides each dice has (6 in your question). Whether the binomial coefficients are evaluated using loops, or precomputed using Pascal's triangle, either way the time complexity is O(n2) if we take s = 6 to be a constant and X - n to be O(n).
Here is an alternative algorithm, which computes all of the probabilities at once. The idea is to use discrete convolution to compute the distribution of the sum of two random variables given their distributions. By using a divide and conquer approach as in the exponentiation by squaring algorithm, we only have to do O(log n) convolutions.
The pseudocode is below; sum_distribution(v, n) returns an array where the value at index X - n is the number of combinations where the sum of n dice rolls is X.
// for exact results using integers, let v = [1, 1, 1, 1, 1, 1]
// and divide the result through by 6^n afterwards
let v = [1/6.0, 1/6.0, 1/6.0, 1/6.0, 1/6.0, 1/6.0]
sum_distribution(distribution, n)
if n == 0
return [1]
else if n == 1
return v
else
let r = convolve(distribution, distribution)
// the division here rounds down
let d = sum_distribution(r, n / 2)
if n is even
return d
else
return convolve(d, v)
Convolution cannot be done in linear time, so the running time is dominated by the last convolution on two arrays of length 3n, since the other convolutions are on sufficiently shorter arrays.
This means if you use a simple convolution algorithm, it should take O(n2) time to compute all of the probabilities, and if you use a fast Fourier transform then it should take O(n log n) time.
You might want to take a look at Wolfram article for a completely different approach, which calculates the desired probability with a single loop.
The idea is to have an array storing the current "state" of each dice, starting will every dice at one, and count upwards. For example, with three dice you would generate the combinations:
111
112
...
116
121
122
...
126
...
665
666
Once you have a state, you can easily find if the sum is the one you are looking for.
I leave the details to you, as it seems a useful learning exercise :)
This code calculates the function f(x) = -1 + 2 + -3 + 4 + ... + (( - 1)^n)*n
But when the input(n) is too big, like 1000000000, java doesn't display an output.
What can I do to solve this problem?
import java.util.Scanner;
public class Calculating_function {
public static void main(String[] args) {
Scanner input_taker = new Scanner(System.in);
String n_string = input_taker.nextLine();
long n = Long.parseLong(n_string);
System.out.println(fonk(n));
}
public static long fonk(long n) {
long total = 0;
for(long i = 1; i <= n; i++) {
total += (long)Math.pow(-1, i) * i;
}
return total;
}
As the value of i increases, your exponent calculation Math.pow(-1, i) will take longer and longer to calculate.
As you're using Math.pow(-1, i) to simply swap the sign, you can optimize it as Math.pow(-1, i%2). Better yet, map the multiplier to the values 1 and -1 and use i%2 as your key.
Additionally, you are risking overflows as your total has an upper bound of 500,000,000,000,000,000 so use BigInteger instead to store the total.
e can be approximated using the formula e = 1 + (1/1!) + (1/2!) + (1/3!)... + (1/n!). I am trying to use for loops to accept whatever integer the user sets n to be. The program should approximate e by using the formula above from (1/1!) + .... (1/n!) and out put the result.
The nested for loop calculates the factorial of n (tested it separately and it works) and the variable defined, frac, puts the factorial into a fraction of 1/(answer to factorial). I store the value into a variable e and it should add the new fraction to the old value every time an iteration is done. I cannot not understand what is wrong with my loops that they are not out putting the right answer.
System.out.println("Enter an integer to show the result of
approximating e using n number of terms.");
int n=scan.nextInt();
double e=1;
double result=1;
for(int i=1; n>=i; n=(n-1))
{
for(int l=1; l<=n; l++)
{
result=result*l;
}
double frac=(1/result);
e=e+frac;
}
System.out.println(e);
Output when I enter the integer 7 as n = 1.0001986906956286
You don't need that whole inner loop. All you need is result *= i.
for (int i = 1; i <= n; i++)
{
result *= i;
double frac = (1 / result);
e += frac;
}
Here's a JavaScript version I just threw together:
function init() {
const elem = document.getElementById('eapprox');
let eapprox = 1;
const n = 15;
let frac = 1;
for (var i = 1; i <= n; ++i) {
frac /= i;
eapprox += frac;
}
elem.textContent = eapprox;
}
This yields 2.718281828458995. Plunker here: http://plnkr.co/edit/OgXbr36dKce21urHH1Ge?p=preview
I am trying to practice java over the summer and i'm stuck on this problem. I need to swap the 2 letters in a integer in java. For example in my main method I make a method called swapdigits and have my parameters as 1432. The program should swap the 4 and 1 and 3 and 2. The output should be 4123 since it swapped the two letters in order. Lets say I do swapdigits(1341234) the output should be 3114324. I know I have to use while loops but i'm getting stuck on the swapping.
This is what I have so far:
public static void main(String[] args) {
Swapdigits(2413);
}
public static void Swapdigits(int number){
while(number>0){
int y=number/1000;
int x=number%10;
int original=number-y;
System.out.println(original);
}
System.out.println();
}
}
public static int swapDigitPairs(int number) {
int result = 0;
int place = 1;
while (number > 9) {
result += place * 10 * (number % 10);
number /= 10;
result += place * (number % 10);
number /= 10;
place *= 100;
}
return result + place * number;
}
You can also try
char[] a = String.valueOf(number).toCharArray();
for (int i = 0; i < a.length - 1; i += 2) {
char tmp = a[i];
a[i] = a[i + 1];
a[i + 1] = tmp;
}
int number = Integer.parseInt(new String(a));
Because you're just swapping the places of digits, it doesn't actually matter what the number is. So, it's probably easier (and makes more sense) to represent the argument as a string. That way you aren't dealing with weird modulo operators - If you were solving the problem by hand, would you actually do any math? You'd treat this problem the same whether it were numbers of a bunch of characters.
Take a look at the following question for information on swapping characters in a String:
How to swap String characters in Java?
I'm working on a practice program at InterviewStreet and I have a solution that runs with a time of 5.15xx seconds, while the maximum time allowed for a java solution is 5 seconds. Is there anything I can do with what I've got here to get it under 5 seconds? There's also a limit of 256 MB so as near as I can tell this is both the most time and memory efficient solution to the problem...
edit:
The possible values for N and K are N <= 10^9 and K <= N, which is why I chose to do everything using BigInteger. The maximum number of trials is 10000. So basically, you input the number of trials, then a pair of integer values for each number of trials, and the program computes the three versions of the binomial coefficient for the equation in the second loop. I figured it would be faster to read everything into the arrays, then process the arrays and put the results into a third array to be processed by the third loop because I figured it might be faster that way. I tried doing everything in the same loop and it ran slower.
I've tried three or four different algorithms for calculating the binomial coefficient (nCr - or n choose r, all are different ways of saying the same thing). Some of the algorithms involve a two dimensional array like c[n][k]. This is the only solution I've submitted that didn't come back with some sort of memory error. The answer needs to be output mod (10 ^ 6) + 3 because the answers of nCr * nCr get pretty huge. A sample run of the program is:
3
4 1
5 2
90 13
2
5
815483
Can't run it on a faster machine because it needs to pass on their machine to count, basically I submit the code and they run it against their test cases, and I have no idea what their test case is, just that the inputs are within the bounds given above.
And the program itself:
import java.math.BigInteger;
import java.util.Scanner;
public class Solution {
public BigInteger nCr(int n, int r) {
if (r > n ) {
return BigInteger.ZERO;
}
if (r > n / 2) {
r = n - r;
}
BigInteger result = BigInteger.ONE;
for (int i = 0; i < r; i++) {
result = result.multiply(BigInteger.valueOf(n - i));
result = result.divide(BigInteger.valueOf(i + 1));
}
return result;
}
public static void main(String[] args) {
Scanner input = new Scanner( System.in );
BigInteger m = BigInteger.valueOf(1000003);
Solution p = new Solution();
short T = input.nextShort(); // Number of trials
BigInteger intermediate = BigInteger.ONE;
int[] r = new int[T];
int[] N = new int[T];
int[] K = new int[T];
short x = 0;
while (x < T) {
N[x] = input.nextInt();
K[x] = input.nextInt();
x++;
}
x = 0;
while (x < T) {
if (N[x] >= 3) {
r[x] = ((p.nCr(N[x] - 3, K[x]).multiply(p.nCr(N[x] + K[x], N[x] - 1))).divide(BigInteger.valueOf((N[x] + K[x]))).mod(m)).intValue();
} else {
r[x] = 0;
}
x++;
}
x = 0;
while (x < T) {
System.out.println(r[x]);
x++;
}
}
}
Not entirely sure what the algorithm is trying to accomplish but I'm guessing something with binomial coefficients based on your tagging of the post.
You'll need to check if my suggestion modifies the result but it looks like you could merge two of your while loops:
Original:
while (x < T) {
N[x] = input.nextInt();
K[x] = input.nextInt();
x++;
}
x = 0;
while (x < T) {
if (N[x] >= 3) {
r[x] = ((p.nCr(N[x] - 3, K[x]).multiply(p.nCr(N[x] + K[x], N[x] - 1))).divide(BigInteger.valueOf((N[x] + K[x]))).mod(m)).intValue();
} else {
r[x] = 0;
}
x++;
}
New:
x = 0;
while (x < T) {
//this has been moved from your first while loop
N[x] = input.nextInt();
K[x] = input.nextInt();
if (N[x] >= 3) {
r[x] = ((p.nCr(N[x] - 3, K[x]).multiply(p.nCr(N[x] + K[x], N[x] - 1))).divide(BigInteger.valueOf((N[x] + K[x]))).mod(m)).intValue();
} else {
r[x] = 0;
}
x++;
}
try to run using a profilerm for example the jvisualvm and run this class with
-Dcom.sun.management.jmxremote
attach to the process and start a profile.