I have this code below, I would like to know how to calculate the number of swaps. I used a count variable to figure it out, but I was getting different number than the computer. I figure the number of swaps would be 2 * (n - 1)(n - 2)...(n - n + 1). For n == 4, the computer got 128, and I got 48. What am I doing wrong?
public void permute(int n) {
if (n == 1) {
printOutPut();
}
for (int i = 1; i <= n; i++){
swap(i, n);
permute1(n-1);
swap(i, n);
}
}
The code defines a recursion:
num_swaps(0) = 0
num_swaps(i) = i * (num_swaps(i - 1) + 2)
or with more math-like symbols:
s_{n+1} = (n + 1) (s_n + 2)
s_0 = 0
s_1 = 2
s_2 = 8
s_3 = 30
s_4 = 128
You can probably solve that recursion for a general n using techniques from maths, but this verifies that the computer is right
Edit: I was trying to find a solution for general n, ended up on wolfram alpha and the solution presented had incomplete gamma functions and stuff. So, don't expect the calculation to be easy!
Related
I am trying to write a Java method that checks whether a number is a perfect number or not.
A perfect number is a number that is equal to the sum of all its divisor (excluding itself).
For example, 6 is a perfect number because 1+2+3=6. Then, I have to write a Java program to use the method to display the first 5 perfect numbers.
I have no problem with this EXCEPT that it is taking forever to get the 5th perfect number which is 33550336.
I am aware that this is because of the for loop in my isPerfectNumber() method. However, I am very new to coding and I do not know how to come up with a better code.
public class Labreport2q1 {
public static void main(String[] args) {
//Display the 5 first perfect numbers
int counter = 0,
i = 0;
while (counter != 5) {
i++;
isPerfectNumber(i);
if (isPerfectNumber(i)) {
counter++;
System.out.println(i + " ");
}
}
}
public static boolean isPerfectNumber(int a) {
int divisor = 0;
int sum = 0;
for (int i = 1; i < a; i++) {
if (a % i == 0) {
divisor = i;
sum += divisor;
}
}
return sum == a;
}
}
This is the output that is missing the 5th perfect number
Let's check the properties of a perfect number. This Math Overflow question tells us two very interesting things:
A perfect number is never a perfect square.
A perfect number is of the form (2k-1)×(2k-1).
The 2nd point is very interesting because it reduces our search field to barely nothing. An int in Java is 32 bits. And here we see a direct correlation between powers and bit positions. Thanks to this, instead of making millions and millions of calls to isPerfectNumber, we will be making less than 32 to find the 5th perfect number.
So we can already change the search field, that's your main loop.
int count = 0;
for (int k = 1; count < 5; k++) {
// Compute candidates based on the formula.
int candidate = (1L << (k - 1)) * ((1L << k) - 1);
// Only test candidates, not all the numbers.
if (isPerfectNumber(candidate)) {
count++;
System.out.println(candidate);
}
}
This here is our big win. No other optimization will beat this: why test for 33 million numbers, when you can test less than 100?
But even though we have a tremendous improvement, your application as a whole can still be improved, namely your method isPerfectNumber(int).
Currently, you are still testing way too many numbers. A perfect number is the sum of all proper divisors. So if d divides n, n/d also divides n. And you can add both divisors at once. But the beauty is that you can stop at sqrt(n), because sqrt(n)*sqrt(n) = n, mathematically speaking. So instead of testing n divisors, you will only test sqrt(n) divisors.
Also, this means that you have to start thinking about corner cases. The corner cases are 1 and sqrt(n):
1 is a corner case because you if you divide n by 1, you get n but you don't add n to check if n is a perfect number. You only add 1. So we'll probably start our sum with 1 just to avoid too many ifs.
sqrt(n) is a corner case because we'd have to check whether sqrt(n) is an integer or not and it's tedious. BUT the Math Overflow question I referenced says that no perfect number is a perfect square, so that eases our loop condition.
Then, if at some point sum becomes greater than n, we can stop. The sum of proper divisors being greater than n indicates that n is abundant, and therefore not perfect. It's a small improvement, but a lot of candidates are actually abundant. So you'll probably save a few cycles if you keep it.
Finally, we have to take care of a slight issue: the number 1 as candidate. 1 is the first candidate, and will pass all our tests, so we have to make a special case for it. We'll add that test at the start of the method.
We can now write the method as follow:
static boolean isPerfectNumber(int n) {
// 1 would pass the rest because it has everything of a perfect number
// except that its only divisor is itself, and we need at least 2 divisors.
if (n < 2) return false;
// divisor 1 is such a corner case that it's very easy to handle:
// just start the sum with it already.
int sum = 1;
// We can stop the divisors at sqrt(n), but this is floored.
int sqrt = (int)Math.sqrt(n);
// A perfect number is never a square.
// It's useful to make this test here if we take the function
// without the context of the sparse candidates, because we
// might get some weird results if this method is simply
// copy-pasted and tested on all numbers.
// This condition can be removed in the final program because we
// know that no numbers of the form indicated above is a square.
if (sqrt * sqrt == n) {
return false;
}
// Since sqrt is floored, some values can still be interesting.
// For instance if you take n = 6, floor(sqrt(n)) = 2, and
// 2 is a proper divisor of 6, so we must keep it, we do it by
// using the <= operator.
// Also, sqrt * sqrt != n, so we can safely loop to sqrt
for (int div = 2; div <= sqrt; div++) {
if (n % div == 0) {
// Add both the divisor and n / divisor.
sum += div + n / div;
// Early fail if the number is abundant.
if (sum > n) return false;
}
}
return n == sum;
}
These are such optimizations that you can even find the 7th perfect number under a second, on the condition that you adapt the code for longs instead of ints. And you could still find the 8th within 30 seconds.
So here's that program (test it online). I removed the comments as the explanations are here above.
public class Main {
public static void main(String[] args) {
int count = 0;
for (int k = 1; count < 8; k++) {
long candidate = (1L << (k - 1)) * ((1L << k) - 1);
if (isPerfectNumber(candidate)) {
count++;
System.out.println(candidate);
}
}
}
static boolean isPerfectNumber(long n) {
if (n < 2) return false;
long sum = 1;
long sqrt = (long)Math.sqrt(n);
for (long div = 2; div <= sqrt; div++) {
if (n % div == 0) {
sum += div + n / div;
if (sum > n) return false;
}
}
return n == sum;
}
}
The result of the above program is the list of the first 8 perfect numbers:
6
28
496
8128
33550336
8589869056
137438691328
2305843008139952128
You can find further optimization, notably in the search if you check whether 2k-1 is prime or not as Eran says in their answer, but given that we have less than 100 candidates for longs, I don't find it useful to potentially gain a few milliseconds because computing primes can also be expensive in this program. If you want to check for bigger perfect primes, it makes sense, but here? No: it adds complexity and I tried to keep these optimization rather simple and straight to the point.
There are some heuristics to break early from the loops, but finding the 5th perfect number still took me several minutes (I tried similar heuristics to those suggested in the other answers).
However, you can rely on Euler's proof that all even perfect numbers (and it is still unknown if there are any odd perfect numbers) are of the form:
2i-1(2i-1)
where both i and 2i-1 must be prime.
Therefore, you can write the following loop to find the first 5 perfect numbers very quickly:
int counter = 0,
i = 0;
while (counter != 5) {
i++;
if (isPrime (i)) {
if (isPrime ((int) (Math.pow (2, i) - 1))) {
System.out.println ((int) (Math.pow (2, i -1) * (Math.pow (2, i) - 1)));
counter++;
}
}
}
Output:
6
28
496
8128
33550336
You can read more about it here.
If you switch from int to long, you can use this loop to find the first 7 perfect numbers very quickly:
6
28
496
8128
33550336
8589869056
137438691328
The isPrime method I'm using is:
public static boolean isPrime (int a)
{
if (a == 1)
return false;
else if (a < 3)
return true;
else {
for (int i = 2; i * i <= a; i++) {
if (a % i == 0)
return false;
}
}
return true;
}
Given an integer A representing the square blocks. The height of each square block is 1. The task is to create a staircase of max height using these blocks. The first stair would require only one block, the second stair would require two blocks and so on. Find and return the maximum height of the staircase.
Your submission failed for the following input: A : 92761
Your function returned the following : 65536
The expected returned value : 430
Approach:
We are interested in the number of steps and we know that each step Si uses exactly Bi number of bricks. We can represent this problem as an equation:
n * (n + 1) / 2 = T (For Natural number series starting from 1, 2, 3, 4, 5 …)
n * (n + 1) = 2 * T
n-1 will represent our final solution because our series in problem starts from 2, 3, 4, 5…
Now, we just have to solve this equation and for that we can exploit binary search to find the solution to this equation. Lower and Higher bounds of binary search are 1 and T.
CODE
public int solve(int A) {
int l=1,h=A,T=2*A;
while(l<=h)
{
int mid=l+(h-l)/2;
if((mid*(mid+1))==T)
return mid;
if((mid*(mid+1))>T && (mid!=0 && (mid*(mid-1))<=T) )
return mid-1;
if((mid*(mid+1))>T)
h=mid-1;
else
l=mid+1;
}
return 0;
}
To expand on the comment by Matt Timmermans:
You know that for n steps, you need (n * (n + 1))/2 blocks. You want know, if given B blocks, how many steps you can create.
So you have:
(n * (n + 1))/2 = B
(n^2 + n)/2 = B
n^2 + n = 2B
n^2 + n - 2B = 0
That looks suspiciously like something for which you'd use the quadratic formula.
In this case, a=1, b=1, and c=(-2B). Plugging the numbers into the formula:
n = ((-b) + sqrt(b^2 - 4*a*c))/(2*a)
= (-1 + sqrt(1 - 4*1*(-2B)))/(2*a)
= (-1 + sqrt(1 + 8B))/2
= (sqrt(1 + 8B) - 1)/2
So if you have 5050 blocks, you get:
n = (sqrt(1 + 40400) - 1)/2
= (sqrt(40401) - 1)/2
= (201 - 1)/2
= 100
Try it with the quadratic formula calculator. Use 1 for the value of a and b, and replace c with negative two times the number of blocks you're given. So in the example above, c would be -10100.
In your program, since you can't have a partial step, you'd want to truncate the result.
Why are you using all these formulas? A simple while() loop should do the trick, eventually, it's just a simple Gaussian Sum ..
public static int calculateStairs(int blocks) {
int lastHeight = 0;
int sum = 0;
int currentHeight = 0; //number of bricks / level
while (sum <= blocks) {
lastHeight = currentHeight;
currentHeight++;
sum += currentHeight;
}
return lastHeight;
}
So this should do the job as it also returns the expected value. Correct me if im wrong.
public int solve(int blocks) {
int current; //Create Variables
for (int x = 0; x < Integer.MAX_VALUE; x++) { //Increment until return
current = 0; //Set current to 0
//Implementation of the Gauss sum
for (int i = 1; i <= x; i++) { //Sum up [1,*current height*]
current += i;
} //Now we have the amount of blocks required for the current height
//Now we check if the amount of blocks is bigger than
// the wanted amount, and if so we return the last one
if (current > blocks) {
return x - 1;
}
}
return current;
}
as a beginner in programming I am trying to convert the following recursive method to an iterative one but I just don't get the hang of it. The method or function has a binary tree like recursion and I would like to use an array for the iterative solution.. unfortunately I am very confused how to do it.
I have already checked the way of converting the fibonnaci recursive method to an iterative one. But I think this is not the same here. Also I am not sure if a tree search method is useful?! Any help, hint, idea would be appreciated. Thanks.
public static int funct(int n) {
if (n == 0) return 1;
if (n == 1) return 2;
if n > 1 return funct(n-2)*funct(n/2);
}
Since every n-th member is computed by others before if you can cache all in a list. You start by adding the first 2 known members. Fibonacci its easier because you always need only previous value.
private static int func(int n) {
List<Integer> values = new ArrayList<>(n+1);
values.add(1);
values.add(2);
for (int i = 2; i <= n; i++) {
values.add(values.get(i - 2) * values.get(i / 2));
}
return values.get(n);
}
Now the real function is without last if:
public static int funct(int n) {
if (n == 0) return 1;
if (n == 1) return 2;
return funct(n-2) * funct(n/2);
}
As the recursive calls refer to smaller parameters one can cache all return values upto n.
Unfortunately this already spoils the pleasure, as the resulting code is complete:
public static int funct(int n) {
int[] results = new int[n+1];
results[0] = 1;
results[1] = 2;
int i = 2;
while (i <= n) {
results[i] = results[i-2] * results[i/2];
++i;
}
return results[n];
}
It indeed looks like fibonacci.
In general one would not need to fill all items of results. like probably results[n - 1].
Unfortunately you should have learnt prior to this problem:
Solving tail recursion.
Using a stack (like here) to use inner results of a recurive call.
You might look into those topics.
Math afterlude
The initial values are powers of 2. As the result is a product of earlier results, all results will be powers of 2.
f(0) = 1 = 2^0
f(1) = 2 = 2^1
f(n) = f(n - 2) * f(n / 2)
Hence you can introduce:
g(0) = 0
g(1) = 1
g(n) = g(n - 2) + g(n / 2)
f(n) = 2^g(n)
This will enlarge the range you can calculate as say 2100.
You will also see:
g(2k + 1) = g(2k) + 1
So you will only need a domain of even numbers:
g(2k) = g(2(k-1)) + g(k - k%2) + k%2
Is there a difference between the way that the Modulo operates calculates values in Java vs the way that it does in VBScript?
Both of these are returning a digit that I am using as part of a larger number later in the code but I believe the issue is between the way VBScript and Java are handling the Mod operator. I may be wrong though.
I am trying to work through reasons why I am seeing different outputs from when I run the below VBscript code block vs my replicated version in Java, sorry for the delay in updating the post.
The function takes in a String and then works to determine a return digit based upon the logic in the loop. The missing code just has to do with initializing the variables used, and determining the length of the string to loop over.
Any help would be greatly appreciated! Thank you
VBScript:
For i=1 to Length
CurrentNumber = Mid(CCNumber,i,1)
CurrentNumber = Int(CurrentNumber)
If (i mod 2) <> 0 then
ModNumber = CurrentNumber * 2
If ModNumber > 9 then
Total = Total + 1 + (ModNumber mod 10)
Else
Total = Total + ModNumber
End If
Else
Total = Total + CurrentNumber
End If
Next
cd = ((Int(Total/10) + 1) * 10) - Total
if cd = 10 then cd = 0
CheckDigit = cd
Java:
for (i=0; i<length; i++)
{
String currentNumberString = CCNumber.substring(i,i+1);
currentNumber = Integer.valueOf(currentNumberString);
if (i % 2 != 0)
{
Integer ModNumber = currentNumber * 2;
if (ModNumber > 9)
{
total = total + 1 + (ModNumber % 10);
}
else
{
total = total + ModNumber;
}
}
else
{
total = total + currentNumber;
}
}
int cd = ((Integer.valueOf(total/10) + 1) * 10) - total;
if (cd == 10)
{
cd = 0;
}
return cd;
}
One difference: The Mod operator in VBScript always returns an integer. Java's % operator can return a fractional value. So 5.2 Mod 2 evaluates to 1 in VBScript, but 5.2 % 2 evaluates to 1.2 in Java.
Edit: Based on your edit, this appears to be the Luhn algorithm. The only real problem with the Java code is a typo; nothing to do with the mod operator. Here you assign a variable currrentNumber (with a triple R):
currrentNumber = Integer.valueOf(currentNumberString);
Then you use a different variable (double R):
Integer ModNumber = currentNumber * 2;
Edit: Another difference is that because VBScript string indices start at 1, and Java string indices start at 0, the code is using different alternate digits. Either If (i mod 2) <> 0 should be If (i mod 2) = 0, or if (i % 2 != 0) should be if (i % 2 == 0), I'm not sure which.
I know how to get the program to add up the sums of the multiple for each of 3, 5 and 7, but I'm not sure how I'd get the program to only use each number once. For example, I can get the program to find out all of the numbers and add them up for 3 and then do the same for 5, but then the number 15 would be in the final number twice. I'm not sure exactly how I'd get it to only take the number once. Thanks for any help.
While the generate-and-test approach is simple to understand, it is also not very efficient if you want to run this on larger numbers. Instead, we can use the inclusion-exclusion principle.
The idea is to first sum up too many numbers by looking at the multiples of 3, 5 and 7 separately. Then we subtract the ones we counted twice, i.e. multiples of 3*5, 3*7 and 5*7. But now we subtracted too much and need to add back the multiples of 3*5*7 again.
We start by finding the sum of all integers 1..n which are multiples of k. First, we find out how many there are, m = n / k, rounded down thanks to integer division. Now we just need to sum up the sequence k + 2*k + 3*k + ... + m*k. We factor out the k and get k * (1 + 2 + ... + m).
This is a well-known arithmetic series, which we know sums to k * m * (m + 1)/2 (See triangle number).
private long n = 9999;
private long multiples(long k) {
long m = n / k;
return k * m * (m + 1) / 2:
}
Now we just use inclusion-exclusion to get the final sum:
long sum = multiples(3) + multiples(5) + multiples(7)
- multiples(3*5) - multiples(3*7) - multiples(5*7)
+ multiples(3*5*7);
This will scale much better to larger n than just looping over all the values, but beware of overflow and change to BigIntegers if necessary.
The easiest approach would be to use a for loop thus:
int sum = 0;
for(int i=1; i<10000; i++)
{
if (i % 3 == 0 || i % 5 == 0 || i % 7 == 0)
sum += i;
}
Use a Set to store the unique multiples, and then sum the values of the Set.
I would use a Set. This way you are guaranteed that you won't get any duplicates if they are your main problem.
One simple solution would be to add each number thats a multiple of 3,5, or 7 to an Answer list. And then as you work thru each number, make sure that its not already in the answer list.
(pseudo-code)
List<int> AnswerList;
List<int> MultiplesOfFive;
List<int> MultiplesOfSeven;
List<int> MultiplesOfThree;
for (int i = 0 ; i < 10000; i++)
{
if ( i % 3 == 0 && AnswserList.Contains(i) == false)
{
MultiplesOfThree.Add(i);
AnswerList.Add(i);
}
if ( i % 5 == 0 && AnswserList.Contains(i) == false)
{
MultiplesOfFive.Add(i);
AnswerList.Add(i);
}
if ( i % 7 == 0 && AnswserList.Contains(i) == false)
{
MultiplesOfSeven.Add(i);
AnswerList.Add(i);
}
}
for the solution that loops 1 to 1000 use i<=10000 otherwise it'll skip 10000 itself which is a multiple of 5. Apologies, for some reason i can't post this as a comment