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Java double to int convertion changes sign of result

I tried to calculate a series of the N first fibonacci numbers using Binets Formula.
Every result i get is correct until F47 where the result is NEGATIVE.
This is my result : -1323752223
And heres the expected result : 2971215073
I really think the problem occures during the double to int conversion
Source Code:
import java.lang.Math;
class fibonacci{
public static int NthFibonacci(int n){
double fi = 1.61803398875;
int fb = (int)Math.round((Math.pow(fi,n) - Math.pow(1-fi,n))/Math.sqrt(5));
return fb;
}
public static void FibonacciSeries(Integer n){
for(int i = 0; i < n; i++){
System.out.println(NthFibonacci(i) + " ");
}
}
public static void main(String[] args) {
FibonacciSeries(50);
}
}

The real explanation for the behavior of the version in your question giving a negative number is a bit subtle.
At F47, this expression
(Math.pow(fi, n) - Math.pow(1 - fi, n)) / Math.sqrt(5)
will give you 2.971215073009069E9 ... which is close to the desired 2971215073.
The problem arises when you call Math.round(2.971215073009069E9). This returns a long - 2971215073L. But then you cast the result of the round call to an int, and it all goes pear-shaped.
Casting a long to an int will just lop off the top 32 bits ... and that results in a meaningless number.
If we modify fibonacci to return a long instead of an int, we get correct results up to F55. F56 and F57 are off by 1. F58 is off by 2.
What is happening now is that we are running into the problem that double (64-bit IEEE floating point) has only about 13.5 decimal digits of precision. The rounding error incurred in the computation of the intermediate floating point value for F56 larger that 0.5 ... so the rounded value is then incorrect.
The computed fibonacci numbers continue to get increasingly inaccurate until you get to F93, where the (modified) fibonacci method returns Long.MAX_VALUE.
To get correct values for very large Fibonacci numbers:
we need to use BigInteger to represent the numbers,
we need to do the computations using BigDecimal with sufficient precision, and (maybe)
we need to use a more accurate value for phi.
Or we need to use the recurrence relationship to compute the numbers.
The 2 take-aways from all of this are:
casting a long to an int is a lossy conversion, and
floating point arithmetic is inexact and ... tricky.

I think that the problem does not have something to do with the double conversion.
int can store numbers that can be represented by 32 bits. This means the highest number integer can represents is 2.147.483.647.
The F47 is breaking this limit and results in an bit-overflow, so it starts at -2.147.483.68 and adds the rest of your 2971215073 - 2147483647 to it. -1323752223 is the outcome.
Use a long (64bit) instead of an int and you should be good :)

2971215073 is too big to be represented as an int at all. The maximum value of an int -- Integer.MAX_VALUE -- is 2^31 - 1, or 2147483647.

Ok so i found a decent fix.
I used a Geometrical version of Binets rule which you can find here : Binets Geometrical Rule
I also used long instead of int so now I can accurately calculate up to F70. F71 is wrong by a digit and after that it just builds up.
New Source Code :
import java.lang.Math;
class fibonacci{
public static long NthFibonacci(int n){
double a = (1/Math.sqrt(5))*Math.pow(2, n);
double radians1 = Math.toRadians(36.0);
double radians2 = Math.toRadians(108.0);
double b = Math.pow(Math.cos(radians1), n) - Math.pow(Math.cos(radians2), n);
long fb = (long) Math.round(a*b);
return fb;
}
public static void FibonacciSeries(int n){
for(int i = 0; i < n; i++){
System.out.println( i + " : " + NthFibonacci(i));
}
}
public static void main(String[] args) {
FibonacciSeries(100);
}
}

LeetCode 231: Problem in finding whether a given number is Power of 2

I want to find whether a given number is a power of two in a mathematical way, not with a bitwise approach. Here is my code:
private static double logBaseTwo(final double x) {
return Math.log(x) / Math.log(2);
}
private static double roundToNearestHundredThousandth(final double x) {
return Math.round(x * 100000.0) / 100000.0;
}
private static boolean isInteger(final double x) {
return (int)(Math.ceil(x)) == (int)(Math.floor(x));
}
public static boolean isPowerOfTwo(final int n) {
return isInteger(roundToNearestHundredThousandth(logBaseTwo(n)));
}
It incorrectly returns true for certain numbers, such as 524287. Why is that?

Your code fails because you may need more precision than you allow to capture the difference between the logs of BIG_NUMBER and BIG_NUMBER+1
The bitwise way is really best, but if you really want to use only "mathy" operations, then the best you can do is probably:
public static boolean isPowerOfTwo(final int n) {
int exp = (int)Math.round(logBaseTwo(n));
int test = (int)Math.round(Math.pow(2.0,exp));
return test == n;
}
This solution does not require any super-fine precision, and will work fine for all positive ints.

This is truly horrifyingly bad code, and I have no idea what you are trying to do. You seem to be trying to check if the log base 2 of n is an integer. Instead I would write a loop:
while (n>1) {
m = (n/2) * 2
if (n!=m){
return false;
}
n /=2;
}
return true;

The solution seems more complicated than it should be. I don't get the 100000d parts - seems to potentially cause problems when converting to ceiling.
This is the simple solution that works for all cases:
public static boolean isPowerOfTwo(int n) {
return Math.ceil(Math.log(n)/Math.log(2)) == Math.floor(Math.log(n)/Math.log(2));
}

Originally I had a problem using Math.log in my computations. I switched to Math.log10 and the problem went away. Although mathematically, any logB of base B should work, the nature of floating point math can be unpredictable.
Try this.
public static boolean isPowerOfTwo(int n) {
return n > 0 && Integer.highestOneBit(n) == Integer.lowestOneBit(n);
}
If you prefer to use logs you can do it this way.
public static boolean isPowerOfTwo(int n) {
return n > 0 && (Math.log10(n)/Math.log10(2))%1 == 0;
}

doubles and floats have, respectively, 64-bit and 32-bit precision. That means they can hold at the very most 18446744073709551616 unique numbers. That's a lot of numbers, but not an infinite amount of them. At some point (in fact, that point occurs about at 2^52), the 'gap' between any 2 numbers which are part of the 18446744073709551616 representable ones becomes larger than 1.000. Similar rules apply to small numbers. Math.log does double based math.
Secondarily, ints are similarly limited. They can hold up to 4294967296 different numbers. For ints it's much simpler: Ints can hold from -2147483648 up to 2147483647. If you try to add 1 to 2147483647, you get -2147483648 (it silently wraps around). It's quite possible you're running into that with trying to convert such a large number (your double times 10000d) to an int first.
Note that ? true : false (as in the original version of the question) is literally completely useless. the thing to the left of the question mark must be a boolean, and booleans are already true or false, that's their nature.
See the other answers for simpler approaches to this problem. Although, of course, the simplest solution is to simply count bits in the number. If it's precisely 1 bit, it's a power of 2. If it's 0 bits, well, you tell me if you consider '0' a power of 2 :)

Why does my recursion program print a negative number?

My code for whatever reason is printing out a negative number when i run it with certain numbers(17). It is supposed to find the factorial of a number and print it out however clearly that isn't happening.
package recursion;
public class recursion_1 {
public static void main(String[] args) {
int x = factorial(17);
System.out.println(x);
}
public static int factorial(int N) {
if (N == 1) return 1;
return N * factorial(N-1);
}
}

You're encountering integer overflow.
factorial(17) is 3.5568743e+14, which is well beyond the bounds of int. When an integer operation overflows, it can end up negative. For example:
int x = Integer.MAX_VALUE;
x++;
System.out.println(x); // Very large negative number
In your case, you'll have overflowed several times - even if the result were positive, it still wouldn't be right.
If you need integers in the range of [-263, 263-1] you can use long instead of int. If you want arbitrarily large integers, use BigInteger instead. For example:
// Note rename of parameter to follow Java conventions
public static BigInteger factorial(int n) {
return factorial(BigInteger.valueOf(n));
}
public static BigInteger factorial(BigInteger n) {
if (n.equals(BigInteger.ONE)) {
return BigInteger.ONE;
}
return n.multiply(n.subtract(BigInteger.ONE));
}

Factorials grow quickly in value, such that 17! (355687428096000) too large to fit in an int, causing overflow and the negative number.
Return a long from factorial, so that when the multiplication occurs, it won't overflow (yet). You'll need to declare x as a long also. Note that this will only postpone the problem, because sufficiently high values of N will overflow a long too. If necessary, use BigIntegers.

This is because the maximum value an int can have is 2,147,483,647. 17! exceeds this number. If an integer is assigned a number bigger than its maximum size, it starts counting up from -2,147,483,647.
2,147,483,647 + 1 = -12,147,483,647
Try a long or BigDecimal instead =)

Recursive function to calculate combination and factorial

I am using the following two functions to calculate factorials and combinations.
public static long Factorial(long n)
{
if (n == 0)
return 1;
else
return n * Factorial(n-1);
}
public static long combinations (long n, long k)
{
return Factorial(n)/(Factorial(k) * Factorial(n - k));
}
I am testing it using:
long test = combinations((long)21, (long)13);
It seems to work for small numbers such as 5,2. But if I try 21,13, I get incorrect answers (negatives or 0).
Would anyone know what is happening here?

The maximum value of long in java is 2^63.
That will safely take you up to the factorial of 20. However, factorial of 21 comes to around 2^65, so you are exceeding the maximum value that can be represented.
See this question for a discussion about what happens in java if you perform a multiplication that results in an overflow.

This is mainly because of overflow from long (64bit signed). You can look up BigDecimal or BigInteger for use in this case.

As other users have said long can't hold Factorial(21). I rewrote your Factorial method using BigInteger and it seems to work, although you have to pass a BigInteger in as the parameter.
public static BigInteger Factorial(BigInteger n)
{
if (n.equals(BigInteger.ZERO))
return BigInteger.ONE;
else
return n.multiply(Factorial(n.subtract(BigInteger.ONE)));
}
Then rewrite your combinations method using BigInteger:
public static BigInteger combinations (BigInteger n, BigInteger k)
{
return Factorial(n).divide(Factorial(k).multiply(Factorial(n.subtract(k))));
}
In the main method I called the combinations method like this
System.out.print(combinations(new BigInteger("21"), new BigInteger("13")));

Dealing with overflow in Java without using BigInteger

Suppose I have a method to calculate combinations of r items from n items:
public static long combi(int n, int r) {
if ( r == n) return 1;
long numr = 1;
for(int i=n; i > (n-r); i--) {
numr *=i;
}
return numr/fact(r);
}
public static long fact(int n) {
long rs = 1;
if(n <2) return 1;
for (int i=2; i<=n; i++) {
rs *=i;
}
return rs;
}
As you can see it involves factorial which can easily overflow the result. For example if I have fact(200) for the foctorial method I get zero. The question is why do I get zero?
Secondly how do I deal with overflow in above context? The method should return largest possible number to fit in long if the result is too big instead of returning wrong answer.
One approach (but this could be wrong) is that if the result exceed some large number for example 1,400,000,000 then return remainder of result modulo
1,400,000,001. Can you explain what this means and how can I do that in Java?
Note that I do not guarantee that above methods are accurate for calculating factorial and combinations. Extra bonus if you can find errors and correct them.
Note that I can only use int or long and if it is unavoidable, can also use double. Other data types are not allowed.
I am not sure who marked this question as homework. This is NOT homework. I wish it was homework and i was back to future, young student at university. But I am old with more than 10 years working as programmer. I just want to practice developing highly optimized solutions in Java. In our times at university, Internet did not even exist. Today's students are lucky that they can even post their homework on site like SO.

Use the multiplicative formula, instead of the factorial formula.

Since its homework, I won't want to just give you a solution. However a hint I will give is that instead of calculating two large numbers and dividing the result, try calculating both together. e.g. calculate the numerator until its about to over flow, then calculate the denominator. In this last step you can chose the divide the numerator instead of multiplying the denominator. This stops both values from getting really large when the ratio of the two is relatively small.
I got this result before an overflow was detected.
combi(61,30) = 232714176627630544 which is 2.52% of Long.MAX_VALUE
The only "bug" I found in your code is not having any overflow detection, since you know its likely to be a problem. ;)

To answer your first question (why did you get zero), the values of fact() as computed by modular arithmetic were such that you hit a result with all 64 bits zero! Change your fact code to this:
public static long fact(int n) {
long rs = 1;
if( n <2) return 1;
for (int i=2; i<=n; i++) {
rs *=i;
System.out.println(rs);
}
return rs;
}
Take a look at the outputs! They are very interesting.
Now onto the second question....
It looks like you want to give exact integer (er, long) answers for values of n and r that fit, and throw an exception if they do not. This is a fair exercise.
To do this properly you should not use factorial at all. The trick is to recognize that C(n,r) can be computed incrementally by adding terms. This can be done using recursion with memoization, or by the multiplicative formula mentioned by Stefan Kendall.
As you accumulate the results into a long variable that you will use for your answer, check the value after each addition to see if it goes negative. When it does, throw an exception. If it stays positive, you can safely return your accumulated result as your answer.
To see why this works consider Pascal's triangle
1
1 1
1 2 1
1 3 3 1
1 4 6 4 1
1 5 10 10 5 1
1 6 15 20 15 6 1
which is generated like so:
C(0,0) = 1 (base case)
C(1,0) = 1 (base case)
C(1,1) = 1 (base case)
C(2,0) = 1 (base case)
C(2,1) = C(1,0) + C(1,1) = 2
C(2,2) = 1 (base case)
C(3,0) = 1 (base case)
C(3,1) = C(2,0) + C(2,1) = 3
C(3,2) = C(2,1) + C(2,2) = 3
...
When computing the value of C(n,r) using memoization, store the results of recursive invocations as you encounter them in a suitable structure such as an array or hashmap. Each value is the sum of two smaller numbers. The numbers start small and are always positive. Whenever you compute a new value (let's call it a subterm) you are adding smaller positive numbers. Recall from your computer organization class that whenever you add two modular positive numbers, there is an overflow if and only if the sum is negative. It only takes one overflow in the whole process for you to know that the C(n,r) you are looking for is too large.
This line of argument could be turned into a nice inductive proof, but that might be for another assignment, and perhaps another StackExchange site.
ADDENDUM
Here is a complete application you can run. (I haven't figured out how to get Java to run on codepad and ideone).
/**
* A demo showing how to do combinations using recursion and memoization, while detecting
* results that cannot fit in 64 bits.
*/
public class CombinationExample {
/**
* Returns the number of combinatios of r things out of n total.
*/
public static long combi(int n, int r) {
long[][] cache = new long[n + 1][n + 1];
if (n < 0 || r > n) {
throw new IllegalArgumentException("Nonsense args");
}
return c(n, r, cache);
}
/**
* Recursive helper for combi.
*/
private static long c(int n, int r, long[][] cache) {
if (r == 0 || r == n) {
return cache[n][r] = 1;
} else if (cache[n][r] != 0) {
return cache[n][r];
} else {
cache[n][r] = c(n-1, r-1, cache) + c(n-1, r, cache);
if (cache[n][r] < 0) {
throw new RuntimeException("Woops too big");
}
return cache[n][r];
}
}
/**
* Prints out a few example invocations.
*/
public static void main(String[] args) {
String[] data = ("0,0,3,1,4,4,5,2,10,0,10,10,10,4,9,7,70,8,295,100," +
"34,88,-2,7,9,-1,90,0,90,1,90,2,90,3,90,8,90,24").split(",");
for (int i = 0; i < data.length; i += 2) {
int n = Integer.valueOf(data[i]);
int r = Integer.valueOf(data[i + 1]);
System.out.printf("C(%d,%d) = ", n, r);
try {
System.out.println(combi(n, r));
} catch (Exception e) {
System.out.println(e.getMessage());
}
}
}
}
Hope it is useful. It's just a quick hack so you might want to clean it up a little.... Also note that a good solution would use proper unit testing, although this code does give nice output.

You can use the java.math.BigInteger class to deal with arbitrarily large numbers.

If you make the return type double, it can handle up to fact(170), but you'll lose some precision because of the nature of double (I don't know why you'd need exact precision for such huge numbers).
For input over 170, the result is infinity

Note that java.lang.Long includes constants for the min and max values for a long.
When you add together two signed 2s-complement positive values of a given size, and the result overflows, the result will be negative. Bit-wise, it will be the same bits you would have gotten with a larger representation, only the high-order bit will be truncated away.
Multiplying is a bit more complicated, unfortunately, since you can overflow by more than one bit.
But you can multiply in parts. Basically you break the to multipliers into low and high halves (or more than that, if you already have an "overflowed" value), perform the four possible multiplications between the four halves, then recombine the results. (It's really just like doing decimal multiplication by hand, but each "digit" is, say, 32 bits.)

You can copy the code from java.math.BigInteger to deal with arbitrarily large numbers. Go ahead and plagiarize.