In one of my java programs I am trying to read a number and then use the golden ratio (1.618034) to find the next smallest fibonacci number its index. For example, if I enter 100000 I should get back "the smallest fibonacci number which is greater than 100000 is the 26th and its value is 121393".
The program should also calculate a fibonacci number by index (case 1 in the code below) which I have coded so far, but I can't figure out how to solve the problem described above (case 2). I have a horrible teacher and I don't really understand what I need to do. I am not asking for the code, just kind of a step by step what I should do for case 2. I can not use recursion. Thank you for any help. I seriously suck at wrapping my head around this.
import java.util.Scanner;
public class Fibonacci {
public static void main(String args[]) {
Scanner scan = new Scanner(System.in);
System.out.println("This is a Fibonacci sequence generator");
System.out.println("Choose what you would like to do");
System.out.println("1. Find the nth Fibonacci number");
System.out.println("2. Find the smallest Fibonacci number that exceeds user given value");
System.out.println("3. Find the two Fibonacci numbers whose ratio is close enough to the golden number");
System.out.print("Enter your choice: ");
int choice = scan.nextInt();
int xPre = 0;
int xCurr = 1;
int xNew = 0;
switch (choice)
{
case 1:
System.out.print("Enter the target index to generate (>1): ");
int index = scan.nextInt();
for (int i = 2; i <= index; i++)
{
xNew = xPre + xCurr;
xPre = xCurr;
xCurr = xNew;
}
System.out.println("The " + index + "th number Fibonacci number is " + xNew);
break;
case 2:
System.out.print("Enter the target value (>1): ");
int value = scan.nextInt();
}
}
}
First, you should understand what this golden ration story is all about. The point is, Fibonacci numbers can be calced recursively, but there's also a formula for the nth Fibonacci number:
φ(n) = [φ^n - (-φ)^(-n)]/√5
where φ = (√5 + 1)/2 is the Golden Ratio (approximately 1.61803). Now, |(-φ)^(-1)| < 1 which means that you can calc φ(n) as the closest integer to φ^n/√5 (unless n = 1).
So, calc √5, calc φ, then learn how to get an integer closest to the value of a real variable and then calc φ(n) using the φ^n/√5 formula (or just use the "main" [φ^n - (-φ)^(-n)]/√5 formula) in a loop and in that loop compare φ(n) with the number that user input. When φ(n) exceeds the user's number, remember n and φ(n).
Related
So the Fibonacci number for log (N) — without matrices.
Ni // i-th Fibonacci number
= Ni-1 + Ni-2 // by definition
= (Ni-2 + Ni-3) + Ni-2 // unwrap Ni-1
= 2*Ni-2 + Ni-3 // reduce the equation
= 2*(Ni-3 + Ni-4) + Ni-3 //unwrap Ni-2
// And so on
= 3*Ni-3 + 2*Ni-4
= 5*Ni-4 + 3*Ni-5
= 8*Ni-5 + 5*Ni-6
= Nk*Ni-k + Nk-1*Ni-k-1
Now we write a recursive function, where at each step we take k~=I/2.
static long N(long i)
{
if (i < 2) return 1;
long k=i/2;
return N(k) * N(i - k) + N(k - 1) * N(i - k - 1);
}
Where is the fault?
You get a recursion formula for the effort: T(n) = 4T(n/2) + O(1). (disregarding the fact that the numbers get bigger, so the O(1) does not even hold). It's clear from this that T(n) is not in O(log(n)). Instead one gets by the master theorem T(n) is in O(n^2).
Btw, this is even slower than the trivial algorithm to calculate all Fibonacci numbers up to n.
The four N calls inside the function each have an argument of around i/2. So the length of the stack of N calls in total is roughly equal to log2N, but because each call generates four more, the bottom 'layer' of calls has 4^log2N = O(n2) Thus, the fault is that N calls itself four times. With only two calls, as in the conventional iterative method, it would be O(n). I don't know of any way to do this with only one call, which could be O(log n).
An O(n) version based on this formula would be:
static long N(long i) {
if (i<2) {
return 1;
}
long k = i/2;
long val1;
long val2;
val1 = N(k-1);
val2 = N(k);
if (i%2==0) {
return val2*val2+val1*val1;
}
return val2*(val2+val1)+val1*val2;
}
which makes 2 N calls per function, making it O(n).
public class fibonacci {
public static int count=0;
public static void main(String[] args) {
Scanner scan = new Scanner(System.in);
int i = scan.nextInt();
System.out.println("value of i ="+ i);
int result = fun(i);
System.out.println("final result is " +result);
}
public static int fun(int i) {
count++;
System.out.println("fun is called and count is "+count);
if(i < 2) {
System.out.println("function returned");
return 1;
}
int k = i/2;
int part1 = fun(k);
int part2 = fun(i-k);
int part3 = fun(k-1);
int part4 = fun(i-k-1);
return ((part1*part2) + (part3*part4)); /*RESULT WILL BE SAME FOR BOTH METHODS*/
//return ((fun(k)*fun(i-k))+(fun(k-1)*fun(i-k-1)));
}
}
I tried to code to problem defined by you in java. What i observed is that complexity of above code is not completely O(N^2) but less than that.But as per conventions and standards the worst case complexity is O(N^2) including some other factors like computation(division,multiplication) and comparison time analysis.
The output of above code gives me information about how many times the function
fun(int i) computes and is being called.
OUTPUT
So including the time taken for comparison and division, multiplication operations, the worst case time complexity is O(N^2) not O(LogN).
Ok if we use Analysis of the recursive Fibonacci program technique.Then we end up getting a simple equation
T(N) = 4* T(N/2) + O(1)
where O(1) is some constant time.
So let's apply Master's method on this equation.
According to Master's method
T(n) = aT(n/b) + f(n) where a >= 1 and b > 1
There are following three cases:
If f(n) = Θ(nc) where c < Logba then T(n) = Θ(nLogba)
If f(n) = Θ(nc) where c = Logba then T(n) = Θ(ncLog n)
If f(n) = Θ(nc) where c > Logba then T(n) = Θ(f(n))
And in our equation a=4 , b=2 & c=0.
As case 1 c < logba => 0 < 2 (which is log base 2 and equals to 2) is satisfied
hence T(n) = O(n^2).
For more information about how master's algorithm works please visit: Analysis of Algorithms
Your idea is correct, and it will perform in O(log n) provided you don't compute the same formula
over and over again. The whole point of having N(k) * N(i-k) is to have (k = i - k) so you only have to compute one instead of two. But if you only call recursively, you are performing the computation twice.
What you need is called memoization. That is, store every value that you already have computed, and
if it comes up again, then you get it in O(1).
Here's an example
const int MAX = 10000;
// memoization array
int f[MAX] = {0};
// Return nth fibonacci number using memoization
int fib(int n) {
// Base case
if (n == 0)
return 0;
if (n == 1 || n == 2)
return (f[n] = 1);
// If fib(n) is already computed
if (f[n]) return f[n];
// (n & 1) is 1 iff n is odd
int k = n/2;
// Applying your formula
f[n] = fib(k) * fib(n - k) + fib(k - 1) * fib(n - k - 1);
return f[n];
}
I was solving this codechef problem on Fibonacci numbers. It says number is of 1000 digits then why it is not causing integer overflow in tester's solution when it is scanning the array and storing it in unsigned long long int. I can't understand how solution is working. Below is the problem and tester's solution.
The Head Chef has been playing with Fibonacci numbers for long . He has learnt several tricks related to Fibonacci numbers . Now he wants to test his chefs in the skills .
A fibonacci number is defined by the recurrence :
f(n) = f(n-1) + f(n-2) for n > 2
and f(1) = 0
and f(2) = 1 .
Given a number A , determine if it is a fibonacci number.
Input
The first line of the input contains an integer T denoting the number of test cases. The description of T test cases follows.
The only line of each test case contains a single integer A denoting the number to be checked .
Output
For each test case, output a single line containing "YES" if the given number is a fibonacci number , otherwise output a single line containing "NO" .
Constraints
1 ≤ T ≤ 1000
1 ≤ number of digits in A ≤ 1000
The sum of number of digits in A in all test cases <= 10000.
Example
Input:
3
3
4
5
Output:
YES
NO
YES
**Tester's solution:**
#include <iostream>
#include <cstdio>
#include <algorithm>
#include <set>
#include <cstring>
using namespace std;
int const mx = 6666;
set <unsigned long long> f;
unsigned long long fib[mx + 10];
char s[mx + 1];
int main(){
// freopen("input.txt", "r", stdin);
// freopen("output.txt", "w", stdout);
fib[0] = 0;
fib[1] = 1;
f.insert(1);
f.insert(0);
int i;
for (i = 2; i <= mx; i++){
fib[i] = fib[i - 1] + fib[i - 2];
f.insert(fib[i]);
}
int tc;
cin>>tc;
while (tc--){
unsigned long long n = 0, ten = 10;
cin>>s;
int len = strlen(s);
for (i = 0; i < len; i++){
char q = s[i];
unsigned long long a = q - '0';
n = n * ten + a;
}
if (f.find(n) == f.end()) printf("NO\n");
else printf("YES\n");
}
return 0;
}
From cplusplus you will see that,
ULLONG_MAX Maximum value for an object of type unsigned long long int is 18446744073709551615 (264-1) or greater.
The actual value depends on the particular system and library implementation, but shall reflect the limits of these types in
the target platform.
Above information is just to let you know its a BIG number. Moreover the cause of not getting overflow is not the limit i mentioned.
Most probably, the input file of judge does not contain any input that can cause an overflow.
And its still possible to set such input even after fulfilling the conditions,
1 ≤ T ≤ 1000
1 ≤ number of digits in A ≤ 1000
The sum of number of digits in A in all test cases <= 10000.
I need to round a number, let's say 543 to either the hundreds or the tens place. It could be either one, as it's part of a game and this stage can ask you to do one or the other.
So for example, it could ask, "Round number to nearest tens", and if the number was 543, they would have to enter in 540.
However, I don't see a function that you can specify target place value to round at. I know there's an easy solution, I just can't think of one right now.
From what I see, the round function rounds the last decimal place?
Thanks
To rounding to 100's place
NSInteger num=543;
NSInteger deci=num%100;//43
if(deci>49){
num=num-deci+100;//543-43+100 =600
}
else{
num=num-deci;//543-43=500
}
To round to 10's place
NSInteger num=543;
NSInteger deci=num%10;//3
if(deci>4){
num=num-deci+100;//543-3+10 =550
}
else{
num=num-deci;//543-3=540
}
EDIT:
Tried to merge the above in one:
NSInteger num=543;
NSInteger place=100; //rounding factor, 10 or 100 or even more.
NSInteger condition=place/2;
NSInteger deci=num%place;//43
if(deci>=condition){
num=num-deci+place;//543-43+100 =600.
}
else{
num=num-deci;//543-43=500
}
You may just use an algorithm in your code:
For example, lets say that you need to round up a number to hundred's place.
int c = 543
int k = c % 100
if k > 50
c = (c - k) + 100
else
c = c - k
To round numbers, you can use the modulus operator, %.
The modulus operator gives you the remainder after division.
So 543 % 10 = 3, and 543 % 100 = 43.
Example:
int place = 10;
int numToRound=543;
// Remainder is 3
int remainder = numToRound%place;
if(remainder>(place/2)) {
// Called if remainder is greater than 5. In this case, it is 3, so this line won't be called.
// Subtract the remainder, and round up by 10.
numToRound=(numToRound-remainder)+place;
}
else {
// Called if remainder is less than 5. In this case, 3 < 5, so it will be called.
// Subtract the remainder, leaving 540
numToRound=(numToRound-remainder);
}
// numToRound will output as 540
NSLog(#"%i", numToRound);
Edit: My original answer was submitted before it was ready, because I accidentally hit a key to submit it. Oops.
Can I set a range of numbers when using arc4random()? For example 50-100 only.
As pointed out in other posts below, it is better to use arc4random_uniform. (When this answer was originally written, arc4random_uniform was not available). Besides avoiding the modulo bias of arc4random() % x, it also avoids a seeding problem with arc4random when used recursively in short timeframes.
arc4random_uniform(4)
will generate 0, 1, 2 or 3. Thus you could use:
arc4random_uniform(51)
and merely add 50 to the result to get a range between 50 & 100 (inclusive).
To expand upon JohnK comment.
It is suggested that you use the following function to return a ranged random number:
arc4random_uniform(51)
which will return a random number in the range 0 to 50.
Then you can add your lower bounds to this like:
arc4random_uniform(51) + 50
which will return a random number in the range 50 to 100.
The reason we use arc4random_uniform(51) over arc4random() % 51 is to avoid the modulo bias. This is highlighted in the man page as follows:
arc4random_uniform(upper_bound) will return a uniformly distributed random number less than upper_bound. arc4random_uniform() is recommended over constructions like ``arc4random() % upper_bound'' as it avoids "modulo bias" when the upper bound is not a power of two.
In short you get a more evenly distributed random number generated.
int fromNumber = 10;
int toNumber = 30;
int randomNumber = (arc4random()%(toNumber-fromNumber))+fromNumber;
Will generate randon number between 10 and 30, i.e. 11,12,13,14......29
You can use this code for generating random values with range:
//range from 50 to 100
int num1 = (arc4random() % 50) + 50; or
int num1 = arc4random_uniform(50) + 50;
//range from 0-100
int num1 = arc4random() % 100; or
int num1 = arc4random_uniform(100);
In Swift you can use this (inspired by answer of #Justyn)
func generateRandomKey(fromRange rangeFrom:Int, toRange rangeTo:Int) -> Int{
let theKey = arc4random_uniform(UInt32(rangeTo - rangeFrom)) + UInt32(rangeFrom)
return Int(theKey)
}
Will always give you a random range Integer.
In many situations 10 thru 30 would mean inclusive, (includes 10 and 30) ...
int fromNumber = 10;
int toNumber = 30;
toNumber ++;
int randomNumber = (arc4random()%(toNumber-fromNumber))+fromNumber;
Notice the difference toNumber - fromNumber is now 21 ... (20+1) which yields the possible results of 0 thru 20 (inclusive) which when added to fromNumber (10) results in 10 thru 30 (inclusive).
If I am given a floating point number but do not know beforehand what range the number will be in, is it possible to scale that number in some meaningful way to be in another range? I am thinking of checking to see if the number is in the range 0<=x<=1 and if not scale it to that range and then scale it to my final range. This previous post provides some good information, but it assumes the range of the original number is known beforehand.
You can't scale a number in a range if you don't know the range.
Maybe what you're looking for is the modulo operator. Modulo is basically the remainder of division, the operator in most languages is is %.
0 % 5 == 0
1 % 5 == 1
2 % 5 == 2
3 % 5 == 3
4 % 5 == 4
5 % 5 == 0
6 % 5 == 1
7 % 5 == 2
...
Sure it is not possible. You can define range and ignore all extrinsic values. Or, you can collect statistics to find range in run time (i.e. via histogram analysis).
Is it really about image processing? There are lots of related problems in image segmentation field.
You want to scale a single random floating point number to be between 0 and 1, but you don't know the range of the number?
What should 99.001 be scaled to? If the range of the random number was [99, 100], then our scaled-number should be pretty close to 0. If the range of the random number was [0, 100], then our scaled-number should be pretty close to 1.
In the real world, you always have some sort of information about the range (either the range itself, or how wide it is). Without further info, the answer is "No, it can't be done."
I think the best you can do is something like this:
int scale(x) {
if (x < -1) return 1 / x - 2;
if (x > 1) return 2 - 1 / x;
return x;
}
This function is monotonic, and has a range of -2 to 2, but it's not strictly a scaling.
I am assuming that you have the result of some 2-dimensional measurements and want to display them in color or grayscale. For that, I would first want to find the maximum and minimum and then scale between these two values.
static double[][] scale(double[][] in, double outMin, double outMax) {
double inMin = Double.POSITIVE_INFINITY;
double inMax = Double.NEGATIVE_INFINITY;
for (double[] inRow : in) {
for (double d : inRow) {
if (d < inMin)
inMin = d;
if (d > inMax)
inMax = d;
}
}
double inRange = inMax - inMin;
double outRange = outMax - outMin;
double[][] out = new double[in.length][in[0].length];
for (double[] inRow : in) {
double[] outRow = new double[inRow.length];
for (int j = 0; j < inRow.length; j++) {
double normalized = (inRow[j] - inMin) / inRange; // 0 .. 1
outRow[j] = outMin + normalized * outRange;
}
}
return out;
}
This code is untested and just shows the general idea. It further assumes that all your input data is in a "reasonable" range, away from infinity and NaN.