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How to get the correct output in Modulo (10^9 + 7) format?

I am working on this code challenge:
Problem Description
Given 2 integers x and n, you have to calculate x
to the power of n, modulo 10^9+7 i.e. calculate (x^n) % (10^9+7).
In other words, you have to find the value when x is raised to the
power of n, and then modulo is taken with 10^9+7.
a%b means the remainder when a divides b. For instance, 5%3 = 2, as
when we divide 5 by 3, 2 is the remainder.
Note that 10^9 is also represented as 1e9.
Input format
One line of input containing two space separated
integers, x and n.
Output format Print the required answer.
Sample Input 1 100000000 2
Sample Output 1 930000007
Explanation 1 (10^8)^2 = 10^16
10^16 % (10^9+7) = 930000007
Constraints 0 <= x < 10^9
0 <= n < 10^5
Code
The following is my code:
import java.util.*;
class ModularExponentiation {
// NOTE: Please do not modify this function
public static void main(String args[]) {
Scanner sc = new Scanner(System.in);
int x = sc.nextInt();
int n = sc.nextInt();
int ans = modularExponentiation(x, n);
System.out.println(ans);
}
// TODO: Implement this method
static int modularExponentiation(int x, int n) {
int M = 1000000007;
long a = (long) Math.pow(x, n);
long b = a%M;
return (int)b;
}
}
When I run my code, it succeeds for the sample test case and an edge case, but fails for 3 base cases. How do I make my code succeed all test cases?

Does this work?
public static int modularExponentiation(int x, int n) {
int modulo = 1000000007;
if (n == 0) {
return 1;
} else if (n == 1) {
return x % modulo;
} else if (n == -1) {
return 1 / x;
}
int p = modularExponentiation(x, n >> 1);
long product = ((long) p * p) % modulo;
return (int) (product * modularExponentiation(x, n & 1) % modulo);
}
Key points:
Math.pow(x,n) suffers from overflow and we can't compensate that overflow relying on result only, that is why initial idea of Math.pow(x,n) % modulo produces wrong results
We may notice that (x * x) % modulo == (x % modulo) * (x % modulo) % modulo, and it is safe to use long here as intermediate result because x % modulo < modulo and modulo * modulo < 2^63 - 1
We need to reconstruct the process, but naive approach that x^n is a product of n x's is too slow - it has O(N) time complexity, however we may notice that x^2k == (x^k)^2 and x^(2k+1) == x * (x^k)^2 - so we may use either recursion here or loop to achieve O(LogN) time complexity
alternative loop solution:
public static int modularExponentiation(int x, int n) {
int modulo = 1000000007;
long product = 1;
long p = x;
while (n != 0) {
if ((n & 1) == 1) {
product = product * p % modulo;
}
p = (p * p % modulo);
n >>= 1;
}
return (int) product;
}

If you have problem in C++ then , you can use
const unsigned int Mod=1e9+7;

Maximum height of the staircase

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;
}

Combinatory issue due to Factorial overflow

I need a function which can calculate the mathematical combination of (n, k) for a card game.
My current attempt is to use a function based on usual Factorial method :
static long Factorial(long n)
{
return n < 2 ? 1 : n * Factorial(n - 1);
}
static long Combinatory(long n , long k )
{
return Factorial(n) / (Factorial(k) * Factorial(n - k));
}
It's working very well but the matter is when I use some range of number (n value max is 52 and k value max is 4), it keeps me returning a wrong value. E.g :
long comb = Combinatory(52, 2) ; // return 1 which should be actually 1326
I know that it's because I overflow the long when I make Factorial(52) but the range result I need is not as big as it seems.
Is there any way to get over this issue ?

Instead of using the default combinatory formula n! / (k! x (n - k)!), use the recursive property of the combinatory function.
(n, k) = (n - 1, k) + (n - 1, k - 1)
Knowing that : (n, 0) = 1 and (n, n) = 1.
-> It will make you avoid using factorial and overflowing your long.
Here is sample of implementation you can do :
static long Combinatory(long n, long k)
{
if (k == 0 || n == k )
return 1;
return Combinatory(n - 1, k) + Combinatory(n - 1, k - 1);
}
EDIT : With a faster iterative algorithm
static long Combinatory(long n, long k)
{
if (n - k < k)
k = n - k;
long res = 1;
for (int i = 1; i <= k; ++i)
{
res = (res * (n - i + 1)) / i;
}
return res;
}

In C# you can use BigInteger (I think there's a Java equivalent).
e.g.:
static long Combinatory(long n, long k)
{
return (long)(Factorial(new BigInteger(n)) / (Factorial(new BigInteger(k)) * Factorial(new BigInteger(n - k))));
}
static BigInteger Factorial(BigInteger n)
{
return n < 2 ? 1 : n * Factorial(n - 1);
}
You need to add a reference to System.Numerics to use BigInteger.

If this is not for a homework assignment, there is an efficient implementation in Apache's commons-math package
http://commons.apache.org/proper/commons-math/apidocs/org/apache/commons/math3/util/ArithmeticUtils.html#binomialCoefficientDouble%28int,%20int%29
If it is for a homework assignment, start avoiding factorial in your implementation.
Use the property that (n, k) = (n, n-k) to rewrite your choose using the highest value for k.
Then note that you can reduce n!/k!(n-k)! to n * n-1 * n-2 .... * k / (n-k) * (n-k-1) ... * 1 means that you are multiplying every number from [k, n] inclusive, then dividing by every number [1,n-k] inclusive.
// From memory, please verify correctness independently before trusting its use.
//
public long choose(n, k) {
long kPrime = Math.max(k, n-k);
long returnValue = 1;
for(i = kPrime; i <= n; i++) {
returnValue *= i;
}
for(i = 2; i <= n - kPrime; i++) {
returnValue /= i;
}
return returnValue;
}
Please double check the maths, but this is a basic idea you could go down to get a reasonably efficient implementation that will work for numbers up to a poker deck.

The recursive formula is also known as Pascal's triangle, and IMO it's the easiest way to calculate combinatorials. If you're only going to need C(52,k) (for 0<=k<=52) I think it would be best to fill a table with them at program start. The following C code fills a table using this method:
static int64_t* pascals_triangle( int N)
{
int n,k;
int64_t* C = calloc( N+1, sizeof *C);
for( n=0; n<=N; ++n)
{ C[n] = 1;
for( k=n-1; k>0; --k)
{ C[k] += C[k-1];
}
}
return C;
}
After calling this with N=52, for example returns, C[k] will hold C(52,k) for k=0..52

Calculating powers of integers

Is there any other way in Java to calculate a power of an integer?
I use Math.pow(a, b) now, but it returns a double, and that is usually a lot of work, and looks less clean when you just want to use ints (a power will then also always result in an int).
Is there something as simple as a**b like in Python?

When it's power of 2. Take in mind, that you can use simple and fast shift expression 1 << exponent
example:
22 = 1 << 2 = (int) Math.pow(2, 2)
210 = 1 << 10 = (int) Math.pow(2, 10)
For larger exponents (over 31) use long instead
232 = 1L << 32 = (long) Math.pow(2, 32)
btw. in Kotlin you have shl instead of << so
(java) 1L << 32 = 1L shl 32 (kotlin)

Integers are only 32 bits. This means that its max value is 2^31 -1. As you see, for very small numbers, you quickly have a result which can't be represented by an integer anymore. That's why Math.pow uses double.
If you want arbitrary integer precision, use BigInteger.pow. But it's of course less efficient.

Best the algorithm is based on the recursive power definition of a^b.
long pow (long a, int b)
{
if ( b == 0) return 1;
if ( b == 1) return a;
if (isEven( b )) return pow ( a * a, b/2); //even a=(a^2)^b/2
else return a * pow ( a * a, b/2); //odd a=a*(a^2)^b/2
}
Running time of the operation is O(logb).
Reference:More information

No, there is not something as short as a**b
Here is a simple loop, if you want to avoid doubles:
long result = 1;
for (int i = 1; i <= b; i++) {
result *= a;
}
If you want to use pow and convert the result in to integer, cast the result as follows:
int result = (int)Math.pow(a, b);

Google Guava has math utilities for integers.
IntMath

import java.util.*;
public class Power {
public static void main(String args[])
{
Scanner sc=new Scanner(System.in);
int num = 0;
int pow = 0;
int power = 0;
System.out.print("Enter number: ");
num = sc.nextInt();
System.out.print("Enter power: ");
pow = sc.nextInt();
System.out.print(power(num,pow));
}
public static int power(int a, int b)
{
int power = 1;
for(int c = 0; c < b; c++)
power *= a;
return power;
}
}

Guava's math libraries offer two methods that are useful when calculating exact integer powers:
pow(int b, int k) calculates b to the kth the power, and wraps on overflow
checkedPow(int b, int k) is identical except that it throws ArithmeticException on overflow
Personally checkedPow() meets most of my needs for integer exponentiation and is cleaner and safter than using the double versions and rounding, etc. In almost all the places I want a power function, overflow is an error (or impossible, but I want to be told if the impossible ever becomes possible).
If you want get a long result, you can just use the corresponding LongMath methods and pass int arguments.

Well you can simply use Math.pow(a,b) as you have used earlier and just convert its value by using (int) before it. Below could be used as an example to it.
int x = (int) Math.pow(a,b);
where a and b could be double or int values as you want.
This will simply convert its output to an integer value as you required.

A simple (no checks for overflow or for validity of arguments) implementation for the repeated-squaring algorithm for computing the power:
/** Compute a**p, assume result fits in a 32-bit signed integer */
int pow(int a, int p)
{
int res = 1;
int i1 = 31 - Integer.numberOfLeadingZeros(p); // highest bit index
for (int i = i1; i >= 0; --i) {
res *= res;
if ((p & (1<<i)) > 0)
res *= a;
}
return res;
}
The time complexity is logarithmic to exponent p (i.e. linear to the number of bits required to represent p).

I managed to modify(boundaries, even check, negative nums check) Qx__ answer. Use at your own risk. 0^-1, 0^-2 etc.. returns 0.
private static int pow(int x, int n) {
if (n == 0)
return 1;
if (n == 1)
return x;
if (n < 0) { // always 1^xx = 1 && 2^-1 (=0.5 --> ~ 1 )
if (x == 1 || (x == 2 && n == -1))
return 1;
else
return 0;
}
if ((n & 1) == 0) { //is even
long num = pow(x * x, n / 2);
if (num > Integer.MAX_VALUE) //check bounds
return Integer.MAX_VALUE;
return (int) num;
} else {
long num = x * pow(x * x, n / 2);
if (num > Integer.MAX_VALUE) //check bounds
return Integer.MAX_VALUE;
return (int) num;
}
}

base is the number that you want to power up, n is the power, we return 1 if n is 0, and we return the base if the n is 1, if the conditions are not met, we use the formula base*(powerN(base,n-1)) eg: 2 raised to to using this formula is : 2(base)*2(powerN(base,n-1)).
public int power(int base, int n){
return n == 0 ? 1 : (n == 1 ? base : base*(power(base,n-1)));
}

There some issues with pow method:
We can replace (y & 1) == 0; with y % 2 == 0
bitwise operations always are faster.
Your code always decrements y and performs extra multiplication, including the cases when y is even. It's better to put this part into else clause.
public static long pow(long x, int y) {
long result = 1;
while (y > 0) {
if ((y & 1) == 0) {
x *= x;
y >>>= 1;
} else {
result *= x;
y--;
}
}
return result;
}

Use the below logic to calculate the n power of a.
Normally if we want to calculate n power of a. We will multiply 'a' by n number of times.Time complexity of this approach will be O(n)
Split the power n by 2, calculate Exponentattion = multiply 'a' till n/2 only. Double the value. Now the Time Complexity is reduced to O(n/2).
public int calculatePower1(int a, int b) {
if (b == 0) {
return 1;
}
int val = (b % 2 == 0) ? (b / 2) : (b - 1) / 2;
int temp = 1;
for (int i = 1; i <= val; i++) {
temp *= a;
}
if (b % 2 == 0) {
return temp * temp;
} else {
return a * temp * temp;
}
}

Apache has ArithmeticUtils.pow(int k, int e).

import java.util.Scanner;
class Solution {
public static void main(String[] args) {
Scanner sc = new Scanner(System.in);
int t = sc.nextInt();
for (int i = 0; i < t; i++) {
try {
long x = sc.nextLong();
System.out.println(x + " can be fitted in:");
if (x >= -128 && x <= 127) {
System.out.println("* byte");
}
if (x >= -32768 && x <= 32767) {
//Complete the code
System.out.println("* short");
System.out.println("* int");
System.out.println("* long");
} else if (x >= -Math.pow(2, 31) && x <= Math.pow(2, 31) - 1) {
System.out.println("* int");
System.out.println("* long");
} else {
System.out.println("* long");
}
} catch (Exception e) {
System.out.println(sc.next() + " can't be fitted anywhere.");
}
}
}
}

int arguments are acceptable when there is a double paramter. So Math.pow(a,b) will work for int arguments. It returns double you just need to cast to int.
int i = (int) Math.pow(3,10);

Without using pow function and +ve and -ve pow values.
public class PowFunction {
public static void main(String[] args) {
int x = 5;
int y = -3;
System.out.println( x + " raised to the power of " + y + " is " + Math.pow(x,y));
float temp =1;
if(y>0){
for(;y>0;y--){
temp = temp*x;
}
} else {
for(;y<0;y++){
temp = temp*x;
}
temp = 1/temp;
}
System.out.println("power value without using pow method. :: "+temp);
}
}

Unlike Python (where powers can be calculated by a**b) , JAVA has no such shortcut way of accomplishing the result of the power of two numbers.
Java has function named pow in the Math class, which returns a Double value
double pow(double base, double exponent)
But you can also calculate powers of integer using the same function. In the following program I did the same and finally I am converting the result into an integer (typecasting). Follow the example:
import java.util.*;
import java.lang.*; // CONTAINS THE Math library
public class Main{
public static void main(String[] args){
Scanner sc = new Scanner(System.in);
int n= sc.nextInt(); // Accept integer n
int m = sc.nextInt(); // Accept integer m
int ans = (int) Math.pow(n,m); // Calculates n ^ m
System.out.println(ans); // prints answers
}
}
Alternatively,
The java.math.BigInteger.pow(int exponent) returns a BigInteger whose value is (this^exponent). The exponent is an integer rather than a BigInteger. Example:
import java.math.*;
public class BigIntegerDemo {
public static void main(String[] args) {
BigInteger bi1, bi2; // create 2 BigInteger objects
int exponent = 2; // create and assign value to exponent
// assign value to bi1
bi1 = new BigInteger("6");
// perform pow operation on bi1 using exponent
bi2 = bi1.pow(exponent);
String str = "Result is " + bi1 + "^" +exponent+ " = " +bi2;
// print bi2 value
System.out.println( str );
}
}

Newton's method with specified digits of precision

I'm trying to write a function in Java that calculates the n-th root of a number. I'm using Newton's method for this. However, the user should be able to specify how many digits of precision they want. This is the part with which I'm having trouble, as my answer is often not entirely correct. The relevant code is here: http://pastebin.com/d3rdpLW8. How could I fix this code so that it always gives the answer to at least p digits of precision? (without doing more work than is necessary)
import java.util.Random;
public final class Compute {
private Compute() {
}
public static void main(String[] args) {
Random rand = new Random(1230);
for (int i = 0; i < 500000; i++) {
double k = rand.nextDouble()/100;
int n = (int)(rand.nextDouble() * 20) + 1;
int p = (int)(rand.nextDouble() * 10) + 1;
double math = n == 0 ? 1d : Math.pow(k, 1d / n);
double compute = Compute.root(n, k, p);
if(!String.format("%."+p+"f", math).equals(String.format("%."+p+"f", compute))) {
System.out.println(String.format("%."+p+"f", math));
System.out.println(String.format("%."+p+"f", compute));
System.out.println(math + " " + compute + " " + p);
}
}
}
/**
* Returns the n-th root of a positive double k, accurate to p decimal
* digits.
*
* #param n
* the degree of the root.
* #param k
* the number to be rooted.
* #param p
* the decimal digit precision.
* #return the n-th root of k
*/
public static double root(int n, double k, int p) {
double epsilon = pow(0.1, p+2);
double approx = estimate_root(n, k);
double approx_prev;
do {
approx_prev = approx;
// f(x) / f'(x) = (x^n - k) / (n * x^(n-1)) = (x - k/x^(n-1)) / n
approx -= (approx - k / pow(approx, n-1)) / n;
} while (abs(approx - approx_prev) > epsilon);
return approx;
}
private static double pow(double x, int y) {
if (y == 0)
return 1d;
if (y == 1)
return x;
double k = pow(x * x, y >> 1);
return (y & 1) == 0 ? k : k * x;
}
private static double abs(double x) {
return Double.longBitsToDouble((Double.doubleToLongBits(x) << 1) >>> 1);
}
private static double estimate_root(int n, double k) {
// Extract the exponent from k.
long exp = (Double.doubleToLongBits(k) & 0x7ff0000000000000L);
// Format the exponent properly.
int D = (int) ((exp >> 52) - 1023);
// Calculate and return 2^(D/n).
return Double.longBitsToDouble((D / n + 1023L) << 52);
}
}

Just iterate until the update is less than say, 0.0001, if you want a precision of 4 decimals.
That is, set your epsilon to Math.pow(10, -n) if you want n digits of precision.

Let's recall what the error analysis of Newton's method says. Basically, it gives us an error for the nth iteration as a function of the error of the n-1 th iteration.
So, how can we tell if the error is less than k? We can't, unless we know the error at e(0). And if we knew the error at e(0), we would just use that to find the correct answer.
What you can do is say "e(0) <= m". You can then find n such that e(n) <= k for your desired k. However, this requires knowing the maximal value of f'' in your radius, which is (in general) just as hard a problem as finding the x intercept.
What you're checking is if the error changes by less than k, which is a perfectly acceptable way to do it. But it's not checking if the error is less than k. As Axel and others have noted, there are many other root-approximation algorithms, some of which will yield easier error analysis, and if you really want this, you should use one of those.

You have a bug in your code. Your pow() method's last line should read
return (y & 1) == 1 ? k : k * x;
rather than
return (y & 1) == 0 ? k : k * x;