I have this problem for the course "Algorithm and data structures"
You have a equation x^2+s(x)+200·x=N, where x and N are natural numbers and S(x) is the sum of digits of number x.
On the input we have N and A, B such that A≤B and A, B≤1,000,000,000. You need to check if there is a natural number x in the interval [A, B] that solves the equation. If found you need to return that number, otherwise return -1.
Example Input:
1456
10 80
Output
-1
I managed to solve this problem by using some math and a bit modified version of brute force algorithm. But are there any more effective(algorithm based) ways to solve this problem?
This is my code:
import java.io.BufferedReader;
import java.io.InputStreamReader;
import java.util.StringTokenizer;
public class Range {
static int proveri(long N, long A, long B) {
long res = 0;
long start = (long)((-200 + Math.sqrt(4*N + 4))/2);
//System.out.println(start);
for (long i = Math.max(A, start); i <= B; i++) {
res = i * i + S(i) + 200 * i;
if(res == N)
return (int)i;
if(res > N)
return -1;
}
return -1;
}
static int S(long x) {
int sum = 0;
while(x > 0) {
sum += x % 10;
x /= 10;
}
return sum;
}
public static void main(String[] args) throws Exception {
int i,j,k;
BufferedReader br = new BufferedReader(new InputStreamReader(System.in));
long N = Long.parseLong(br.readLine());
StringTokenizer st = new StringTokenizer(br.readLine());
long A = Long.parseLong(st.nextToken());
long B = Long.parseLong(st.nextToken());
int res = proveri(N, A, B);
System.out.println(res);
br.close();
}
}
Here's a way where you can cut down on the amount of numbers you have to search.
Consider the equation anxn +
an-1xn-1 + ... + a1x + a0 = 0.
The rational root theorem states that if x = p/q is a solution,
then p divides a0 and q divides an
In your case, an is 1 and a0 is equal to S(x)-N. Thus, we know that any solution must divide S(x)-N.
This is where ben75's tip comes in. Since S(x) can't be bigger than 81, we can loop through all of the possible values of S(x), and solve separately. Something like this:
for each possible value of S(x)
loop through every factor x of S(x) - N
check if it is between A and B, if its digits sum to S(x)
and if it is a solution to x*x + 200x + S(x) = N.
if it is, return it.
return -1
There's also a pretty slick way for you to loop through all of the factors of a number, but I'll let you work that one out for yourself since this is for a course. My hint there is to look at the prime factorization of a number.
For the equation x^2+s(x)+200·x=N, consider
x^2 + 200·x + (N - s(x)) = 0
For a solution to a*x^2 + b*x + c = 0 equation with integer solutions, we need to have:
b^2 - 4*a*c >= 0 and must be a perfect square
Hence 200^2 - 4 * (N - s(x)) >=0 and a square or
10000 >= (N - s(x)) and (10,000 - (N - s(x)) must be a square. The square value is therefore less than 10,000 and hence there can be at most 100 values you need to check. With proper values of N it can be much lesser.
Also note that since N < 10,000, s(x) can be at most 36. These should cut down the range quite a bit.
Related
What is Cardano Triplet ?
If a set of any three positive integers, let's say a, b and c satisfies the condition
cbrt(a + b(sqrt(c)) + cbrt(a - b(sqrt(c)) == 1
Explanation.
if sum of Cubic Root of a + (b * square root of c) and Cubic root of a - (b * square root of c) equals 1 then (a, b, c) is said to be a Cardano triplet.
cbrt represents Cubic Root and sqrt means Square Root.
A integer n will be given, so the numbers a, b and c that we take when added should be lesser than or equal to n.
In short a + b + c <= n.
Constraint : n <= 2^31 -1.
Problem
I've already done something which finds out the correct triplets but when the value of n is greater than 1000 the program runs forever.
public static void cardanoTriplets(long n) {
DecimalFormat decimalFormat = new DecimalFormat("#.###");
long numberOfPairs = 0;
for (long a = 0; a <= n; a++) {
for (long b = 0; b <= n; b++) {
for (long c = 0; c <= (n - a - b); c++) {
if ((a + b + c) == n) {
double val = b * Math.sqrt(c);
double LHS = Double.parseDouble(decimalFormat.format(Math.cbrt(a + val)));
double RHS = Double.parseDouble(decimalFormat.format(Math.cbrt(a - val)));
double addedVal = LHS + RHS;
//System.out.println("RHS and LHS -: ( " + RHS + " , " + LHS + " )");
if (addedVal == 1.0d) {
numberOfPairs++;
//System.out.println(a);
//System.out.println(b);
//System.out.println(c + "\n");
}
}
}
}
}
System.out.println(numberOfPairs);
}
Results
When I pass the value of n as 8, on average the time taken to find the cardano triplet is 31ms and sometimes as low as 16ms. The result was accurate and the result is just one and the triplet is (2, 1, 5).
But when I pass the value of n as 1000, it increases to about 1015ms and the result are not as accurate. It misses out almost 19 triplets. Total number of triplets are 149 for n == 1000.
When the value of n > 1000, let's say 5000, it took 29271ms which is 29 seconds approx and the triplets found are 3364.
Is there any way to reduce time taken to a reasonable amount like less than 5 seconds ?
If so how ?
My Device Specs :
Processor : AMD Ryzen 5 3500U Quad Core
RAM : 8 GB
IDE used : IntelliJ IDEA v2021.2.3 (Community Edition)
Thank you :)
This is a number-theoretical problem; using an imprecise floating point is obviously wrong.
The correct solution requires some math insight. Cardano's name is a great hint.
The expression
cbrt(a + b(sqrt(c)) + cbrt(a - b(sqrt(c))
describes a root of a certain cubic equation. Specifically, the roots of an equation
x^3 + px - q = 0
are
cbrt(q/2 + sqrt((q/2)^2 + (p/3)^3)) + cbrt(q/2) - sqrt(q/2)^2 + (p/3)^3))
Comparing with your problem statement, conclude that a = q/2, and c*b^2 = (q/2)^2 + (p/3)^3
Since a is an integer, q must be even, and since b, c are also integers, p must be divisible by 3. Therefore we are interested in the equations
x^3 + 3ux - 2a = 0
having 1 as a root. That narrows the problem down to searching u, v such that 1 + 3u - 2a = 0. Here u^3 + a^2 = b^2*c. Notice that u must be odd.
All these observations lead to a (pseudo)code:
for u in range(1, n, 2)
a = (1 + 3u)/2
t = u^3 + a^2
find the largest b such that b^2 divides t
c = t / b^2
if a + b + c < n
they are a Cardano triplet
Your first problem, is the loop-in-loop-in-loop what will take 1.000.000.000 rounds for n=1000.
As you know already that n = a + b + c, you can take one loop out. the c-loop
and rewrite as:
for (long a = 0; a <= n; a++) {
for (long b = 0; b <= (n - a); b++) {
long c = n - a - b;
so you go from n * n * n -> n * n
If the equation is n => a + b + c (as in your problem statement), you can use:
for (long a = 0; a <= n; a++) {
for (long b = 0; b <= (n - a); b++) {
for (long c = 0; c <= (n - a - b); c++) {
Second, you are doing a format to a decimal and then convert back to double where as the Math.cbrt gives already a double. I would suggest not doing so.
The problem of "missing 19 triplets" is related to the point above. You only accept 1.0d as the correct answer, there in the previous step you did formatting on the doubles (most likely giving rounding issues). Even if you would take out the formatting, I believe it is better to allow for a bit more rounding error..
something like:
if (0.999 < addedVal && addedVal < 1.001)
However, I have no idea on the math of this equation as there must be a reason why you say there are 149 triplets.. Depending on the rounding for sure you have different answers... I believe there is something like mathemathical proof the triplets are 1.
Last what you can do: I believe the calculation of the Math.cbrt is not that fast. You are repeating this a lot. You can keep track of your calculation by placing the result of the Math,cbrt in a HashSet. The Key is the input and the Value the result of the Math.cbrt.
So first check if you have the Key already in the HashSet, if not calculate the cbrt and place it, if already available us it..
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;
}
The motto is to find the sum of all the multiples of 3 or 5 below N.
Here's my code:
public class Solution
{
public static void main(String[] args)
{
Scanner in = new Scanner(System.in);
int t = in.nextInt();
long n=0;
long sum=0;
for(int a0 = 0; a0 < t; a0++)
{
n = in.nextInt();
sum=0;
for(long i=1;i<n;i++)
{
if(i%3==0 || i%5==0)
sum = sum + i;
}
System.out.println(sum);
}
}
}
It's taking more than 1sec to execute for some of the test cases. Can anyone please help me out so as to reduce the time complexity?
We can find the sum of all multiples of number d that are below N as a sum of an arithmetic progression (their sum is equal to d + 2*d + 3*d + ...).
long multiplesSum(long N, long d) {
long highestMultiple = (N-1) / d * d;
long numberOfMultiples = highestMultiple / d;
return (d + highestMultiple) * numberOfMultiples / 2;
}
Then the result will be equal to:
long resultSum(long N) {
return multiplesSum(N, 3) + multiplesSum(N, 5) - multiplesSum(N, 3*5);
}
We need to subtract multiplesSum(N, 15) because there are numbers that are multiples of both 3 and 5 and we added them twice.
Complexity: O(1)
You can't reduce the time complexity in this case as there are still O(N) of each set of numbers. However you can reduce the constant multiplier by using integer division:
static int findMultiples(int N, int s)
{
int c = N / s, sum = 0;
for (int i = 0, k = s; i < c; i++, k += s)
sum += k;
return sum;
}
This way you only loop through the multiples themselves instead of the whole range [0, N].
Note that you will need to do findMultiples(N, 3) + findMultiples(N, 5) - findMultiples(N, 15), to remove the duplicated multiples of both 3 and 5. The number of loops is therefore N/3 + N/5 + N/15 = 0.6N instead of N.
EDIT: in general the solution for an arbitrary number of divisors is sum(findMultiples(N,divisor_i) - findMultiples(N,LCM(all_divisors)); however it is only worth doing this if sum(1/divisor_i) + 1/LCM(all_divisors) < 1, otherwise there will be more loops. Luckily this will never be true for 2 divisors.
The sum of all numbers from 1 to (including) N is known to be N(N+1)/2 (no need for iteration).
So, the sum of all multiples of K, from K to KM is K times the above formula, giving KM(M+1)/2.
Combine this with #meowgoesthedog's findMultiples(N, 3) + findMultiples(N, 5) - findMultiples(N, 15) idea, and you have a constant-time solution.
A solution for your problem.Fastest method for solving your problem.
import java.util.*;
class Solution {
public static void main(String[] args) {
Scanner in = new Scanner(System.in);
int t = in.nextInt();
while(t!=0)
{
long a=in.nextLong();
long q=a-1;
long aa=q/3;
long bb=q/5;
long cc=q/15;
long aaa=((aa*(aa+1))/2)*3;
long bbb=((bb*(bb+1))/2)*5;
long ccc=((cc*(cc+1))/2)*15;
System.out.println(aaa+bbb-ccc);
t-=1;}
}
}
I am working on a very simple spoj problem in which we have to take input N calculate its factorial then find out number of trailing zeros and display it some thing like
Sample Input:
6
3
60 // fact of 60 has 14 trailing zeros
100
1024
23456
8735373
Sample Output:
0
14
24
253
5861
2183837
so i have written a code which is working fine on my machine but when i am submitting it is giving me time limit error. i don't know how to make this code fast. So i want suggestions from you guys.
public class Factorial {
public static void main(String[] args) throws IOException {
try {
BufferedReader bf = new BufferedReader(new InputStreamReader(System.in));
int t = Integer.parseInt(bf.readLine());
for (int i = 0; i < t; i++) {
Long num = Long.parseLong(bf.readLine());
BigInteger bd = BigInteger.valueOf(num);
System.out.println(countTrailinZeros(factorial(bd.toString())));
}
} catch (IllegalStateException e) {
return;
}
}
public static BigInteger factorial(String n) {
BigInteger x = BigInteger.valueOf(1);
for (long i = 1; i <= Integer.parseInt(n); i++) {
x = x.multiply(BigInteger.valueOf(i));
}
return x;
}
public static int countTrailinZeros(BigInteger bd) {
String s = bd.toString();
int glen = s.length();
s = s.replaceAll("[0.]*$", "");
int llen = s.length();
return glen - llen;
}
}
I have googled about some possible solutions and found out that lookup table may work i don't have much idea about this. I'd be very thankful if some can explain me about lookup table.
edit: Could it be java is too slow to solve this problem in given time? or in general it is not favorable to use java for competitive programing?
you dont need to calculate factorial to get number of trailing zeroes.
Solution :
import java.io.BufferedReader;
import java.io.IOException;
import java.io.InputStreamReader;
public class Main {
public static void main(String[] args) throws IOException {
BufferedReader br = new BufferedReader(new InputStreamReader(System.in));
int lines = Integer.parseInt(br.readLine());
int sum, N, p;
for (int i = 0; i < lines; i++) {
N = Integer.parseInt(br.readLine());
sum = 0;
p = 5;
while (N / p != 0) {
sum = sum + N / p;
p = p * 5;
}
System.out.println(sum);
}
}
}
Logic is :
The highest power of a prime number p in N! is given by
floor(N/p) + floor(N/p*p) + floor(N/p*p*p) ... so on till [floor(N/p^n) = 0]
so since number of ending zeroes is required , ans = min(max power of 2 in N!, max power of 5 in N!)
because zeroes appears on multiplication by ten and ten can be decomposed to 10 = (2 * 5).
It is fine to assume that max power of 5 in N! is always less than max power of 2 in N!.
as multiples of 2 occur more frequently than multiples of 5.
So problem reduces to finding max power of 5 in N! and hence the solution.
Example :
N = 5
max power of 5 in 5! = floor(5/5) + floor(5/25) => 1 + 0 => ans = 1
N = 100
max power of 5 in 100! = floor(100/5) + floor(100/25) + floor(100/125) => 20 + 4 + 0 => ans = 24
I have solved the same problem in spoj platform, you just have to divide the value by 5 until the value becomes less than 5. print all the result of the division and that's your output.
To solve this problem, consider prime factorization of N factorial:
N! = 2^a1 * 3^a2 * 5^a3 * .... where a1, a2, a3, ... >= 0
Since N! = N*(N-1)(N-2)..., multiples of 2 are more frequent than 5.
So, a1 >= a3 in this expansion.
Number of trailing zeros = how many times you can divide N! by 10.
Which implies, ans = min(a1, a3) based on the prime factorization given above.
Since we already proved a1 >= a3, hence ans = a3, i.e power of 5 in the prime factorization of N!.
There will be floor(N/5) numbers that will contribute to power of 5 atleast once.
There will be floor(N/25) numbers that will contribute to power of 5 atleast twice.
There will be floor(N/125) numbers that will contribute atleast thrice
and so on.
The total power of 5 = floor(N/5) + floor(N/25) + floor(N/125) + ...
Implementation of this formula in code is left as an exercise.
I just gave a coding interview on codility
I was asked the to implement the following, but i was not able to finish it in 20 minutes, now I am here to get ideas form this community
Write a function public int whole_cubes_count ( int A,int B ) where it should return whole cubes within the range
For example if A=8 and B=65, all the possible cubes in the range are 2^3 =8 , 3^3 =27 and 4^3=64, so the function should return count 3
I was not able to figure out how to identify a number as whole cube. How do I solve this problem?
A and B can have range from [-20000 to 20000]
This is what I tried
import java.util.Scanner;
class Solution1 {
public int whole_cubes_count ( int A,int B ) {
int count =0;
while(A<=B)
{
double v = Math.pow(A, 1 / 3); // << What goes here?
System.out.println(v);
if (v<=B)
{
count=count+1;
}
A =A +1;
}
return count ;
}
public static void main(String[] args)
{
System.out.println("Enter 1st Number");
Scanner scan = new Scanner(System.in);
int s1 = scan.nextInt();
System.out.println("Enter 2nd Number");
//Scanner scan = new Scanner(System.in);
int s2 = scan.nextInt();
Solution1 n = new Solution1();
System.out.println(n.whole_cubes_count (s1,s2));
}
}
Down and dirty, that's what I say.
If you only have 20 minutes, then they shouldn't expect super-optimized code. So don't even try. Play to the constraints of the system which say only +20,000 to -20,000 as the range. You know the cube values have to be within 27, since 27 * 27 * 27 = 19683.
public int whole_cubes_count(int a, int b) {
int count = 0;
int cube;
for (int x = -27; x <= 27; x++) {
cube = x * x * x;
if ((cube >= a) && (cube <= b))
count++;
}
return count;
}
For the positive cubes:
i = 1
while i^3 < max
++i
Similarly for the negative cubes but with an absolute value in the comparison.
To make this more general, you need to find the value of i where i^3 >= min, in the case that both min and max are positive. A similar solution works if both min and max are negative.
Well, it can be computed with O(1) complexity, we will need to find the largest cube that fits into the range, and the smallest one. All those that are between will obviously also be inside.
def n_cubes(A, B):
a_cr = int(math.ceil(cube_root(A)))
b_cr = int(math.floor(cube_root(B)))
if b_cr >= a_cr:
return b_cr - a_cr + 1
return 0
just make sure your cube_root returns integers for actual cubes. Complete solution as gist https://gist.github.com/tymofij/9035744
int countNoOfCubes(int a, int b) {
int count = 0;
for (int startsCube = (int) Math.ceil(Math.cbrt(a)); Math.pow(
startsCube, 3.0) <= b; startsCube++) {
count++;
}
return count;
}
The solution suggested by #Tim is faster than the one provided by #Erick, especially when A...B range increased.
Let me quote the ground from github here:
"one can notice that x³ > y³ for any x > y. (that is called monotonic function)
therefore for any x that lies in ∛A ≤ x ≤ ∛B, cube would fit: A ≤ x³ ≤ B
So to get number of cubes which lie within A..B, you can simply count number of integers between ∛A and ∛B. And number of integers between two numbers is their difference."
It seems perfectly correct, isn't it? It works for any power, not only for cube.
Here is my port of cube_root method for java:
/*
* make sure your cube_root returns integers for actual cubes
*/
static double cubeRoot(int x) {
//negative number cannot be raised to a fractional power
double res = Math.copySign(Math.pow(Math.abs(x), (1.0d/3)) , x);
long rounded_res = symmetricRound(res);
if (rounded_res * rounded_res * rounded_res == x)
return rounded_res;
else
return res;
}
private static long symmetricRound( double d ) {
return d < 0 ? - Math.round( -d ) : Math.round( d );
}
I am aware of Math.cbrt in java but with Math.pow approach it is easy to generalize the solution for other exponents.