First, sorry for my bad English.
Special numbers are numbers that the sum of the digits is divisible to the number of the digit.
Example: 135 is a special number because the sum of the digits is 1+3+5 = 9, the number of the digit is 3, and 9 is divisible to 3 because 9 % 3 == 0. 2,3,9,13,17,15,225, 14825 are also special numbers.
Requirement:
Write a program that read the number n (n <= 10^6) from a file named SNUMS.INP (SNUMS.INP can contain up to 10^6 numbers) and print the result out into the file SNUMS.OUT. Number n is the order of the special number and the result will be that special number in n order (sorry I don't know how to express it).
Example: n = 3 means you have to print out the 3rd special number which is 3, n = 10 you have to print out 10th special number which is 11, n = 13 you have to print out 13th special number which is 17, n = 15 you have to print out 15th special number which is 20.
The example bellow will demonstrate the file SNUMS.INP and SNUMS.OUT (Remember: SNUMS.INP can contain up to 10^6 numbers)
SNUMS.INP:
2
14
17
22
SNUMS.OUT:
2
19
24
35
I have my own alogrithm but the the running time exceeds 1 second (my SNUMS.INP has 10^6 numbers). So I need the optimal alogrithm so that the running time will be less than or equal 1s.
Guys I decide to post my own code which is written in Java, it always take more than 4 seconds to run. Could you guys please suggest some ideas to improve or how to make it run faster
import java.util.Scanner;
import java.io.*;
public class Test
{
public static void main(String[]args) throws IOException
{
File file = new File("SNUMS.INP");
Scanner inputFile = new Scanner(file);
int order = 1;
int i = 1;
int[] special = new int[1000000+1];
// Write all 10^6 special numbers into an array named "special"
while (order <= 1000000)
{
if (specialNumber(i) == true)
{
special[order] = i;
order++;
}
i++;
}
// Write the result to file
PrintWriter outputFile = new PrintWriter("SNUMS.OUT");
outputFile.println(special[inputFile.nextInt()]);
while (inputFile.hasNext())
outputFile.println(special[inputFile.nextInt()]);
outputFile.close();
}
public static boolean specialNumber(int i)
{
// This method check whether the number is a special number
boolean specialNumber = false;
byte count=0;
long sum=0;
while (i != 0)
{
sum = sum + (i % 10);
count++;
i = i / 10;
}
if (sum % count == 0) return true;
else return false;
}
}
This is file SNUMS.INP (sample) contains 10^6 numbers if you guys want to test.
https://drive.google.com/file/d/0BwOJpa2dAZlUNkE3YmMwZmlBOTg/view?usp=sharing
I've managed to solve it in 0.6 seconds on C# 6.0 (.Net 4.6 IA-64) at Core i7 3.2 GHz with HDD 7200 rpc; hope that precompution will be fast enough at your workstation:
// Precompute beautiful numbers
private static int[] BeautifulNumbers(int length) {
int[] result = new int[length];
int index = 0;
for (int i = 1; ; ++i) {
int sum = 0;
int count = 0;
for (int v = i; v > 0; sum += v % 10, ++count, v /= 10)
;
if (sum % count == 0) {
result[index] = i;
if (++index >= result.Length)
return result;
}
}
}
...
// Test file with 1e6 items
File.WriteAllLines(#"D:\SNUMS.INP", Enumerable
.Range(1, 1000000)
.Select(index => index.ToString()));
...
Stopwatch sw = new Stopwatch();
sw.Start();
// Precomputed numbers (about 0.3 seconds to be created)
int[] data = BeautifulNumbers(1000000);
// File (about 0.3 seconds for both reading and writing)
var result = File
.ReadLines(#"D:\SNUMS.INP")
.Select(line => data[int.Parse(line) - 1].ToString());
File.WriteAllLines(#"D:\SNUMS.OUT", result);
sw.Stop();
Console.Write("Elapsed time {0}", sw.ElapsedMilliseconds);
The output vary from
Elapsed time 516
to
Elapsed time 660
with average elapsed time at about 580 milliseconds
Now that you have the metaphor of abacus implemented below, here are some hints
instead of just incrementing with 1 inside a cycle, can we incremente more aggressively? Indeed we can, but with an extra bit of care.
first, how much aggressive we can be? Looking to 11 (first special with 2 digits), it doesn't pay to just increment by 1, we can increment it by 2. Looking to 102 (special with 3 digits), we can increment it by 3. Is it natural to think we should use increments equal with the number of digits?
now the "extra bit of care" - whenever the "increment by the number of digits" causes a "carry", the naive increment breaks. Because the carry will add 1 to the sum of digits, so that we may need to subtract that one from something to keep the sum of digits well behaved.
one of the issues in the above is that we jumped quite happily at "first special with N digits", but the computer is not us to see it at a glance. Fortunately, the "first special with N digits" is easy to compute: it is 10^(N-1)+(N-1) - 10^(N-1) brings an 1 and the rest is zero, and N-1 brings the rest to make the sum of digits be the first divisible with N. Of course, this will break down if N > 10, but fortunately the problem is limited to 10^6 special numbers, which will require at most 7 digits (the millionth specual number is 6806035 - 7 digits);
so, we can detect the "first special number with N digits" and we know we should try with care to increment it by N. Can we look now better into that "extra care"?.
The code - twice as speedy as the previous one and totally "orthodox" in obtaining the data (via getters instead of direct access to data members).
Feel free to inline:
import java.util.ArrayList;
import java.util.Arrays;
public class Abacus {
static protected int pow10[]=
{1,10,100,1000, 10000, 100000, 1000000, 10000000, 100000000}
;
// the value stored for line[i] corresponds to digit[i]*pow10[i]
protected int lineValues[];
protected int sumDigits;
protected int representedNumber;
public Abacus() {
this.lineValues=new int[0];
this.sumDigits=0;
this.representedNumber=0;
}
public int getLineValue(int line) {
return this.lineValues[line];
}
public void clearUnitLine() {
this.sumDigits-=this.lineValues[0];
this.representedNumber-=this.lineValues[0];
this.lineValues[0]=0;
}
// This is how you operate the abacus in real life being asked
// to add a number of units to the line presenting powers of 10
public boolean addWithCarry(int units, int line) {
if(line-1==pow10.length) {
// don't have enough pow10 stored
pow10=Arrays.copyOf(pow10, pow10.length+1);
pow10[line]=pow10[line-1]*10;
}
if(line>=this.lineValues.length) {
// don't have enough lines for the carry
this.lineValues=Arrays.copyOf(this.lineValues, line+1);
}
int digitOnTheLine=this.lineValues[line]/pow10[line];
int carryOnTheNextLine=0;
while(digitOnTheLine+units>=10) {
carryOnTheNextLine++;
units-=10;
}
if(carryOnTheNextLine>0) {
// we have a carry, the sumDigits will be affected
// 1. the next two statememts are equiv with "set a value of zero on the line"
this.sumDigits-=digitOnTheLine;
this.representedNumber-=this.lineValues[line];
// this is the new value of the digit to set on the line
digitOnTheLine+=units;
// 3. set that value and keep all the values synchronized
this.sumDigits+=digitOnTheLine;
this.lineValues[line]=digitOnTheLine*pow10[line];
this.representedNumber+=this.lineValues[line];
// 4. as we had a carry, the next line will be affected as well.
this.addWithCarry(carryOnTheNextLine, line+1);
}
else { // we an simply add the provided value without carry
int delta=units*pow10[line];
this.lineValues[line]+=delta;
this.representedNumber+=delta;
this.sumDigits+=units;
}
return carryOnTheNextLine>0;
}
public int getSumDigits() {
return this.sumDigits;
}
public int getRepresentedNumber() {
return this.representedNumber;
}
public int getLinesCount() {
return this.lineValues.length;
}
static public ArrayList<Integer> specials(int N) {
ArrayList<Integer> ret=new ArrayList<>(N);
Abacus abacus=new Abacus();
ret.add(1);
abacus.addWithCarry(1, 0); // to have something to add to
int increment=abacus.getLinesCount();
while(ret.size()<N) {
boolean hadCarry=abacus.addWithCarry(increment, 0);
if(hadCarry) {
// need to resynch the sum for a perfect number
int newIncrement=abacus.getLinesCount();
abacus.clearUnitLine();
if(newIncrement!=increment) {
// we switched powers of 10
abacus.addWithCarry(newIncrement-1, 0);
increment=newIncrement;
}
else { // simple carry
int digitsSum=abacus.getSumDigits();
// how much we should add to the last digit to make the sumDigits
// divisible again with the increment?
int units=increment-digitsSum % increment;
if(units<increment) {
abacus.addWithCarry(units, 0);
}
}
}
ret.add(abacus.getRepresentedNumber());
}
return ret;
}
// to understand how the addWithCarry works, try the following code
static void add13To90() {
Abacus abacus; // starts with a represented number of 0
// line==1 means units of 10^1
abacus.addWithCary(9, 1); // so this should make the abacus store 90
System.out.println(abacus.getRepresentedNumber());
// line==0 means units of 10^0
abacus.addWithCarry(13, 0);
System.out.println(abacus.getRepresentedNumber()); // 103
}
static public void main(String[] args) {
int count=1000000;
long t1=System.nanoTime();
ArrayList<Integer> s1=Abacus.specials(count);
long t2=System.nanoTime();
System.out.println("t:"+(t2-t1));
}
}
Constructing the numbers from their digits is bound to be faster.
Remember the abacus? Ever used one?
import java.util.ArrayList;
public class Specials {
static public ArrayList<Integer> computeNSpecials(int N) {
ArrayList<Integer> specials = new ArrayList<>();
int abacus[] = new int[0]; // at index i we have the digit for 10^i
// This way, when we don't have enough specials,
// we simply reallocate the array and continue
while (specials.size() < N) {
// see if a carry operation is necessary
int currDigit = 0;
for (; currDigit < abacus.length && abacus[currDigit] == 9; currDigit++) {
abacus[currDigit] = 0; // a carry occurs when adding 1
}
if (currDigit == abacus.length) {
// a carry, but we don't have enough lines on the abacus
abacus = new int[abacus.length + 1];
abacus[currDigit] = 1; // we resolved the carry, all the digits below
// are 0
} else {
abacus[currDigit]++; // we resolve the carry (if there was one),
currDigit = 0; // now it's safe to continue incrementing at 10^0
}
// let's obtain the current number and the sum of the digits
int sumDigits = 0;
for (int i = 0; i<abacus.length; i++) {
sumDigits += abacus[i];
}
// is it special?
if (sumDigits % abacus.length == 0) {
// only now compute the number and collect it as special
int number = 0;
for (int i = abacus.length - 1; i >= 0; i--) {
number = 10 * number + abacus[i];
}
specials.add(number);
}
}
return specials;
}
static public void main(String[] args) {
ArrayList<Integer> specials=Specials.computeNSpecials(100);
for(int i=0; i<specials.size(); i++) {
System.out.println(specials.get(i));
}
}
}
Related
I'm doing online course and got stuck at this problem.
The first line contains two non-negative integers 1 ≤ n, m ≤ 50000 — the number of segments and points on a line, respectively. The next n lines contain two integers a_i ≤ b_i defining the i-th segment. The next line contain m integers defining points. All the integers are of absolute value at most 10^8. For each segment, output the number of points it is used from the n-points table.
My solution is :
for point in points:
occurrence = 0
for l, r in segments:
if l <= point <= r:
occurrence += 1
print(occurrence),
The complexity of this algorithm is O(m*n), which is obviously not very efficient. What is the best way of solving this problem? Any help will be appreciated!
Sample Input:
2 3
0 5
7 10
1 6 11
Sample Output:
1 0 0
Sample Input 2:
1 3
-10 10
-100 100 0
Sample Output 2:
0 0 1
You can use sweep line algorithm to solve this problem.
First, break each segment into two points, open and close points.
Add all these points together with those m points, and sort them based on their locations.
Iterating through the list of points, maintaining a counter, every time you encounter an open point, increase the counter, and if you encounter an end point, decrease it. If you encounter a point in list m point, the result for this point is the value of counter at this moment.
For example 2, we have:
1 3
-10 10
-100 100 0
After sorting, what we have is:
-100 -10 0 10 100
At point -100, we have `counter = 0`
At point -10, this is open point, we increase `counter = 1`
At point 0, so result is 1
At point 10, this is close point, we decrease `counter = 0`
At point 100, result is 0
So, result for point -100 is 0, point 100 is 0 and point 0 is 1 as expected.
Time complexity is O((n + m) log (n + m)).
[Original answer] by how many segments is each point used
I am not sure I got the problem correctly but looks like simple example of Histogram use ...
create counter array (one item per point)
set it to zero
process the last line incrementing each used point counter O(m)
write the answer by reading histogram O(n)
So the result should be O(m+n) something like (C++):
const int n=2,m=3;
const int p[n][2]={ {0,5},{7,10} };
const int s[m]={1,6,11};
int i,cnt[n];
for (i=0;i<n;i++) cnt[i]=0;
for (i=0;i<m;i++) if ((s[i]>=0)&&(s[i]<n)) cnt[s[i]]++;
for (i=0;i<n;i++) cout << cnt[i] << " "; // result: 0 1
But as you can see the p[] coordinates are never used so either I missed something in your problem description or you missing something or it is there just to trick solvers ...
[edit1] after clearing the inconsistencies in OP the result is a bit different
By how many points is each segment used:
create counter array (one item per segment)
set it to zero
process the last line incrementing each used point counter O(m)
write the answer by reading histogram O(m)
So the result is O(m) something like (C++):
const int n=2,m=3;
const int p[n][2]={ {0,5},{7,10} };
const int s[m]={1,6,11};
int i,cnt[m];
for (i=0;i<m;i++) cnt[i]=0;
for (i=0;i<m;i++) if ((s[i]>=0)&&(s[i]<n)) cnt[i]++;
for (i=0;i<m;i++) cout << cnt[i] << " "; // result: 1,0,0
[Notes]
After added new sample set to OP it is clear now that:
indexes starts from 0
the problem is how many points from table p[n] are really used by each segment (m numbers in output)
Use Binary Search.
Sort the line segments according to 1st value and the second value. If you use c++, you can use custom sort like this:
sort(a,a+n,fun); //a is your array of pair<int,int>, coordinates representing line
bool fun(pair<int,int> a, pair<int,int> b){
if(a.first<b.first)
return true;
if(a.first>b.first)
return false;
return a.second < b.second;
}
Then, for every point, find the 1st line that captures the point and the first line that does not (after the line that does of course). If no line captures the point, you can return -1 or something (and not check for the point that does not).
Something like:
int checkFirstHold(pair<int,int> a[], int p,int min, int max){ //p is the point
while(min < max){
int mid = (min + max)/2;
if(a[mid].first <= p && a[mid].second>=p && a[mid-1].first<p && a[mid-1].second<p) //ie, p is in line a[mid] and not in line a[mid-1]
return mid;
if(a[mid].first <= p && a[mid].second>=p && a[mid-1].first<=p && a[mid-1].second>=p) //ie, p is both in line a[mid] and not in line a[mid-1]
max = mid-1;
if(a[mid].first < p && a[mid].second<p ) //ie, p is not in line a[mid]
min = mid + 1;
}
return -1; //implying no point holds the line
}
Similarly, write a checkLastHold function.
Then, find checkLastHold - checkFirstHold for every point, which is the answer.
The complexity of this solution will be O(n log m), as it takes (log m) for every calculation.
Here is my counter-based solution in Java.
Note that all points, segment start and segment end are read into one array.
If points of different PointType have the same x-coordinate, then the point is sorted after segment start and before segment end. This is done to count the point as "in" the segment if it coincides with both the segment start (counter already increased) and the segment end (counter not yet decreased).
For storing an answer in the same order as the points from the input, I create the array result of size pointsCount (only points counted, not the segments) and set its element with index SuperPoint.index, which stores the position of the point in the original input.
import java.util.Arrays;
import java.util.Scanner;
public final class PointsAndSegmentsSolution {
enum PointType { // in order of sort, so that the point will be counted on both segment start and end coordinates
SEGMENT_START,
POINT,
SEGMENT_END,
}
static class SuperPoint {
final PointType type;
final int x;
final int index; // -1 (actually does not matter) for segments, index for points
public SuperPoint(final PointType type, final int x) {
this(type, x, -1);
}
public SuperPoint(final PointType type, final int x, final int index) {
this.type = type;
this.x = x;
this.index = index;
}
}
private static int[] countSegments(final SuperPoint[] allPoints, final int pointsCount) {
Arrays.sort(allPoints, (o1, o2) -> {
if (o1.x < o2.x)
return -1;
if (o1.x > o2.x)
return 1;
return Integer.compare( o1.type.ordinal(), o2.type.ordinal() ); // points with the same X coordinate by order in PointType enum
});
final int[] result = new int[pointsCount];
int counter = 0;
for (final SuperPoint superPoint : allPoints) {
switch (superPoint.type) {
case SEGMENT_START:
counter++;
break;
case SEGMENT_END:
counter--;
break;
case POINT:
result[superPoint.index] = counter;
break;
default:
throw new IllegalArgumentException( String.format("Unknown SuperPoint type: %s", superPoint.type) );
}
}
return result;
}
public static void main(final String[] args) {
final Scanner scanner = new Scanner(System.in);
final int segmentsCount = scanner.nextInt();
final int pointsCount = scanner.nextInt();
final SuperPoint[] allPoints = new SuperPoint[(segmentsCount * 2) + pointsCount];
int allPointsIndex = 0;
for (int i = 0; i < segmentsCount; i++) {
final int start = scanner.nextInt();
final int end = scanner.nextInt();
allPoints[allPointsIndex] = new SuperPoint(PointType.SEGMENT_START, start);
allPointsIndex++;
allPoints[allPointsIndex] = new SuperPoint(PointType.SEGMENT_END, end);
allPointsIndex++;
}
for (int i = 0; i < pointsCount; i++) {
final int x = scanner.nextInt();
allPoints[allPointsIndex] = new SuperPoint(PointType.POINT, x, i);
allPointsIndex++;
}
final int[] pointsSegmentsCounts = countSegments(allPoints, pointsCount);
for (final int count : pointsSegmentsCounts) {
System.out.print(count + " ");
}
}
}
I recently came across this question - Given a binary string, check if we can partition/split the string into 0..n parts such that each part is a power of 5. Return the minimum number of splits, if it can be done.
Examples would be:
input = "101101" - returns 1, as the string can be split once to form "101" and "101",as 101= 5^1.
input = "1111101" - returns 0, as the string itself is 5^3.
input = "100"- returns -1, as it can't be split into power(s) of 5.
I came up with this recursive algorithm:
Check if the string itself is a power of 5. if yes, return 0
Else, iterate over the string character by character, checking at every point if the number seen so far is a power of 5. If yes, add 1 to split count and check the rest of the string recursively for powers of 5 starting from step 1.
return the minimum number of splits seen so far.
I implemented the above algo in Java. I believe it works alright, but it's a straightforward recursive solution. Can this be solved using dynamic programming to improve the run time?
The code is below:
public int partition(String inp){
if(inp==null || inp.length()==0)
return 0;
return partition(inp,inp.length(),0);
}
public int partition(String inp,int len,int index){
if(len==index)
return 0;
if(isPowerOfFive(inp,index))
return 0;
long sub=0;
int count = Integer.MAX_VALUE;
for(int i=index;i<len;++i){
sub = sub*2 +(inp.charAt(i)-'0');
if(isPowerOfFive(sub))
count = Math.min(count,1+partition(inp,len,i+1));
}
return count;
}
Helper functions:
public boolean isPowerOfFive(String inp,int index){
long sub = 0;
for(int i=index;i<inp.length();++i){
sub = sub*2 +(inp.charAt(i)-'0');
}
return isPowerOfFive(sub);
}
public boolean isPowerOfFive(long val){
if(val==0)
return true;
if(val==1)
return false;
while(val>1){
if(val%5 != 0)
return false;
val = val/5;
}
return true;
}
Here is simple improvements that can be done:
Calculate all powers of 5 before start, so you could do checks faster.
Stop split input string if the number of splits is already greater than in the best split you've already done.
Here is my solution using these ideas:
public static List<String> powers = new ArrayList<String>();
public static int bestSplit = Integer.MAX_VALUE;
public static void main(String[] args) throws Exception {
// input string (5^5, 5^1, 5^10)
String inp = "110000110101101100101010000001011111001";
// calc all powers of 5 that fits in given string
for (int pow = 1; ; ++pow) {
String powStr = Long.toBinaryString((long) Math.pow(5, pow));
if (powStr.length() <= inp.length()) { // can be fit in input string
powers.add(powStr);
} else {
break;
}
}
Collections.reverse(powers); // simple heuristics, sort powers in decreasing order
// do simple recursive split
split(inp, 0, -1);
// print result
if (bestSplit == Integer.MAX_VALUE) {
System.out.println(-1);
} else {
System.out.println(bestSplit);
}
}
public static void split(String inp, int start, int depth) {
if (depth >= bestSplit) {
return; // can't do better split
}
if (start == inp.length()) { // perfect split
bestSplit = depth;
return;
}
for (String pow : powers) {
if (inp.startsWith(pow, start)) {
split(inp, start + pow.length(), depth + 1);
}
}
}
EDIT:
I also found another approach which looks like very fast one.
Calculate all powers of 5 whose string representation is shorter than input string. Save those strings in powers array.
For every string power from powers array: if power is substring of input then save its start and end indexes into the edges array (array of tuples).
Now we just need to find shortest path from index 0 to index input.length() by edges from the edges array. Every edge has the same weight, so the shortest path can be found very fast with BFS.
The number of edges in the shortest path found is exactly what you need -- minimum number of splits of the input string.
Instead of calculating all possible substrings, you can check the binary representation of the powers of 5 in search of a common pattern. Using something like:
bc <<< "obase=2; for(i = 1; i < 40; i++) 5^i"
You get:
51 = 1012
52 = 110012
53 = 11111012
54 = 10011100012
55 = 1100001101012
56 = 111101000010012
57 = 100110001001011012
58 = 10111110101111000012
59 = 1110111001101011001012
510 = 1001010100000010111110012
511 = 101110100100001110110111012
512 = 11101000110101001010010100012
513 = 10010001100001001110011100101012
514 = 1011010111100110001000001111010012
515 = 111000110101111110101001001100011012
516 = 100011100001101111001001101111110000012
517 = 10110001101000101011110000101110110001012
518 = 1101111000001011011010110011101001110110012
...
529 = 101000011000111100000111110101110011011010111001000010111110010101012
As you can see, odd powers of 5 always ends with 101 and even powers of 5 ends with the pattern 10+1 (where + means one or more occurrences).
You could put your input string in a trie and then iterate over it identifying the 10+1 pattern, once you have a match, evaluate it to check if is not a false positive.
You just have to save the value for a given string in a map. For example having if you have a string ending like this: (each letter may be a string of arbitrary size)
ABCD
You find that part A mod 5 is ok, so you try again for BCD, but find that B mod 5 is also ok, same for C and D as well as CD together. Now you should have the following results cached:
C -> 0
D -> 0
CD -> 0
BCD -> 1 # split B/CD is the best
But you're not finished with ABCD - you find that AB mod 5 is ok, so you check the resulting CD - it's already in the cache and you don't have to process it from the beginning.
In practice you just need to cache answers from partition() - either for the actual string or for the (string, start, length) tuple. Which one is better depends on how many repeating sequences you have and whether it's faster to compare the contents, or just indexes.
Given below is a solution in C++. Using dynamic programming I am considering all the possible splits and saving the best results.
#include<bits/stdc++.h>
using namespace std;
typedef long long ll;
int isPowerOfFive(ll n)
{
if(n == 0) return 0;
ll temp = (ll)(log(n)/log(5));
ll t = round(pow(5,temp));
if(t == n)
{
return 1;
}
else
{
return 0;
}
}
ll solve(string s)
{
vector<ll> dp(s.length()+1);
for(int i = 1; i <= s.length(); i++)
{
dp[i] = INT_MAX;
for(int j = 1; j <= i; j++)
{
if( s[j-1] == '0')
{
continue;
}
ll num = stoll(s.substr(j-1, i-j+1), nullptr, 2);
if(isPowerOfFive(num))
{
dp[i] = min(dp[i], dp[j-1]+1);
}
}
}
if(dp[s.length()] == INT_MAX)
{
return -1;
}
else
{
return dp[s.length()];
}
}
int main()
{
string s;
cin>>s;
cout<<solve(s);
}
I found this to be asked as an interview question. While it is fairly trivial to solve using bit masking and loops, any idea on how this can be done without loops? While I'm looking for an algorithm, any code would be appreciated as well.
The options I see for solving the problem without loops are bit hacks, recursion and loop unrolling.
Solving this with bit hacks seems quite difficult - most likely something only the most skilled bit hackers would be able to figure out in the time limit of an interview, or really figure out at all, but it's possible that that's who they were looking for.
Loop unrolling is just a silly solution.
So that leaves recursion.
Below is a recursive solution in Java.
It basically maintains the current count of consecutive zeros and also the best count, checks the last digit (i.e. checks the number modulo 10), sets these values appropriately and recurses on the number without the last digit (i.e. divided by 10).
I assumed we're talking about zeros in the decimal representation of the number, but converting this to use the binary representation is trivial (just change 10 to 2).
public static int countMaxConsecutiveZeros(int number)
{
return countMaxConsecutiveZeros(number, 0, 0);
}
private static int countMaxConsecutiveZeros(int number, int currentCount, int bestCount)
{
if (number == 0)
return bestCount;
if (number % 10 == 0)
currentCount++;
else
{
bestCount = Math.max(bestCount, currentCount);
currentCount = 0;
}
return countMaxConsecutiveZeros(number / 10, currentCount, bestCount);
}
public static void main(String[] args)
{
System.out.println(countMaxConsecutiveZeros(40040001)); // prints 3
}
Here's a roughly equivalent loop-based solution, which should provide a better understanding of the recursive solution:
private static int countMaxConsecutiveZerosWithLoop(int number)
{
int currentCount = 0, bestCount = 0;
while (number > 0)
{
if (number % 10 == 0)
currentCount++;
else
{
bestCount = Math.max(bestCount, currentCount);
currentCount = 0;
}
number /= 10;
}
return bestCount;
}
I don't know if this is what they were looking for, but here is a recursive solution.
I used two recursions, one comparing the current string of zeros to the record, and another recursion calculating the current string of zeros.
public class countconsecutivezeros{
public static void main(String[] Args){
int number = 40040001; // whatever the number is
System.out.println(consecutivezeros(number, 0));
}
public static int consecutivezeros(int number, int max){
if (number != 0){
if (max < zerosfrompoint(number)) max = zerosfrompoint(number);
return consecutivezeros(number/10, max);
}
return max;
}
public static int zerosfrompoint(int number){
int zeros = 0;
if ((number != 0) && ((number/10)*10 == number)){
zeros++;
System.out.println(zeros);
return zeros + zerosfrompoint(number/10);
}
return zeros;
}
}
Say I have 4 possible results and the probabilities of each result appearing are
1 = 10%
2 = 20%
3 = 30%
4 = 40%
I'd like to write a method like GetRandomValue which if called 1000 times would return
1 x 100 times
2 x 200 times
3 x 300 times
4 x 400 times
Whats the name of an algorithm which would produce such results?
in your case you can generate a random number (int) within 1..10 and if it's 1 then select 1, if it's between 2-3 select 2 and if it's between 4..6 select 3 and if is between 7..10 select 4.
In all if you have some probabilities which sum to 1, you can have a random number within (0,1) distribute your generated result to related value (I simplified in your case within 1..10).
To get a random number you would use the Random class of .Net.
Something like the following would accomplish what you requested:
public class MyRandom
{
private Random m_rand = new Random();
public int GetNextValue()
{
// Gets a random value between 0-9 with equal probability
// and converts it to a number between 1-4 with the probablities requested.
switch (m_rand.Next(0, 9))
{
case 0:
return 1;
case 1: case 2:
return 2;
case 3: case 4: case 5:
return 3;
default:
return 4;
}
}
}
If you just want those probabilities in the long run, you can just get values by randomly selecting one element from the array {1,2,2,3,3,3,4,4,4,4}.
If you however need to retrieve exactly 1000 elements, in those specific quantities, you can try something like this (not C#, but shouldn't be a problem):
import java.util.Random;
import java.util.*;
class Thing{
Random r = new Random();
ArrayList<Integer> numbers=new ArrayList<Integer>();
ArrayList<Integer> counts=new ArrayList<Integer>();
int totalCount;
public void set(int i, int count){
numbers.add(i);
counts.add(count);
totalCount+=count;
}
public int getValue(){
if (totalCount==0)
throw new IllegalStateException();
double pos = r.nextDouble();
double z = 0;
int index = 0;
//we select elements using their remaining counts for probabilities
for (; index<counts.size(); index++){
z += counts.get(index) / ((double)totalCount);
if (pos<z)
break;
}
int result = numbers.get(index);
counts.set( index , counts.get(index)-1);
if (counts.get(index)==0){
counts.remove(index);
numbers.remove(index);
}
totalCount--;
return result;
}
}
class Test{
public static void main(String []args){
Thing t = new Thing(){{
set(1,100);
set(2,200);
set(3,300);
set(4,400);
}};
int[]hist=new int[4];
for (int i=0;i<1000;i++){
int value = t.getValue();
System.out.print(value);
hist[value-1]++;
}
System.out.println();
double sum=0;
for (int i=0;i<4;i++) sum+=hist[i];
for (int i=0;i<4;i++)
System.out.printf("%d: %d values, %f%%\n",i+1,hist[i], (100*hist[i]/sum));
}
}
hi i am using Random class for getting random numbers but my requirement is once it generate one no that should not be repeate again pls help me.
Keep a list of the generated numbers and check this list before returning the next random.
Since you have not specified a language, I'll use C#
List<int> generated = new List<int>;
public int Next()
{
int r;
do { r = Random.Next() } while generated.Contains(r);
generated.Add(r);
return r;
}
The following C# code shows how to obtain 7 random cards with no duplicates. It is the most efficient method to use when your random number range is between 1 and 64 and are integers:
ulong Card, SevenCardHand;
int CardLoop;
const int CardsInDeck = 52;
Random RandObj = new Random(Seed);
for (CardLoop = 0; CardLoop < 7; CardLoop++)
{
do
{
Card = (1UL << RandObj.Next(CardsInDeck));
} while ((SevenCardHand & Card) != 0);
SevenCardHand |= Card;
}
If the random number range is greater than 64, then the next most efficient way to get random numbers without any duplicates is as follows from this C# code:
const int MaxNums = 1000;
int[] OutBuf = new int[MaxNums];
int MaxInt = 250000; // Reps the largest random number that should be returned.
int Loop, Val;
// Init the OutBuf with random numbers between 1 and MaxInt, which is 250,000.
BitArray BA = new BitArray(MaxInt + 1);
for (Loop = 0; Loop < MaxNums; Loop++)
{
// Avoid duplicate numbers.
for (; ; )
{
Val = RandObj.Next(MaxInt + 1);
if (BA.Get(Val))
continue;
OutBuf[Loop] = Val;
BA.Set(Val, true);
break;
}
}
The drawback with this technique is that it tends to use more memory, but it should be significantly faster than other approaches since it does not have to look through a large container each time a random number is obtained.