Related
I have got a code that generates all possible correct strings of balanced brackets. So if the input is n = 4 there should be 4 brackets in the string and thus the answers the code will give are: {}{} and
{{}}.
Now, what I would like to do is print the number of possible strings. For example, for n = 4 the outcome would be 2.
Given my code, is this possible and how would I make that happen?
Just introduce a counter.
// Change prototype to return the counter
int findBalanced(int p,int n,int o,int c)
{
static char str[100];
// The counter
static int count = 0;
if (c == n) {
// Increment it on every printout
count ++;
printf("%s\n", str);
// Just return zero. This is not used anyway and will give
// Correct result for n=0
return 0;
} else {
if (o > c) {
str[p] = ')';
findBalanced(p + 1, n, o, c + 1);
}
if (o < n) {
str[p] = '(';
findBalanced(p + 1, n, o + 1, c);
}
}
// Return it
return count;
}
What you're looking for is the n-th Catalan number. You'll need to implement binomial coefficient to calculate it, but that's pretty much it.
I have a question which asks us to reduce the string as follows.
The input is a string having only A, B or C. Output must be length of
the reduced string
The string can be reduced by the following rules
If any 2 different letters are adjacent, these two letters can be
replaced by the third letter.
Eg ABA -> CA -> B . So final answer is 1 (length of reduced string)
Eg ABCCCCCCC
This doesn't become CCCCCCCC, as it can be reduced alternatively by
ABCCCCCCC->AACCCCCC->ABCCCCC->AACCCC->ABCCC->AACC->ABC->AA
as here length is 2 < (length of CCCCCCCC)
How do you go about this problem?
Thanks a lot!
To make things clear: the question states it wants the minimum length of the reduced string. So in the second example above there are 2 solutions possible, one CCCCCCCC and the other AA. So 2 is the answer as length of AA is 2 which is smaller than the length of CCCCCCCC = 8.
The way this question is phrased, there are only three distinct possibilities:
If the string has only one unique character, the length is the same as the length of the string.
2/3. If the string contains more than one unique character, the length is either 1 or 2, always (based on the layout of the characters).
Edit:
As a way of proof of concept here is some grammar and its extensions:
I should note that although this seems to me a reasonable proof for the fact that the length will reduce to either 1 or 2, I am reasonably sure that determining which of these lengths will result is not as trivial as I originally thought ( you would still have to recurse through all options to find it out)
S : A|B|C|()
S : S^
where () denotes the empty string, and s^ means any combination of the previous [A,B,C,()] characters.
Extended Grammar:
S_1 : AS^|others
S_2 : AAS^|ABS^|ACS^|others
S_3 : AAAS^|
AABS^ => ACS^ => BS^|
AACS^ => ABS^ => CS^|
ABAS^ => ACS^ => BS^|
ABBS^ => CBS^ => AS^|
ABCS^ => CCS^ | AAS^|
ACAS^ => ABS^ => CS^|
ACBS^ => AAS^ | BBS^|
ACCS^ => BCS^ => AS^|
The same thing will happen with extended grammars starting with B, and C (others). The interesting cases are where we have ACB and ABC (three distinct characters in sequence), these cases result in grammars that appear to lead to longer lengths however:
CCS^: CCAS^|CCBS^|CCCS^|
CBS^ => AS^|
CAS^ => BS^|
CCCS^|
AAS^: AAAS^|AABS^|AACS^|
ACS^ => BS^|
ABS^ => CS^|
AAAS^|
BBS^: BBAS^|BBBS^|BBCS^|
BCS^ => AS^|
BAS^ => CS^|
BBBS^|
Recursively they only lead to longer lengths when the remaining string contains their value only. However we have to remember that this case also can be simplified, since if we got to this area with say CCCS^, then we at one point previous had ABC ( or consequently CBA ). If we look back we could have made better decisions:
ABCCS^ => AACS^ => ABS^ => CS^
CBACS^ => CBBS^ => ABS^ => CS^
So in the best case at the end of the string when we make all the correct decisions we end with a remaining string of 1 character followed by 1 more character(since we are at the end). At this time if the character is the same, then we have a length of 2, if it is different, then we can reduce one last time and we end up with a length of 1.
You can generalize the result based on individual character count of string. The algo is as follows,
traverse through the string and get individual char count.
Lets say if
a = no# of a's in given string
b = no# of b's in given string
c = no# of c's in given string
then you can say that, the result will be,
if((a == 0 && b == 0 && c == 0) ||
(a == 0 && b == 0 && c != 0) ||
(a == 0 && b != 0 && c == 0) ||
(a != 0 && b == 0 && c == 0))
{
result = a+b+c;
}
else if(a != 0 && b != 0 && c != 0)
{
if((a%2 == 0 && b%2 == 0 && c%2 == 0) ||
(a%2 == 1 && b%2 == 1 && c%2 == 1))
result = 2;
else
result = 1;
}
else if((a == 0 && b != 0 && c != 0) ||
(a != 0 && b == 0 && c != 0) ||
(a != 0 && b != 0 && c == 0))
{
if(a%2 == 0 && b%2 == 0 && c%2 == 0)
result = 2;
else
result = 1;
}
I'm assuming that you are looking for the length of the shortest possible string that can be obtained after reduction.
A simple solution would be to explore all possibilities in a greedy manner and hope that it does not explode exponentially. I'm gonna write Python pseudocode here because that's easier to comprehend (at least for me ;)):
from collections import deque
def try_reduce(string):
queue = deque([string])
min_length = len(string)
while queue:
string = queue.popleft()
if len(string) < min_length:
min_length = len(string)
for i in xrange(len(string)-1):
substring = string[i:(i+2)]
if substring == "AB" or substring == "BA":
queue.append(string[:i] + "C" + string[(i+2):])
elif substring == "BC" or substring == "CB":
queue.append(string[:i] + "A" + string[(i+2):])
elif substring == "AC" or substring == "CA":
queue.append(string[:i] + "B" + string[(i+2):])
return min_length
I think the basic idea is clear: you take a queue (std::deque should be just fine), add your string into it, and then implement a simple breadth first search in the space of all possible reductions. During the search, you take the first element from the queue, take all possible substrings of it, execute all possible reductions, and push the reduced strings back to the queue. The entire space is explored when the queue becomes empty.
Let's define an automaton with the following rules (K>=0):
Incoming: A B C
Current: --------------------------
<empty> A B C
A(2K+1) A(2K+2) AB AC
A(2K+2) A(2K+3) AAB AAC
AB CA CB ABC
AAB BA ACB BC
ABC CCA AAB AAC
and all rules obtained by permutations of ABC to get the complete definition.
All input strings using a single letter are irreducible. If the input string contains at least two different letters, the final states like AB or AAB can be reduced to a single letter, and the final states like ABC can be reduced to two letters.
In the ABC case, we still have to prove that the input string can't be reduced to a single letter by another reduction sequence.
Compare two characters at a time and replace if both adjacent characters are not same. To get optimal solution, run once from start of the string and once from end of the string. Return the minimum value.
int same(char* s){
int i=0;
for(i=0;i<strlen(s)-1;i++){
if(*(s+i) == *(s+i+1))
continue;
else
return 0;
}
return 1;
}
int reduceb(char* s){
int ret = 0,a_sum=0,i=0;
int len = strlen(s);
while(1){
i=len-1;
while(i>0){
if ((*(s+i)) == (*(s+i-1))){
i--;
continue;
} else {
a_sum = (*(s+i)) + (*(s+i-1));
*(s+i-1) = SUM - a_sum;
*(s+i) = '\0';
len--;
}
i--;
}
if(same(s) == 1){
return strlen(s);
}
}
}
int reducef(char* s){
int ret = 0,a_sum=0,i=0;
int len = strlen(s);
while(1){
i=0;
while(i<len-1){
if ((*(s+i)) == (*(s+i+1))){
i++;
continue;
} else {
a_sum = (*(s+i)) + (*(s+i+1));
*(s+i) = SUM - a_sum;
int j=i+1;
for(j=i+1;j<len;j++)
*(s+j) = *(s+j+1);
len--;
}
i++;
}
if(same(s) == 1){
return strlen(s);
}
}
}
int main(){
int n,i=0,f=0,b=0;
scanf("%d",&n);
int a[n];
while(i<n){
char* str = (char*)malloc(101);
scanf("%s",str);
char* strd = strdup(str);
f = reducef(str);
b = reduceb(strd);
if( f > b)
a[i] = b;
else
a[i] = f;
free(str);
free(strd);
i++;
}
for(i=0;i<n;i++)
printf("%d\n",a[i]);
}
import java.io.*;
import java.util.*;
class StringSim{
public static void main(String args[]){
Scanner sc = new Scanner(System.in);
StringTokenizer st = new StringTokenizer(sc.nextLine(), " ");
int N = Integer.parseInt(st.nextToken());
String op = "";
for(int i=0;i<N;i++){
String str = sc.nextLine();
op = op + Count(str) + "\n";
}
System.out.println(op);
}
public static int Count( String str){
int min = Integer.MAX_VALUE;
char pre = str.charAt(0);
boolean allSame = true;
//System.out.println("str :" + str);
if(str.length() == 1){
return 1;
}
int count = 1;
for(int i=1;i<str.length();i++){
//System.out.println("pre: -"+ pre +"- char at "+i+" is : -"+ str.charAt(i)+"-");
if(pre != str.charAt(i)){
allSame = false;
char rep = (char)(('a'+'b'+'c')-(pre+str.charAt(i)));
//System.out.println("rep :" + rep);
if(str.length() == 2)
count = 1;
else if(i==1)
count = Count(rep+str.substring(2,str.length()));
else if(i == str.length()-1)
count = Count(str.substring(0,str.length()-2)+rep);
else
count = Count(str.substring(0,i-1)+rep+str.substring(i+1,str.length()));
if(min>count) min=count;
}else if(allSame){
count++;
//System.out.println("count: " + count);
}
pre = str.charAt(i);
}
//System.out.println("min: " + min);
if(allSame) return count;
return min;
}
}
Wouldn't a good start be to count which letter you have the most of and look for ways to remove it? Keep doing this until we only have one letter. We might have it many times but as long as it is the same we do not care, we are finished.
To avoid getting something like ABCCCCCCC becoming CCCCCCCC.
We remove the most popular letter:
-ABCCCCCCC
-AACCCCCC
-ABCCCCC
-AACCCC
-ABCCC
-AACC
-ABC
-AA
I disagree with the previous poster who states we must have a length of 1 or 2 - what happens if I enter the start string AAA?
import java.util.LinkedList;
import java.util.List;
import java.util.Scanner;
public class Sample {
private static char[] res = {'a', 'b', 'c'};
private char replacementChar(char a, char b) {
for(char c : res) {
if(c != a && c != b) {
return c;
}
}
throw new IllegalStateException("cannot happen. you must've mucked up the resource");
}
public int processWord(String wordString) {
if(wordString.length() < 2) {
return wordString.length();
}
String wordStringES = reduceFromEnd(reduceFromStart(wordString));
if(wordStringES.length() == 1) {
return 1;
}
String wordStringSE = reduceFromStart(reduceFromEnd(wordString));
if(wordString.length() == 1) {
return 1;
}
int aLen;
if(isReduced(wordStringSE)) {
aLen = wordStringSE.length();
} else {
aLen = processWord(wordStringSE);
}
int bLen;
if(isReduced(wordStringES)) {
bLen = wordStringES.length();
} else {
bLen = processWord(wordStringES);
}
return Math.min(aLen, bLen);
}
private boolean isReduced(String wordString) {
int length = wordString.length();
if(length < 2) {
return true;
}
for(int i = 1; i < length; ++i) {
if(wordString.charAt(i) != wordString.charAt(i - 1)) {
return false;
}
}
return wordString.charAt(0) == wordString.charAt(length - 1);
}
private String reduceFromStart(String theWord) {
if(theWord.length() < 2) {
return theWord;
}
StringBuilder buffer = new StringBuilder();
char[] word = theWord.toCharArray();
char curChar = word[0];
for(int i = 1; i < word.length; ++i) {
if(word[i] != curChar) {
curChar = replacementChar(curChar, word[i]);
if(i + 1 == word.length) {
buffer.append(curChar);
break;
}
} else {
buffer.append(curChar);
if(i + 1 == word.length) {
buffer.append(curChar);
}
}
}
return buffer.toString();
}
private String reduceFromEnd(String theString) {
if(theString.length() < 2) {
return theString;
}
StringBuilder buffer = new StringBuilder(theString);
int length = buffer.length();
while(length > 1) {
char a = buffer.charAt(0);
char b = buffer.charAt(length - 1);
if(a != b) {
buffer.deleteCharAt(length - 1);
buffer.deleteCharAt(0);
buffer.append(replacementChar(a, b));
length -= 1;
} else {
break;
}
}
return buffer.toString();
}
public void go() {
Scanner scanner = new Scanner(System.in);
int numEntries = Integer.parseInt(scanner.nextLine());
List<Integer> counts = new LinkedList<Integer>();
for(int i = 0; i < numEntries; ++i) {
counts.add((processWord(scanner.nextLine())));
}
for(Integer count : counts) {
System.out.println(count);
}
}
public static void main(String[] args) {
Sample solution = new Sample();
solution.go();
}
}
This is greedy approach and traversing the path starts with each possible pair and checking the min length.
import java.io.*;
import java.util.*;
class StringSim{
public static void main(String args[]){
Scanner sc = new Scanner(System.in);
StringTokenizer st = new StringTokenizer(sc.nextLine(), " ");
int N = Integer.parseInt(st.nextToken());
String op = "";
for(int i=0;i<N;i++){
String str = sc.nextLine();
op = op + Count(str) + "\n";
}
System.out.println(op);
}
public static int Count( String str){
int min = Integer.MAX_VALUE;
char pre = str.charAt(0);
boolean allSame = true;
//System.out.println("str :" + str);
if(str.length() == 1){
return 1;
}
int count = 1;
for(int i=1;i<str.length();i++){
//System.out.println("pre: -"+ pre +"- char at "+i+" is : -"+ str.charAt(i)+"-");
if(pre != str.charAt(i)){
allSame = false;
char rep = (char)(('a'+'b'+'c')-(pre+str.charAt(i)));
//System.out.println("rep :" + rep);
if(str.length() == 2)
count = 1;
else if(i==1)
count = Count(rep+str.substring(2,str.length()));
else if(i == str.length()-1)
count = Count(str.substring(0,str.length()-2)+rep);
else
count = Count(str.substring(0,i-1)+rep+str.substring(i+1,str.length()));
if(min>count) min=count;
}else if(allSame){
count++;
//System.out.println("count: " + count);
}
pre = str.charAt(i);
}
//System.out.println("min: " + min);
if(allSame) return count;
return min;
}
}
Following NominSim's observations, here is probably an optimal solution that runs in linear time with O(1) space usage. Note that it is only capable of finding the length of the smallest reduction, not the reduced string itself:
def reduce(string):
a = string.count('a')
b = string.count('b')
c = string.count('c')
if ([a,b,c].count(0) >= 2):
return a+b+c
elif (all(v % 2 == 0 for v in [a,b,c]) or all(v % 2 == 1 for v in [a,b,c])):
return 2
else:
return 1
There is some underlying structure that can be used to solve this problem in O(n) time.
The rules given are (most of) the rules defining a mathematical group, in particular the group D_2 also sometimes known as K (for Klein's four group) or V (German for Viergruppe, four group). D_2 is a group with four elements, A, B, C, and 1 (the identity element). One of the realizations of D_2 is the set of symmetries of a rectangular box with three different sides. A, B, and C are 180 degree rotations about each of the axes, and 1 is the identity rotation (no rotation). The group table for D_2 is
|1 A B C
-+-------
1|1 A B C
A|A 1 C B
B|B C 1 A
C|C B A 1
As you can see, the rules correspond to the rules given in the problem, except that the rules involving 1 aren't present in the problem.
Since D_2 is a group, it satisfies a number of rules: closure (the product of any two elements of the group is another element), associativity (meaning (x*y)*z = x*(y*z) for any elements x, y, z; i.e., the order in which strings are reduced doesn't matter), existence of identity (there is an element 1 such that 1*x=x*1=x for any x), and existence of inverse (for any element x, there is an element x^{-1} such that x*x^{-1}=1 and x^{-1}*x=1; in our case, every element is its own inverse).
It's also worth noting that D_2 is commutative, i.e., x*y=y*x for any x,y.
Given any string of elements in D_2, we can reduce to a single element in the group in a greedy fashion. For example, ABCCCCCCC=CCCCCCCC=CCCCCC=CCCC=CC=1. Note that we don't write the element 1 unless it's the only element in the string. Associativity tells us that the order of the operations doesn't matter, e.g., we could have worked from right to left or started in the middle and gotten the same result. Let's try from the right: ABCCCCCCC=ABCCCCC=ABCCC=ABC=AA=1.
The situation of the problem is different because operations involving 1 are not allowed, so we can't just eliminate pairs AA, BB, or CC. However, the situation is not that different. Consider the string ABB. We can't write ABB=A in this case. However, we can eliminate BB in two steps using A: ABB=CB=A. Since order of operation doesn't matter by associativity, we're guaranteed to get the same result. So we can't go straight from ABB to A but we can get the same result by another route.
Such alternate routes are available whenever there are at least two different elements in a string. In particular, in each of ABB, ACC, BAA, BCC, CAA, CBB, AAB, AAC, BBA, BBC, CCA, CCB, we can act as if we have the reduction xx=1 and then drop the 1.
It follows that any string that is not homogeneous (not all the same letter) and has a double-letter substring (AA, BB, or CC) can be reduced by removing the double letter. Strings that contain just two identical letters can't be further reduced (because there is no 1 allowed in the problem), so it seems safe to hypothesize that any non-homogeneous string can be reduced to A, B, C, AA, BB, CC.
We still have to be careful, however, because CCAACC could be turned into CCCC by removing the middle pair AA, but that is not the best we can do: CCAACC=AACC=CC or AA takes us down to a string of length 2.
Another situation we have to be careful of is AABBBB. Here we could eliminate AA to end with BBBB, but it's better to eliminate the middle B's first, then whatever: AABBBB=AABB=AA or BB (both of which are equivalent to 1 in the group, but can't be further reduced in the problem).
There's another interesting situation we could have: AAAABBBB. Blindly eliminating pairs takes us to either AAAA or BBBB, but we could do better: AAAABBBB=AAACBBB=AABBBB=AABB=AA or BB.
The above indicate that eliminating doubles blindly is not necessarily the way to proceed, but nevertheless it was illuminating.
Instead, it seems as if the most important property of a string is non-homogeneity. If the string is homogeneous, stop, there's nothing we can do. Otherwise, identify an operation that preserves the non-homogeneity property if possible. I assert that it is always possible to identify an operation that preserves non-homogeneity if the string is non-homogeneous and of length four or greater.
Proof: if a 4-substring contains two different letters, a third letter can be introduced at a boundary between two different letters, e.g., AABA goes to ACA. Since one or the other of the original letters must be unchanged somewhere within the string, it follows that the result is still non-homogeneous.
Suppose instead we have a 4-substring that has three different elements, say AABC, with the outer two elements different. Then if the middle two elements are different, perform the operation on them; the result is non-homogeneous because the two outermost elements are still different. On the other hand, if the two inner elements are the same, e.g., ABBC, then they have to be different from both outermost elements (otherwise we'd only have two elements in the set of four, not three). In that case, perform either the first or third operation; that leaves either the last two elements different (e.g., ABBC=CBC) or the first two elements different (e.g., ABBC=ABA) so non-homogeneity is preserved.
Finally, consider the case where the first and last elements are the same. Then we have a situation like ABCA. The middle two elements both have to be different from the outer elements, otherwise we'd have only two elements in this case, not three. We can take the first available operation, ABCA=CCA, and non-homogeneity is preserved again.
End of proof.
We have a greedy algorithm to reduce any non-homogeneous string of length 4 or greater: pick the first operation that preserves non-homogeneity; such an operation must exist by the above argument.
We have now reduced to the case where we have a non-homogeneous string of 3 elements. If two are the same, we either have doubles like AAB etc., which we know can be reduced to a single element, or we have two elements with no double like ABA=AC=B which can also be reduced to a single element, or we have three different elements like ABC. There are six permutations, all of which =1 in the group by associativity and commutativity; all of them can be reduced to two elements by any operation; however, they can't possibly be reduced below a homogeneous pair (AA, BB, or CC) since 1 is not allowed in the problem, so we know that's the best we can do in this case.
In summary, if a string is homogeneous, there's nothing we can do; if a string is non-homogeneous and =A in the group, it can be reduced to A in the problem by a greedy algorithm which maintains non-homogeneity at each step; the same if the string =B or =C in the group; finally if a string is non-homogeneous and =1 in the group, it can be reduced by a greedy algorithm which maintains non-homogeneity as long as possible to one of AA, BB or CC. Those are the best we can do by the group properties of the operation.
Program solving the problem:
Now, since we know the possible outcomes, our program can run in O(n) time as follows: if all the letters in the given string are the same, no reduction is possible so just output the length of the string. If the string is non-homogeneous, and is equal to the identity in the group, output the number 2; otherwise output the number 1.
To quickly decide whether an element equals the identity in the group, we use commutativity and associativity as follows: just count the number of A's, B's and C's into the variables a, b, c. Replace a = a mod 2, b = b mod 2, c = c mod 2 because we can eliminate pairs AA, BB, and CC in the group. If none of the resulting a, b, c is equal to 0, we have ABC=1 in the group, so the program should output 2 because a reduction to the identity 1 is not possible. If all three of the resulting a, b, c are equal to 0, we again have the identity (A, B, and C all cancelled themselves out) so we should output 2. Otherwise the string is non-identity and we should output 1.
//C# Coding
using System;
using System.Collections.Generic;
namespace ConsoleApplication1
{
class Program
{
static void Main(string[] args)
{
/*
Keep all the rules in Dictionary object 'rules';
key - find string, value - replace with value
eg: find "AB" , replace with "AA"
*/
Dictionary<string, string> rules = new Dictionary<string, string>();
rules.Add("AB", "AA");
rules.Add("BA", "AA");
rules.Add("CB", "CC");
rules.Add("BC", "CC");
rules.Add("AA", "A");
rules.Add("CC", "C");
// example string
string str = "AABBCCCA";
//output
Console.WriteLine(fnRecurence(rules, str));
Console.Read();
}
//funcation for applying all the rules to the input string value recursivily
static string fnRecurence(Dictionary<string, string> rules,string str)
{
foreach (var rule in rules)
{
if (str.LastIndexOf(rule.Key) >= 0)
{
str = str.Replace(rule.Key, rule.Value);
}
}
if(str.Length >1)
{
int find = 0;
foreach (var rule in rules)
{
if (str.LastIndexOf(rule.Key) >= 0)
{
find = 1;
}
}
if(find == 1)
{
str = fnRecurence(rules, str);
}
else
{
//if not find any exit
find = 0;
str = str;
return str;
}
}
return str;
}
}
}
Here is my C# solution.
public static int StringReduction(string str)
{
if (str.Length == 1)
return 1;
else
{
int prevAns = str.Length;
int newAns = 0;
while (prevAns != newAns)
{
prevAns = newAns;
string ansStr = string.Empty;
int i = 1;
int j = 0;
while (i < str.Length)
{
if (str[i] != str[j])
{
if (str[i] != 'a' && str[j] != 'a')
{
ansStr += 'a';
}
else if (str[i] != 'b' && str[j] != 'b')
{
ansStr += 'b';
}
else if (str[i] != 'c' && str[j] != 'c')
{
ansStr += 'c';
}
i += 2;
j += 2;
}
else
{
ansStr += str[j];
i++;
j++;
}
}
if (j < str.Length)
{
ansStr += str[j];
}
str = ansStr;
newAns = ansStr.Length;
}
return newAns;
}
}
Compare two characters at a time and replace if both adjacent characters are not same. To get optimal solution, run once from start of the string and once from end of the string. Return the minimum value.
Rav solution is :-
int same(char* s){
int i=0;
for(i=0;i<strlen(s)-1;i++){
if(*(s+i) == *(s+i+1))
continue;
else
return 0;
}
return 1;
}
int reduceb(char* s){
int ret = 0,a_sum=0,i=0;
int len = strlen(s);
while(1){
i=len-1;
while(i>0){
if ((*(s+i)) == (*(s+i-1))){
i--;
continue;
} else {
a_sum = (*(s+i)) + (*(s+i-1));
*(s+i-1) = SUM - a_sum;
*(s+i) = '\0';
len--;
}
i--;
}
if(same(s) == 1){
return strlen(s);
}
}
}
int reducef(char* s){
int ret = 0,a_sum=0,i=0;
int len = strlen(s);
while(1){
i=0;
while(i<len-1){
if ((*(s+i)) == (*(s+i+1))){
i++;
continue;
} else {
a_sum = (*(s+i)) + (*(s+i+1));
*(s+i) = SUM - a_sum;
int j=i+1;
for(j=i+1;j<len;j++)
*(s+j) = *(s+j+1);
len--;
}
i++;
}
if(same(s) == 1){
return strlen(s);
}
}
}
int main(){
int n,i=0,f=0,b=0;
scanf("%d",&n);
int a[n];
while(i<n){
char* str = (char*)malloc(101);
scanf("%s",str);
char* strd = strdup(str);
f = reducef(str);
b = reduceb(strd);
if( f > b)
a[i] = b;
else
a[i] = f;
free(str);
free(strd);
i++;
}
for(i=0;i<n;i++)
printf("%d\n",a[i]);
}
#Rav
this code will fail for input "abccaccba".
solution should be only "b"
but this code wont give that. Since i am not getting correct comment place(due to low points or any other reason) so i did it here.
This problem can be solved by greedy approach. Try to find the best position to apply transformation until no transformation exists. The best position is the position with max number of distinct neighbors of the transformed character.
You can solve this using 2 pass.
In the first pass you apply
len = strlen (str) ;
index = 0 ;
flag = 0 ;
/* 1st pass */
for ( i = len-1 ; i > 0 ; i -- ) {
if ( str[i] != str[i-1] ) {
str[i-1] = getChar (str[i], str[i-1]) ;
if (i == 1) {
output1[index++] = str[i-1] ;
flag = 1 ;
break ;
}
}
else output1[index++] = str[i] ;
}
if ( flag == 0 )
output1[index++] = str[i] ;
output1[index] = '\0';
And in the 2nd pass you will apply the same on 'output1' to get the result.
So, One is forward pass another one is backward pass.
int previous = a.charAt(0);
boolean same = true;
int c = 0;
for(int i = 0; i < a.length();++i){
c ^= a.charAt(i)-'a'+1;
if(a.charAt(i) != previous) same = false;
}
if(same) return a.length();
if(c==0) return 2;
else return 1;
import java.util.Scanner;
public class StringReduction {
public static void main(String[] args) {
Scanner sc = new Scanner(System.in);
String str = sc.nextLine();
int length = str.length();
String result = stringReduction(str);
System.out.println(result);
}
private static String stringReduction(String str) {
String result = str.substring(0);
if(str.length()<2){
return str;
}
if(str.length() == 2){
return combine(str.charAt(0),str.charAt(1));
}
for(int i =1;i<str.length();i++){
if(str.charAt(i-1) != str.charAt(i)){
String temp = str.substring(0, i-1) + combine(str.charAt(i-1),str.charAt(i)) + str.substring(i+1, str.length());
String sub = stringReduction(temp);
if(sub.length() < result.length()){
result = sub;
}
}
}
return result;
}
private static String combine(char c1, char c2) {
if(c1 == c2){
return "" + c1 + c2;
}
else{
if(c1 == 'a'){
if(c2 == 'b'){
return "" + 'c';
}
if(c2 == 'c') {
return "" + 'b';
}
}
if(c1 == 'b'){
if(c2 == 'a'){
return "" + 'c';
}
if(c2 == 'c') {
return "" + 'a';
}
}
if(c1 == 'c'){
if(c2 == 'a'){
return "" + 'b';
}
if(c2 == 'b') {
return "" + 'a';
}
}
return null;
}
}
}
JAVASCRIPT SOLUTION:
function StringChallenge(str) {
// code goes here
if(str.length == 1) {
return 1;
} else {
let prevAns = str.length;
let newAns = 0;
while(prevAns != newAns) {
prevAns = newAns;
let ansStr = "";
let i = 1;
let j = 0;
while(i < str.length) {
if(str[i] !== str[j]) {
if(str[i] != 'a' && str[j] != 'a') {
ansStr += 'a';
} else if(str[i] != 'b' && str[j] !='b') {
ansStr +='b';
} else if(str[i] != 'c' && str[j] != 'c') {
ansStr += 'c';
}
i += 2;
j += 2;
} else {
ansStr += str[j];
j++;
i++;
}
}
if(j < str.length) {
ansStr += str[j];
}
str = ansStr;
newAns = ansStr.length;
}
return newAns;
}
}
Project Euler problem 14:
The following iterative sequence is
defined for the set of positive
integers:
n → n/2 (n is even) n → 3n + 1 (n is
odd)
Using the rule above and starting with
13, we generate the following
sequence: 13 → 40 → 20 → 10 → 5 → 16 →
8 → 4 → 2 → 1
It can be seen that this sequence
(starting at 13 and finishing at 1)
contains 10 terms. Although it has not
been proved yet (Collatz Problem), it
is thought that all starting numbers
finish at 1.
Which starting number, under one
million, produces the longest chain?
My first instinct is to create a function to calculate the chains, and run it with every number between 1 and 1 million. Obviously, that takes a long time. Way longer than solving this should take, according to Project Euler's "About" page. I've found several problems on Project Euler that involve large groups of numbers that a program running for hours didn't finish. Clearly, I'm doing something wrong.
How can I handle large groups of numbers quickly?
What am I missing here?
Have a read about memoization. The key insight is that if you've got a sequence starting A that has length 1001, and then you get a sequence B that produces an A, you don't to repeat all that work again.
This is the code in Mathematica, using memoization and recursion. Just four lines :)
f[x_] := f[x] = If[x == 1, 1, 1 + f[If[EvenQ[x], x/2, (3 x + 1)]]];
Block[{$RecursionLimit = 1000, a = 0, j},
Do[If[a < f[i], a = f[i]; j = i], {i, Reverse#Range#10^6}];
Print#a; Print[j];
]
Output .... chain length´525´ and the number is ... ohhhh ... font too small ! :)
BTW, here you can see a plot of the frequency for each chain length
Starting with 1,000,000, generate the chain. Keep track of each number that was generated in the chain, as you know for sure that their chain is smaller than the chain for the starting number. Once you reach 1, store the starting number along with its chain length. Take the next biggest number that has not being generated before, and repeat the process.
This will give you the list of numbers and chain length. Take the greatest chain length, and that's your answer.
I'll make some code to clarify.
public static long nextInChain(long n) {
if (n==1) return 1;
if (n%2==0) {
return n/2;
} else {
return (3 * n) + 1;
}
}
public static void main(String[] args) {
long iniTime=System.currentTimeMillis();
HashSet<Long> numbers=new HashSet<Long>();
HashMap<Long,Long> lenghts=new HashMap<Long, Long>();
long currentTry=1000000l;
int i=0;
do {
doTry(currentTry,numbers, lenghts);
currentTry=findNext(currentTry,numbers);
i++;
} while (currentTry!=0);
Set<Long> longs = lenghts.keySet();
long max=0;
long key=0;
for (Long aLong : longs) {
if (max < lenghts.get(aLong)) {
key = aLong;
max = lenghts.get(aLong);
}
}
System.out.println("number = " + key);
System.out.println("chain lenght = " + max);
System.out.println("Elapsed = " + ((System.currentTimeMillis()-iniTime)/1000));
}
private static long findNext(long currentTry, HashSet<Long> numbers) {
for(currentTry=currentTry-1;currentTry>=0;currentTry--) {
if (!numbers.contains(currentTry)) return currentTry;
}
return 0;
}
private static void doTry(Long tryNumber,HashSet<Long> numbers, HashMap<Long, Long> lenghts) {
long i=1;
long n=tryNumber;
do {
numbers.add(n);
n=nextInChain(n);
i++;
} while (n!=1);
lenghts.put(tryNumber,i);
}
Suppose you have a function CalcDistance(i) that calculates the "distance" to 1. For instance, CalcDistance(1) == 0 and CalcDistance(13) == 9. Here is a naive recursive implementation of this function (in C#):
public static int CalcDistance(long i)
{
if (i == 1)
return 0;
return (i % 2 == 0) ? CalcDistance(i / 2) + 1 : CalcDistance(3 * i + 1) + 1;
}
The problem is that this function has to calculate the distance of many numbers over and over again. You can make it a little bit smarter (and a lot faster) by giving it a memory. For instance, lets create a static array that can store the distance for the first million numbers:
static int[] list = new int[1000000];
We prefill each value in the list with -1 to indicate that the value for that position is not yet calculated. After this, we can optimize the CalcDistance() function:
public static int CalcDistance(long i)
{
if (i == 1)
return 0;
if (i >= 1000000)
return (i % 2 == 0) ? CalcDistance(i / 2) + 1 : CalcDistance(3 * i + 1) + 1;
if (list[i] == -1)
list[i] = (i % 2 == 0) ? CalcDistance(i / 2) + 1: CalcDistance(3 * i + 1) + 1;
return list[i];
}
If i >= 1000000, then we cannot use our list, so we must always calculate it. If i < 1000000, then we check if the value is in the list. If not, we calculate it first and store it in the list. Otherwise we just return the value from the list. With this code, it took about ~120ms to process all million numbers.
This is a very simple example of memoization. I use a simple list to store intermediate values in this example. You can use more advanced data structures like hashtables, vectors or graphs when appropriate.
Minimize how many levels deep your loops are, and use an efficient data structure such as IList or IDictionary, that can auto-resize itself when it needs to expand. If you use plain arrays they need to be copied to larger arrays as they expand - not nearly as efficient.
This variant doesn't use an HashMap but tries only to not repeat the first 1000000 numbers. I don't use an hashmap because the biggest number found is around 56 billions, and an hash map could crash.
I have already done some premature optimization. Instead of / I use >>, instead of % I use &. Instead of * I use some +.
void Main()
{
var elements = new bool[1000000];
int longestStart = -1;
int longestRun = -1;
long biggest = 0;
for (int i = elements.Length - 1; i >= 1; i--) {
if (elements[i]) {
continue;
}
elements[i] = true;
int currentStart = i;
int currentRun = 1;
long current = i;
while (current != 1) {
if (current > biggest) {
biggest = current;
}
if ((current & 1) == 0) {
current = current >> 1;
} else {
current = current + current + current + 1;
}
currentRun++;
if (current < elements.Length) {
elements[current] = true;
}
}
if (currentRun > longestRun) {
longestStart = i;
longestRun = currentRun;
}
}
Console.WriteLine("Longest Start: {0}, Run {1}", longestStart, longestRun);
Console.WriteLine("Biggest number: {0}", biggest);
}
Are there any examples for a recursive function that calls an other function which calls the first one too ?
Example :
function1()
{
//do something
function2();
//do something
}
function2()
{
//do something
function1();
//do something
}
Mutual recursion is common in code that parses mathematical expressions (and other grammars). A recursive descent parser based on the grammar below will naturally contain mutual recursion: expression-terms-term-factor-primary-expression.
expression
+ terms
- terms
terms
terms
term + terms
term - terms
term
factor
factor * term
factor / term
factor
primary
primary ^ factor
primary
( expression )
number
name
name ( expression )
The proper term for this is Mutual Recursion.
http://en.wikipedia.org/wiki/Mutual_recursion
There's an example on that page, I'll reproduce here in Java:
boolean even( int number )
{
if( number == 0 )
return true;
else
return odd(abs(number)-1)
}
boolean odd( int number )
{
if( number == 0 )
return false;
else
return even(abs(number)-1);
}
Where abs( n ) means return the absolute value of a number.
Clearly this is not efficient, just to demonstrate a point.
An example might be the minmax algorithm commonly used in game programs such as chess. Starting at the top of the game tree, the goal is to find the maximum value of all the nodes at the level below, whose values are defined as the minimum of the values of the nodes below that, whose values are defines as the maximum of the values below that, whose values ...
I can think of two common sources of mutual recursion.
Functions dealing with mutually recursive types
Consider an Abstract Syntax Tree (AST) that keeps position information in every node. The type might look like this:
type Expr =
| Int of int
| Var of string
| Add of ExprAux * ExprAux
and ExprAux = Expr of int * Expr
The easiest way to write functions that manipulate values of these types is to write mutually recursive functions. For example, a function to find the set of free variables:
let rec freeVariables = function
| Int n -> Set.empty
| Var x -> Set.singleton x
| Add(f, g) -> Set.union (freeVariablesAux f) (freeVariablesAux g)
and freeVariablesAux (Expr(loc, e)) =
freeVariables e
State machines
Consider a state machine that is either on, off or paused with instructions to start, stop, pause and resume (F# code):
type Instruction = Start | Stop | Pause | Resume
The state machine might be written as mutually recursive functions with one function for each state:
type State = State of (Instruction -> State)
let rec isOff = function
| Start -> State isOn
| _ -> State isOff
and isOn = function
| Stop -> State isOff
| Pause -> State isPaused
| _ -> State isOn
and isPaused = function
| Stop -> State isOff
| Resume -> State isOn
| _ -> State isPaused
It's a bit contrived and not very efficient, but you could do this with a function to calculate Fibbonacci numbers as in:
fib2(n) { return fib(n-2); }
fib1(n) { return fib(n-1); }
fib(n)
{
if (n>1)
return fib1(n) + fib2(n);
else
return 1;
}
In this case its efficiency can be dramatically enhanced if the language supports memoization
In a language with proper tail calls, Mutual Tail Recursion is a very natural way of implementing automata.
Here is my coded solution. For a calculator app that performs *,/,- operations using mutual recursion. It also checks for brackets (()) to decide the order of precedence.
Flow:: expression -> term -> factor -> expression
Calculator.h
#ifndef CALCULATOR_H_
#define CALCULATOR_H_
#include <string>
using namespace std;
/****** A Calculator Class holding expression, term, factor ********/
class Calculator
{
public:
/**Default Constructor*/
Calculator();
/** Parameterized Constructor common for all exception
* #aparam e exception value
* */
Calculator(char e);
/**
* Function to start computation
* #param input - input expression*/
void start(string input);
/**
* Evaluates Term*
* #param input string for term*/
double term(string& input);
/* Evaluates factor*
* #param input string for factor*/
double factor(string& input);
/* Evaluates Expression*
* #param input string for expression*/
double expression(string& input);
/* Evaluates number*
* #param input string for number*/
string number(string n);
/**
* Prints calculates value of the expression
* */
void print();
/**
* Converts char to double
* #param c input char
* */
double charTONum(const char* c);
/**
* Get error
*/
char get_value() const;
/** Reset all values*/
void reset();
private:
int lock;//set lock to check extra parenthesis
double result;// result
char error_msg;// error message
};
/**Error for unexpected string operation*/
class Unexpected_error:public Calculator
{
public:
Unexpected_error(char e):Calculator(e){};
};
/**Error for missing parenthesis*/
class Missing_parenthesis:public Calculator
{
public:
Missing_parenthesis(char e):Calculator(e){};
};
/**Error if divide by zeros*/
class DivideByZero:public Calculator{
public:
DivideByZero():Calculator(){};
};
#endif
===============================================================================
Calculator.cpp
//============================================================================
// Name : Calculator.cpp
// Author : Anurag
// Version :
// Copyright : Your copyright notice
// Description : Calculator using mutual recursion in C++, Ansi-style
//============================================================================
#include "Calculator.h"
#include <iostream>
#include <string>
#include <math.h>
#include <exception>
using namespace std;
Calculator::Calculator():lock(0),result(0),error_msg(' '){
}
Calculator::Calculator(char e):result(0), error_msg(e) {
}
char Calculator::get_value() const {
return this->error_msg;
}
void Calculator::start(string input) {
try{
result = expression(input);
print();
}catch (Unexpected_error e) {
cout<<result<<endl;
cout<<"***** Unexpected "<<e.get_value()<<endl;
}catch (Missing_parenthesis e) {
cout<<"***** Missing "<<e.get_value()<<endl;
}catch (DivideByZero e) {
cout<<"***** Division By Zero" << endl;
}
}
double Calculator::expression(string& input) {
double expression=0;
if(input.size()==0)
return 0;
expression = term(input);
if(input[0] == ' ')
input = input.substr(1);
if(input[0] == '+') {
input = input.substr(1);
expression += term(input);
}
else if(input[0] == '-') {
input = input.substr(1);
expression -= term(input);
}
if(input[0] == '%'){
result = expression;
throw Unexpected_error(input[0]);
}
if(input[0]==')' && lock<=0 )
throw Missing_parenthesis(')');
return expression;
}
double Calculator::term(string& input) {
if(input.size()==0)
return 1;
double term=1;
term = factor(input);
if(input[0] == ' ')
input = input.substr(1);
if(input[0] == '*') {
input = input.substr(1);
term = term * factor(input);
}
else if(input[0] == '/') {
input = input.substr(1);
double den = factor(input);
if(den==0) {
throw DivideByZero();
}
term = term / den;
}
return term;
}
double Calculator::factor(string& input) {
double factor=0;
if(input[0] == ' ') {
input = input.substr(1);
}
if(input[0] == '(') {
lock++;
input = input.substr(1);
factor = expression(input);
if(input[0]==')') {
lock--;
input = input.substr(1);
return factor;
}else{
throw Missing_parenthesis(')');
}
}
else if (input[0]>='0' && input[0]<='9'){
string nums = input.substr(0,1) + number(input.substr(1));
input = input.substr(nums.size());
return stod(nums);
}
else {
result = factor;
throw Unexpected_error(input[0]);
}
return factor;
}
string Calculator::number(string input) {
if(input.substr(0,2)=="E+" || input.substr(0,2)=="E-" || input.substr(0,2)=="e-" || input.substr(0,2)=="e-")
return input.substr(0,2) + number(input.substr(2));
else if((input[0]>='0' && input[0]<='9') || (input[0]=='.'))
return input.substr(0,1) + number(input.substr(1));
else
return "";
}
void Calculator::print() {
cout << result << endl;
}
void Calculator::reset(){
this->lock=0;
this->result=0;
}
int main() {
Calculator* cal = new Calculator;
string input;
cout<<"Expression? ";
getline(cin,input);
while(input!="."){
cal->start(input.substr(0,input.size()-2));
cout<<"Expression? ";
cal->reset();
getline(cin,input);
}
cout << "Done!" << endl;
return 0;
}
==============================================================
Sample input-> Expression? (42+8)*10 =
Output-> 500
Top down merge sort can use a pair of mutually recursive functions to alternate the direction of merge based on level of recursion.
For the example code below, a[] is the array to be sorted, b[] is a temporary working array. For a naive implementation of merge sort, each merge operation copies data from a[] to b[], then merges b[] back to a[], or it merges from a[] to b[], then copies from b[] back to a[]. This requires n · ceiling(log2(n)) copy operations. To eliminate the copy operations used for merging, the direction of merge can be alternated based on level of recursion, merge from a[] to b[], merge from b[] to a[], ..., and switch to in place insertion sort for small runs in a[], as insertion sort on small runs is faster than merge sort.
In this example, MergeSortAtoA() and MergeSortAtoB() are the mutually recursive functions.
Example java code:
static final int ISZ = 64; // use insertion sort if size <= ISZ
static void MergeSort(int a[])
{
int n = a.length;
if(n < 2)
return;
int [] b = new int[n];
MergeSortAtoA(a, b, 0, n);
}
static void MergeSortAtoA(int a[], int b[], int ll, int ee)
{
if ((ee - ll) <= ISZ){ // use insertion sort on small runs
InsertionSort(a, ll, ee);
return;
}
int rr = (ll + ee)>>1; // midpoint, start of right half
MergeSortAtoB(a, b, ll, rr);
MergeSortAtoB(a, b, rr, ee);
Merge(b, a, ll, rr, ee); // merge b to a
}
static void MergeSortAtoB(int a[], int b[], int ll, int ee)
{
int rr = (ll + ee)>>1; // midpoint, start of right half
MergeSortAtoA(a, b, ll, rr);
MergeSortAtoA(a, b, rr, ee);
Merge(a, b, ll, rr, ee); // merge a to b
}
static void Merge(int a[], int b[], int ll, int rr, int ee)
{
int o = ll; // b[] index
int l = ll; // a[] left index
int r = rr; // a[] right index
while(true){ // merge data
if(a[l] <= a[r]){ // if a[l] <= a[r]
b[o++] = a[l++]; // copy a[l]
if(l < rr) // if not end of left run
continue; // continue (back to while)
while(r < ee){ // else copy rest of right run
b[o++] = a[r++];
}
break; // and return
} else { // else a[l] > a[r]
b[o++] = a[r++]; // copy a[r]
if(r < ee) // if not end of right run
continue; // continue (back to while)
while(l < rr){ // else copy rest of left run
b[o++] = a[l++];
}
break; // and return
}
}
}
static void InsertionSort(int a[], int ll, int ee)
{
int i, j;
int t;
for (j = ll + 1; j < ee; j++) {
t = a[j];
i = j-1;
while(i >= ll && a[i] > t){
a[i+1] = a[i];
i--;
}
a[i+1] = t;
}
}
----------Updated ------------
codymanix and moonshadow have been a big help thus far. I was able to solve my problem using the equations and instead of using right shift I divided by 29. Because with 32bits signed 2^31 = overflows to 29. Which works!
Prototype in PHP
$r = $x - (($x - $y) & (($x - $y) / (29)));
Actual code for LEADS (you can only do one math function PER LINE!!! AHHHH!!!)
DERIVDE1 = IMAGE1 - IMAGE2;
DERIVED2 = DERIVED1 / 29;
DERIVED3 = DERIVED1 AND DERIVED2;
MAX = IMAGE1 - DERIVED3;
----------Original Question-----------
I don't think this is quite possible with my application's limitations but I figured it's worth a shot to ask.
I'll try to make this simple. I need to find the max values between two numbers without being able to use a IF or any conditional statement.
In order to find the the MAX values I can only perform the following functions
Divide, Multiply, Subtract, Add, NOT, AND ,OR
Let's say I have two numbers
A = 60;
B = 50;
Now if A is always greater than B it would be simple to find the max value
MAX = (A - B) + B;
ex.
10 = (60 - 50)
10 + 50 = 60 = MAX
Problem is A is not always greater than B. I cannot perform ABS, MAX, MIN or conditional checks with the scripting applicaiton I am using.
Is there any way possible using the limited operation above to find a value VERY close to the max?
finding the maximum of 2 variables:
max = a-((a-b)&((a-b)>>31))
where >> is bitwise right-shift (also called SHR or ASR depeding on signedness).
Instead of 31 you use the number of bits your numbers have minus one.
I guess this one would be the most simplest if we manage to find difference between two numbers (only the magnitude not sign)
max = ((a+b)+|a-b|)/2;
where |a-b| is a magnitude of difference between a and b.
If you can't trust your environment to generate the appropriate branchless operations when they are available, see this page for how to proceed. Note the restriction on input range; use a larger integer type for the operation if you cannot guarantee your inputs will fit.
Solution without conditionals. Cast to uint then back to int to get abs.
int abs (a) { return (int)((unsigned int)a); }
int max (a, b) { return (a + b + abs(a - b)) / 2; }
int max3 (a, b, c) { return (max(max(a,b),c); }
Using logical operations only, short circuit evaluation and assuming the C convention of rounding towards zero, it is possible to express this as:
int lt0(int x) {
return x && (!!((x-1)/x));
}
int mymax(int a, int b) {
return lt0(a-b)*b+lt0(b-a)*a;
}
The basic idea is to implement a comparison operator that will return 0 or 1. It's possible to do a similar trick if your scripting language follows the convention of rounding toward the floor value like python does.
function Min(x,y:integer):integer;
Var
d:integer;
abs:integer;
begin
d:=x-y;
abs:=d*(1-2*((3*d) div (3*d+1)));
Result:=(x+y-abs) div 2;
end;
Hmmm. I assume NOT, AND, and OR are bitwise? If so, there's going to be a bitwise expression to solve this. Note that A | B will give a number >= A and >= B. Perhaps there's a pruning method for selecting the number with the most bits.
To extend, we need the following to determine whether A (0) or B (1) is greater.
truth table:
0|0 = 0
0|1 = 1
1|0 = 0
1|1 = 0
!A and B
therefore, will give the index of the greater bit. Ergo, compare each bit in both numbers, and when they are different, use the above expression (Not A And B) to determine which number was greater. Start from the most significant bit and proceed down both bytes. If you have no looping construct, manually compare each bit.
Implementing "when they are different":
(A != B) AND (my logic here)
try this, (but be aware for overflows)
(Code in C#)
public static Int32 Maximum(params Int32[] values)
{
Int32 retVal = Int32.MinValue;
foreach (Int32 i in values)
retVal += (((i - retVal) >> 31) & (i - retVal));
return retVal;
}
You can express this as a series of arithmetic and bitwise operations, e.g.:
int myabs(const int& in) {
const int tmp = in >> ((sizeof(int) * CHAR_BIT) - 1);
return tmp - (in ^ tmp(;
}
int mymax(int a, int b) {
return ((a+b) + myabs(b-a)) / 2;
}
//Assuming 32 bit integers
int is_diff_positive(int num)
{
((num & 0x80000000) >> 31) ^ 1; // if diff positive ret 1 else 0
}
int sign(int x)
{
return ((num & 0x80000000) >> 31);
}
int flip(int x)
{
return x ^ 1;
}
int max(int a, int b)
{
int diff = a - b;
int is_pos_a = sign(a);
int is_pos_b = sign(b);
int is_diff_positive = diff_positive(diff);
int is_diff_neg = flip(is_diff_positive);
// diff (a - b) will overflow / underflow if signs are opposite
// ex: a = INT_MAX , b = -3 then a - b => INT_MAX - (-3) => INT_MAX + 3
int can_overflow = is_pos_a ^ is_pos_b;
int cannot_overflow = flip(can_overflow);
int res = (cannot_overflow * ( (a * is_diff_positive) + (b *
is_diff_negative)) + (can_overflow * ( (a * is_pos_a) + (b *
is_pos_b)));
return res;
}
This is my implementation using only +, -, *, %, / operators
using static System.Console;
int Max(int a, int b) => (a + b + Abs(a - b)) / 2;
int Abs(int x) => x * ((2 * x + 1) % 2);
WriteLine(Max(-100, -2) == -2); // true
WriteLine(Max(2, -100) == 2); // true
I just came up with an expression:
(( (a-b)-|a-b| ) / (2(a-b)) )*b + (( (b-a)-|b-a| )/(2(b-a)) )*a
which is equal to a if a>b and is equal to b if b>a
when a>b:
a-b>0, a-b = |a-b|, (a-b)-|a-b| = 0 so the coeficcient for b is 0
b-a<0, b-a = -|b-a|, (b-a)-|b-a| = 2(b-a)
so the coeficcient for a is 2(b-a)/2(b-a) which is 1
so it would ultimately return 0*b+1*a if a is bigger and vice versa
Find MAX between n & m
MAX = ( (n/2) + (m/2) + ( ((n/2) - (m/2)) * ( (2*((n/2) - (m/2)) + 1) % 2) ) )
Using #define in c:
#define MAX(n, m) ( (n/2) + (m/2) + ( ((n/2) - (m/2)) * ( (2*((n/2) - (m/2)) + 1) % 2) ) )
or
#define ABS(n) ( n * ( (2*n + 1) % 2) ) // Calculates abs value of n
#define MAX(n, m) ( (n/2) + (m/2) + ABS((n/2) - (m/2)) ) // Finds max between n & m
#define MIN(n, m) ( (n/2) + (m/2) - ABS((n/2) - (m/2)) ) // Finds min between n & m
please look at this program.. this might be the best answer till date on this page...
#include <stdio.h>
int main()
{
int a,b;
a=3;
b=5;
printf("%d %d\n",a,b);
b = (a+b)-(a=b); // this line is doing the reversal
printf("%d %d\n",a,b);
return 0;
}
If A is always greater than B .. [ we can use] .. MAX = (A - B) + B;
No need. Just use: int maxA(int A, int B){ return A;}
(1) If conditionals are allowed you do max = a>b ? a : b.
(2) Any other method either use a defined set of numbers or rely on the implicit conditional checks.
(2a) max = a-((a-b)&((a-b)>>31)) this is neat, but it only works if you use 32 bit numbers. You can expand it arbitrary large number N, but the method will fail if you try to find max(N-1, N+1). This algorithm works for finite state automata, but not a Turing machine.
(2b) Magnitude |a-b| is a condition |a-b| = a-b>0 a-b : b-a
What about:
Square root is also a condition. Whenever c>0 and c^2 = d we have second solution -c, because (-c)^2 = (-1)^2*c^2 = 1*c^2 = d. Square root returns the greatest in the pair. I comes with a build in int max(int c1, int c2){return max(c1, c2);}
Without comparison operator math is very symmetric as well as limited in power. Positive and negative numbers cannot be distinguished without if of some sort.
It depends which language you're using, but the Ternary Operator might be useful.
But then, if you can't perform conditional checks in your 'scripting application', you probably don't have the ternary operator.
using System;
namespace ConsoleApp2
{
class Program
{
static void Main(string[] args)
{
float a = 101, b = 15;
float max = (a + b) / 2 + ((a > b) ? a - b : b - a) / 2;
}
}
}
#region GetMaximumNumber
/// <summary>
/// Provides method to get maximum values.
/// </summary>
/// <param name="values">Integer array for getting maximum values.</param>
/// <returns>Maximum number from an array.</returns>
private int GetMaximumNumber(params int[] values)
{
// Declare to store the maximum number.
int maximumNumber = 0;
try
{
// Check that array is not null and array has an elements.
if (values != null &&
values.Length > 0)
{
// Sort the array in ascending order for getting maximum value.
Array.Sort(values);
// Get the last value from an array which is always maximum.
maximumNumber = values[values.Length - 1];
}
}
catch (Exception ex)
{
throw ex;
}
return maximumNumber;
}
#endregion