Find the index of a given permutation in the sorted list of the permutations of a given string - algorithm

We're given a string and a permutation of the string.
For example, an input string sandeep and a permutation psdenae.
Find the position of the given permutation in the sorted list of the permutations of the original string.

The total number of permutation of a given string of length n would be n! (if all characters are different), thus it would not be possible to explore all the combinations.
This question is actually like the mathematics P & C question
Find the rank of the word "stack" when arranged in dictionary order.
Given the input string as NILSU
Take a word which we have to find the rank. Take "SUNIL" for example.
Now arrange the letter of "SUNIL" in alphabetical order.
It will be. "I L N S U".
Now take the first letter. Its "I". Now check, is the letter "I" the
first letter of "SUNIL"? No. The number of words that can be formed
starting with I will be 4!, so we know that there will be 4! words
before "SUNIL".
I = 4! = 24
Now go for the second letter. Its "L". Now check once again if this
letter we want in first position? No. So the number of words can be
formed starting with "L" will be 4!.
L = 4! = 24
Now go for "N". Is this we want? No. Write down the number of words
can be formed starting with "N", once again 4!
N = 4! = 24
Now go for "S". Is this what we want? Yes. Now remove the letter from
the alphabetically ordered word. It will now be "I L N U"
Write S and check the word once again in the list. Is we want SI? No.
So the number of words can be formed starting with SI will be 3!
[S]:I-> 3! = 6
Go for L. is we want SL? No. So it will be 3!.
[S]:L-> 3! = 6
Go for N. is we want SN? No.
[S]:N-> 3! = 6
Go for SU. Is this we want? Yes. Cut the letter U from the list and
then it will be "I L N". Now try I. is we want SUI? No. So the number
of words can be formed which starts from SUI will be 2!
[SU]:I-> 2! = 2 Now go for L. Do we want "SUL". No. so the number of
words starting with SUL will be 2!.
[SU]:L-> 2! = 2
Now go for N. Is we want SUN? Yes, now remove that letter. and this
will be "I L". Do we want "SUNI"? Yes. Remove that letter. The only
letter left is "L".
Now go for L. Do we want SUNIL? Yes. SUNIL were the first options, so
we have 1!. [SUN][I][L] = 1! = 1
Now add the whole numbers we get. The sum will be.
24 + 24 + 24 + 6 + 6 + 6 + 2 + 2 + 1 = 95.
So the word SUNIL will be at 95th position if we count the words that can be created using the letters of SUNIL arranged in dictionary order.
Thus through this method you could solve this problem quite easily.

Building off #Algorithmist 's answer, and his comment to his answer, and using the principle discussed in this post for when there are repeated letters, I made the following algorithm in JavaScript that works for all letter-based words even with repeated letter instances.
function anagramPosition(string) {
var index = 1;
var remainingLetters = string.length - 1;
var frequencies = {};
var splitString = string.split("");
var sortedStringLetters = string.split("").sort();
sortedStringLetters.forEach(function(val, i) {
if (!frequencies[val]) {
frequencies[val] = 1;
} else {
frequencies[val]++;
}
})
function factorial(coefficient) {
var temp = coefficient;
var permutations = coefficient;
while (temp-- > 2) {
permutations *= temp;
}
return permutations;
}
function getSubPermutations(object, currentLetter) {
object[currentLetter]--;
var denominator = 1;
for (var key in object) {
var subPermutations = factorial(object[key]);
subPermutations !== 0 ? denominator *= subPermutations : null;
}
object[currentLetter]++;
return denominator;
}
var splitStringIndex = 0;
while (sortedStringLetters.length) {
for (var i = 0; i < sortedStringLetters.length; i++) {
if (sortedStringLetters[i] !== splitString[splitStringIndex]) {
if (sortedStringLetters[i] !== sortedStringLetters[i+1]) {
var permutations = factorial(remainingLetters);
index += permutations / getSubPermutations(frequencies, sortedStringLetters[i]);
} else {
continue;
}
} else {
splitStringIndex++;
frequencies[sortedStringLetters[i]]--;
sortedStringLetters.splice(i, 1);
remainingLetters--;
break;
}
}
}
return index;
}
anagramPosition("ARCTIC") // => 42
I didn't comment the code but I did try to make the variable names as explanatory as possible. If you run it through a debugger process using your dev tools console and throw in a few console.logs you should be able to see how it uses the formula in the above-linked S.O. post.

I tried to implement this in js. It works for string that have no repeated letters but I get a wrong count otherwise. Here is my code:
function x(str) {
var sOrdinata = str.split('').sort()
console.log('sOrdinata = '+ sOrdinata)
var str = str.split('')
console.log('str = '+str)
console.log('\n')
var pos = 1;
for(var j in str){
//console.log(j)
for(var i in sOrdinata){
if(sOrdinata[i]==str[j]){
console.log('found, position: '+ i)
sOrdinata.splice(i,1)
console.log('Nuovo sOrdinata = '+sOrdinata)
console.log('\n')
break;
}
else{
//calculate number of permutations
console.log('valore di j: '+j)
//console.log('lunghezza stringa da permutare: '+str.slice(~~j+1).length);
if(str.slice(j).length >1 ){sub = str.slice(~~j+1)}else {sub = str.slice(j)}
console.log('substring to be used for permutation: '+ sub)
prep = nrepC(sub.join(''))
console.log('prep = '+prep)
num = factorial(sub.length)
console.log('num = '+num)
den = denom(prep)
console.log('den = '+ den)
pos += num/den
console.log(num/den)
console.log('\n')
}
}
}
console.log(pos)
return pos
}
/* ------------ functions used by main --------------- */
function nrepC(str){
var obj={}
var repeats=[]
var res= [];
for(x = 0, length = str.length; x < length; x++) {
var l = str.charAt(x)
obj[l] = (isNaN(obj[l]) ? 1 : obj[l] + 1);
}
//console.log(obj)
for (var i in obj){
if(obj[i]>1) res.push(obj[i])
}
if(res.length==0){res.push(1); return res}
else return res
}
function num(vect){
var res = 1
}
function denom(vect){
var res = 1
for(var i in vect){
res*= factorial(vect[i])
}
return res
}
function factorial (n){
if (n==0 || n==1){
return 1;
}
return factorial(n-1)*n;
}

A bit too late but just as reference... You can use this C# code directly.
It will work but...
The only important thing is that usually, you should have unique values as your starting set. Otherwise you don't have n! permutations. You have something else (less than n!). I have a little doubt of any useful usage when item could be duplicate ones.
using System;
using System.Collections.Generic;
namespace WpfPermutations
{
public class PermutationOuelletLexico3<T>
{
// ************************************************************************
private T[] _sortedValues;
private bool[] _valueUsed;
public readonly long MaxIndex; // long to support 20! or less
// ************************************************************************
public PermutationOuelletLexico3(T[] sortedValues)
{
if (sortedValues.Length <= 0)
{
throw new ArgumentException("sortedValues.Lenght should be greater than 0");
}
_sortedValues = sortedValues;
Result = new T[_sortedValues.Length];
_valueUsed = new bool[_sortedValues.Length];
MaxIndex = Factorial.GetFactorial(_sortedValues.Length);
}
// ************************************************************************
public T[] Result { get; private set; }
// ************************************************************************
/// <summary>
/// Return the permutation relative to the index received, according to
/// _sortedValues.
/// Sort Index is 0 based and should be less than MaxIndex. Otherwise you get an exception.
/// </summary>
/// <param name="sortIndex"></param>
/// <returns>The result is written in property: Result</returns>
public void GetValuesForIndex(long sortIndex)
{
int size = _sortedValues.Length;
if (sortIndex < 0)
{
throw new ArgumentException("sortIndex should be greater or equal to 0.");
}
if (sortIndex >= MaxIndex)
{
throw new ArgumentException("sortIndex should be less than factorial(the lenght of items)");
}
for (int n = 0; n < _valueUsed.Length; n++)
{
_valueUsed[n] = false;
}
long factorielLower = MaxIndex;
for (int index = 0; index < size; index++)
{
long factorielBigger = factorielLower;
factorielLower = Factorial.GetFactorial(size - index - 1); // factorielBigger / inverseIndex;
int resultItemIndex = (int)(sortIndex % factorielBigger / factorielLower);
int correctedResultItemIndex = 0;
for(;;)
{
if (! _valueUsed[correctedResultItemIndex])
{
resultItemIndex--;
if (resultItemIndex < 0)
{
break;
}
}
correctedResultItemIndex++;
}
Result[index] = _sortedValues[correctedResultItemIndex];
_valueUsed[correctedResultItemIndex] = true;
}
}
// ************************************************************************
/// <summary>
/// Calc the index, relative to _sortedValues, of the permutation received
/// as argument. Returned index is 0 based.
/// </summary>
/// <param name="values"></param>
/// <returns></returns>
public long GetIndexOfValues(T[] values)
{
int size = _sortedValues.Length;
long valuesIndex = 0;
List<T> valuesLeft = new List<T>(_sortedValues);
for (int index = 0; index < size; index++)
{
long indexFactorial = Factorial.GetFactorial(size - 1 - index);
T value = values[index];
int indexCorrected = valuesLeft.IndexOf(value);
valuesIndex = valuesIndex + (indexCorrected * indexFactorial);
valuesLeft.Remove(value);
}
return valuesIndex;
}
// ************************************************************************
}
}

My approach to the problem is sort the given permutation.
Number of swappings of the characters in the string will give us the position of the pemutation in the sorted list of permutations.

An inefficient solution would be to successively find the previous permutations until you reach a string that cannot be permuted anymore. The number of permutations it takes to reach this state is the position of the original string.
However, if you use combinatorics you can achieve the solution faster. The previous solution will produce a very slow output if string length exceeds 12.

Related

Fast String Searching Algorithm for large strings

I'm trying to implement a plagiarism detection software using pattern matching algorithms. I came across the KMP Algorithm Here and tried out the c# implementation. I can see that it's not as fast for actual documents (not strings, I uploaded two pdf documents using iText and got the implementation to check for plagiarism in these two papers. About 50 pages).
It's really slow and I have no idea how to go about this. I've looked at Boyer Moore and Rabin Karp as well.
What I am currently doing is taking each sentence in the document (split on '.') and scanning through the whole reference document (2nd document) for a match. Then taking the next sentence and so on...
I am fully aware that this could be very expensive. But I have no idea how else to implement string (pattern) matching without using this approach. It's for my final year project and I was given a topic so I HAVE to use string matching. (Not allowed to do Citation based plagiarism, Semantics or Vector Space.)
The larger the text and pattern gets, the slower the algorithm gets (extremely slow, not even reasonably slow). Is there another way to go about this that I don't know? Or are there faster algorithms for me to use with this my approach?
EDIT
My code below:`
public class MatchChecker
{
public void KMPSearch(string pattern, string text, int page)
{
if (pattern.Trim() != "")
{
int M = pattern.Length;
int N = text.Length;
// create lps[] that will hold the longest
// prefix suffix values for pattern
int[] lps = new int[M];
int j = 0; // index for pat[]
// Preprocess the pattern (calculate lps[]
// array)
computeLPSArray(pattern, M, lps);
int i = 0; //index for text[]
while (i < N)
{
if (pattern[j] == text[i])
{
j++;
i++;
}
if (j == M)
{
Console.WriteLine("Found pattern " + pattern + " at page " + page);
j = lps[j - 1];
}
//mismatch after j matches
else if (i < N && pattern[j] != text[i])
{
//Do not match lps[0..lps[j-1]] characters,
//they will match anyway
if (j != 0)
j = lps[j - 1];
else
i = i + 1;
}
}
}
}
private void computeLPSArray(string pattern, int M, int[] lps)
{
//length of the previous longest prefix suffix
int length = 0;
int i = 1;
lps[0] = 0; //lps[0]is always 0
//the loop calculates lps[i] for i = 1 to M - 1
while (i < M)
{
if (pattern[i] == pattern[length])
{
length++;
lps[i] = length;
i++;
}
else // (pat[i] != pat[len])
{
// This is tricky. Consider the example.
// AAACAAAA and i = 7. The idea is similar
// to search step.
if (length != 0)
{
length = lps[length - 1];
// Also, note that we do not increment
// i here
}
else // if (len == 0)
{
lps[i] = length;
i++;
}
}
}
}
public string ReadDocPDF()
{
List<string> pages = new List<string>();
PdfReader reader2 = new PdfReader(#"C:\Users\obn\Desktop\project\chapter1.pdf");
string strText = string.Empty;
for (int page = 1; page <= reader2.NumberOfPages; page++)
{
ITextExtractionStrategy its = new SimpleTextExtractionStrategy();
PdfReader reader = new PdfReader(#"C:\Users\obn\Desktop\project\chapter1.pdf");
String s = PdfTextExtractor.GetTextFromPage(reader, page, its);
s = Regex.Replace(Encoding.UTF8.GetString(ASCIIEncoding.Convert(Encoding.Default, Encoding.UTF8, Encoding.Default.GetBytes(s))).Replace(",", ""), "[0-9]", "").ToLower();
pages.Add(s);
strText = strText + s;
reader.Close();
}
return strText;
}
public void CheckForPlag()
{
string document = ReadDocPDF().Trim();
string[] sentences = document.Split(new string[] { "\n", "\t\n\r", ". ", "." }, StringSplitOptions.RemoveEmptyEntries);
foreach(string sentence in sentences) {
PdfReader reader2 = new PdfReader(#"C:\Users\obn\Documents\visual studio 2015\Projects\PlagDetector\PlagDetector\bin\Debug\test3.pdf");
for (int page = 1; page <= reader2.NumberOfPages; page++)
{
ITextExtractionStrategy its = new SimpleTextExtractionStrategy();
PdfReader reader = new PdfReader(#"C:\Users\obn\Documents\visual studio 2015\Projects\PlagDetector\PlagDetector\bin\Debug\test3.pdf");
String s = PdfTextExtractor.GetTextFromPage(reader, page, its);
s = Regex.Replace(Encoding.UTF8.GetString(ASCIIEncoding.Convert(Encoding.Default, Encoding.UTF8, Encoding.Default.GetBytes(s))).Trim().Replace(".","").Replace(",","").Replace("\n", ""), "[0-9]", "").ToLower();
KMPSearch(sentence, s, page);
reader.Close();
}
}
}
}`
Your algorithm is doing lot of repeated searches purely a brute force. Some of the problems features can be considered to optimize it.
How do you define 'plagiarism'? content-1 and content-2 are nearly similar. Let us say >80% are same. i.e content-1 is taken 20% is changed to produce content-2.
Now, Let us try to solve: what will be cost (no.of changes) to convert content-1 to content-2?
This is a well know problem in DP(dynamic programming world) as EDIT Distance problem. The standard problem talks about strings distance, but you can easily modify it for words instead of chars.
Now, the above problem will give you least no.of changes for conversion of content-1 to content-2.
With the total length of content-1, we can easily calculate the % of changes to go to content-2 from content-1. If it below a fixed threshold (say 20%) then declare the plagiarism.

Check if binary string can be partitioned such that each partition is a power of 5

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);
}

Find the first un-repeated character in a string

What is the quickest way to find the first character which only appears once in a string?
It has to be at least O(n) because you don't know if a character will be repeated until you've read all characters.
So you can iterate over the characters and append each character to a list the first time you see it, and separately keep a count of how many times you've seen it (in fact the only values that matter for the count is "0", "1" or "more than 1").
When you reach the end of the string you just have to find the first character in the list that has a count of exactly one.
Example code in Python:
def first_non_repeated_character(s):
counts = defaultdict(int)
l = []
for c in s:
counts[c] += 1
if counts[c] == 1:
l.append(c)
for c in l:
if counts[c] == 1:
return c
return None
This runs in O(n).
I see that people have posted some delightful answers below, so I'd like to offer something more in-depth.
An idiomatic solution in Ruby
We can find the first un-repeated character in a string like so:
def first_unrepeated_char string
string.each_char.tally.find { |_, n| n == 1 }.first
end
How does Ruby accomplish this?
Reading Ruby's source
Let's break down the solution and consider what algorithms Ruby uses for each step.
First we call each_char on the string. This creates an enumerator which allows us to visit the string one character at a time. This is complicated by the fact that Ruby handles Unicode characters, so each value we get from the enumerator can be a variable number of bytes. If we know our input is ASCII or similar, we could use each_byte instead.
The each_char method is implemented like so:
rb_str_each_char(VALUE str)
{
RETURN_SIZED_ENUMERATOR(str, 0, 0, rb_str_each_char_size);
return rb_str_enumerate_chars(str, 0);
}
In turn, rb_string_enumerate_chars is implemented as:
rb_str_enumerate_chars(VALUE str, VALUE ary)
{
VALUE orig = str;
long i, len, n;
const char *ptr;
rb_encoding *enc;
str = rb_str_new_frozen(str);
ptr = RSTRING_PTR(str);
len = RSTRING_LEN(str);
enc = rb_enc_get(str);
if (ENC_CODERANGE_CLEAN_P(ENC_CODERANGE(str))) {
for (i = 0; i < len; i += n) {
n = rb_enc_fast_mbclen(ptr + i, ptr + len, enc);
ENUM_ELEM(ary, rb_str_subseq(str, i, n));
}
}
else {
for (i = 0; i < len; i += n) {
n = rb_enc_mbclen(ptr + i, ptr + len, enc);
ENUM_ELEM(ary, rb_str_subseq(str, i, n));
}
}
RB_GC_GUARD(str);
if (ary)
return ary;
else
return orig;
}
From this we can see that it calls rb_enc_mbclen (or its fast version) to get the length (in bytes) of the next character in the string so that it can iterate the next step. By lazily iterating over a string, reading just one character at a time, we end up doing just one full pass over the input string as tally consumes the iterator.
Tally is then implemented like so:
static void
tally_up(VALUE hash, VALUE group)
{
VALUE tally = rb_hash_aref(hash, group);
if (NIL_P(tally)) {
tally = INT2FIX(1);
}
else if (FIXNUM_P(tally) && tally < INT2FIX(FIXNUM_MAX)) {
tally += INT2FIX(1) & ~FIXNUM_FLAG;
}
else {
tally = rb_big_plus(tally, INT2FIX(1));
}
rb_hash_aset(hash, group, tally);
}
static VALUE
tally_i(RB_BLOCK_CALL_FUNC_ARGLIST(i, hash))
{
ENUM_WANT_SVALUE();
tally_up(hash, i);
return Qnil;
}
Here, tally_i uses RB_BLOCK_CALL_FUNC_ARGLIST to call repeatedly to tally_up, which updates the tally hash on every iteration.
Rough time & memory analysis
The each_char method doesn't allocate an array to eagerly hold the characters of the string, so it has a small constant memory overhead. When we tally the characters, we allocate a hash and put our tally data into it which in the worst case scenario can take up as much memory as the input string times some constant factor.
Time-wise, tally does a full scan of the string, and calling find to locate the first non-repeated character will scan the hash again, each of which carry O(n) worst-case complexity.
However, tally also updates a hash on every iteration. Updating the hash on every character can be as slow as O(n) again, so the worst case complexity of this Ruby solution is perhaps O(n^2).
However, under reasonable assumptions, updating a hash has an O(1) complexity, so we can expect the average case amortized to look like O(n).
My old accepted answer in Python
You can't know that the character is un-repeated until you've processed the whole string, so my suggestion would be this:
def first_non_repeated_character(string):
chars = []
repeated = []
for character in string:
if character in chars:
chars.remove(character)
repeated.append(character)
else:
if not character in repeated:
chars.append(character)
if len(chars):
return chars[0]
else:
return False
Edit: originally posted code was bad, but this latest snippet is Certified To Work On Ryan's Computerâ„¢.
Why not use a heap based data structure such as a minimum priority queue. As you read each character from the string, add it to the queue with a priority based on the location in the string and the number of occurrences so far. You could modify the queue to add priorities on collision so that the priority of a character is the sum of the number appearances of that character. At the end of the loop, the first element in the queue will be the least frequent character in the string and if there are multiple characters with a count == 1, the first element was the first unique character added to the queue.
Here is another fun way to do it. Counter requires Python2.7 or Python3.1
>>> from collections import Counter
>>> def first_non_repeated_character(s):
... return min((k for k,v in Counter(s).items() if v<2), key=s.index)
...
>>> first_non_repeated_character("aaabbbcddd")
'c'
>>> first_non_repeated_character("aaaebbbcddd")
'e'
Lots of answers are attempting O(n) but are forgetting the actual costs of inserting and removing from the lists/associative arrays/sets they're using to track.
If you can assume that a char is a single byte, then you use a simple array indexed by the char and keep a count in it. This is truly O(n) because the array accesses are guaranteed O(1), and the final pass over the array to find the first element with 1 is constant time (because the array has a small, fixed size).
If you can't assume that a char is a single byte, then I would propose sorting the string and then doing a single pass checking adjacent values. This would be O(n log n) for the sort plus O(n) for the final pass. So it's effectively O(n log n), which is better than O(n^2). Also, it has virtually no space overhead, which is another problem with many of the answers that are attempting O(n).
Counter requires Python2.7 or Python3.1
>>> from collections import Counter
>>> def first_non_repeated_character(s):
... counts = Counter(s)
... for c in s:
... if counts[c]==1:
... return c
... return None
...
>>> first_non_repeated_character("aaabbbcddd")
'c'
>>> first_non_repeated_character("aaaebbbcddd")
'e'
Refactoring a solution proposed earlier (not having to use extra list/memory). This goes over the string twice. So this takes O(n) too like the original solution.
def first_non_repeated_character(s):
counts = defaultdict(int)
for c in s:
counts[c] += 1
for c in s:
if counts[c] == 1:
return c
return None
The following is a Ruby implementation of finding the first nonrepeated character of a string:
def first_non_repeated_character(string)
string1 = string.split('')
string2 = string.split('')
string1.each do |let1|
counter = 0
string2.each do |let2|
if let1 == let2
counter+=1
end
end
if counter == 1
return let1
break
end
end
end
p first_non_repeated_character('dont doddle in the forest')
And here is a JavaScript implementation of the same style function:
var first_non_repeated_character = function (string) {
var string1 = string.split('');
var string2 = string.split('');
var single_letters = [];
for (var i = 0; i < string1.length; i++) {
var count = 0;
for (var x = 0; x < string2.length; x++) {
if (string1[i] == string2[x]) {
count++
}
}
if (count == 1) {
return string1[i];
}
}
}
console.log(first_non_repeated_character('dont doddle in the forest'));
console.log(first_non_repeated_character('how are you today really?'));
In both cases I used a counter knowing that if the letter is not matched anywhere in the string, it will only occur in the string once so I just count it's occurrence.
I think this should do it in C. This operates in O(n) time with no ambiguity about order of insertion and deletion operators. This is a counting sort (simplest form of a bucket sort, which itself is the simple form of a radix sort).
unsigned char find_first_unique(unsigned char *string)
{
int chars[256];
int i=0;
memset(chars, 0, sizeof(chars));
while (string[i++])
{
chars[string[i]]++;
}
i = 0;
while (string[i++])
{
if (chars[string[i]] == 1) return string[i];
}
return 0;
}
In Ruby:
(Original Credit: Andrew A. Smith)
x = "a huge string in which some characters repeat"
def first_unique_character(s)
s.each_char.detect { |c| s.count(c) == 1 }
end
first_unique_character(x)
=> "u"
def first_non_repeated_character(string):
chars = []
repeated = []
for character in string:
if character in repeated:
... discard it.
else if character in chars:
chars.remove(character)
repeated.append(character)
else:
if not character in repeated:
chars.append(character)
if len(chars):
return chars[0]
else:
return False
Other JavaScript solutions are quite c-style solutions here is a more JavaScript-style solution.
var arr = string.split("");
var occurences = {};
var tmp;
var lowestindex = string.length+1;
arr.forEach( function(c){
tmp = c;
if( typeof occurences[tmp] == "undefined")
occurences[tmp] = tmp;
else
occurences[tmp] += tmp;
});
for(var p in occurences) {
if(occurences[p].length == 1)
lowestindex = Math.min(lowestindex, string.indexOf(p));
}
if(lowestindex > string.length)
return null;
return string[lowestindex];
}
in C, this is almost Shlemiel the Painter's Algorithm (not quite O(n!) but more than 0(n2)).
But will outperform "better" algorithms for reasonably sized strings because O is so small. This can also easily tell you the location of the first non-repeating string.
char FirstNonRepeatedChar(char * psz)
{
for (int ii = 0; psz[ii] != 0; ++ii)
{
for (int jj = ii+1; ; ++jj)
{
// if we hit the end of string, then we found a non-repeat character.
//
if (psz[jj] == 0)
return psz[ii]; // this character doesn't repeat
// if we found a repeat character, we can stop looking.
//
if (psz[ii] == psz[jj])
break;
}
}
return 0; // there were no non-repeating characters.
}
edit: this code is assuming you don't mean consecutive repeating characters.
Here's an implementation in Perl (version >=5.10) that doesn't care whether the repeated characters are consecutive or not:
use strict;
use warnings;
foreach my $word(#ARGV)
{
my #distinct_chars;
my %char_counts;
my #chars=split(//,$word);
foreach (#chars)
{
push #distinct_chars,$_ unless $_~~#distinct_chars;
$char_counts{$_}++;
}
my $first_non_repeated="";
foreach(#distinct_chars)
{
if($char_counts{$_}==1)
{
$first_non_repeated=$_;
last;
}
}
if(length($first_non_repeated))
{
print "For \"$word\", the first non-repeated character is '$first_non_repeated'.\n";
}
else
{
print "All characters in \"$word\" are repeated.\n";
}
}
Storing this code in a script (which I named non_repeated.pl) and running it on a few inputs produces:
jmaney> perl non_repeated.pl aabccd "a huge string in which some characters repeat" abcabc
For "aabccd", the first non-repeated character is 'b'.
For "a huge string in which some characters repeat", the first non-repeated character is 'u'.
All characters in "abcabc" are repeated.
Here's a possible solution in ruby without using Array#detect (as in this answer). Using Array#detect makes it too easy, I think.
ALPHABET = %w(a b c d e f g h i j k l m n o p q r s t u v w x y z)
def fnr(s)
unseen_chars = ALPHABET.dup
seen_once_chars = []
s.each_char do |c|
if unseen_chars.include?(c)
unseen_chars.delete(c)
seen_once_chars << c
elsif seen_once_chars.include?(c)
seen_once_chars.delete(c)
end
end
seen_once_chars.first
end
Seems to work for some simple examples:
fnr "abcdabcegghh"
# => "d"
fnr "abababababababaqababa"
=> "q"
Suggestions and corrections are very much appreciated!
Try this code:
public static String findFirstUnique(String str)
{
String unique = "";
foreach (char ch in str)
{
if (unique.Contains(ch)) unique=unique.Replace(ch.ToString(), "");
else unique += ch.ToString();
}
return unique[0].ToString();
}
In Mathematica one might write this:
string = "conservationist deliberately treasures analytical";
Cases[Gather # Characters # string, {_}, 1, 1][[1]]
{"v"}
This snippet code in JavaScript
var string = "tooth";
var hash = [];
for(var i=0; j=string.length, i<j; i++){
if(hash[string[i]] !== undefined){
hash[string[i]] = hash[string[i]] + 1;
}else{
hash[string[i]] = 1;
}
}
for(i=0; j=string.length, i<j; i++){
if(hash[string[i]] === 1){
console.info( string[i] );
return false;
}
}
// prints "h"
Different approach here.
scan each element in the string and create a count array which stores the repetition count of each element.
Next time again start from first element in the array and print the first occurrence of element with count = 1
C code
-----
#include <stdio.h>
#include <stdlib.h>
int main(int argc, char *argv[])
{
char t_c;
char *t_p = argv[1] ;
char count[128]={'\0'};
char ch;
for(t_c = *(argv[1]); t_c != '\0'; t_c = *(++t_p))
count[t_c]++;
t_p = argv[1];
for(t_c = *t_p; t_c != '\0'; t_c = *(++t_p))
{
if(count[t_c] == 1)
{
printf("Element is %c\n",t_c);
break;
}
}
return 0;
}
input is = aabbcddeef output is = c
char FindUniqueChar(char *a)
{
int i=0;
bool repeat=false;
while(a[i] != '\0')
{
if (a[i] == a[i+1])
{
repeat = true;
}
else
{
if(!repeat)
{
cout<<a[i];
return a[i];
}
repeat=false;
}
i++;
}
return a[i];
}
Here is another approach...we could have a array which will store the count and the index of the first occurrence of the character. After filling up the array we could jst traverse the array and find the MINIMUM index whose count is 1 then return str[index]
#include <iostream>
#include <cstdio>
#include <cstdlib>
#include <climits>
using namespace std;
#define No_of_chars 256
//store the count and the index where the char first appear
typedef struct countarray
{
int count;
int index;
}countarray;
//returns the count array
countarray *getcountarray(char *str)
{
countarray *count;
count=new countarray[No_of_chars];
for(int i=0;i<No_of_chars;i++)
{
count[i].count=0;
count[i].index=-1;
}
for(int i=0;*(str+i);i++)
{
(count[*(str+i)].count)++;
if(count[*(str+i)].count==1) //if count==1 then update the index
count[*(str+i)].index=i;
}
return count;
}
char firstnonrepeatingchar(char *str)
{
countarray *array;
array = getcountarray(str);
int result = INT_MAX;
for(int i=0;i<No_of_chars;i++)
{
if(array[i].count==1 && result > array[i].index)
result = array[i].index;
}
delete[] (array);
return (str[result]);
}
int main()
{
char str[] = "geeksforgeeks";
cout<<"First non repeating character is "<<firstnonrepeatingchar(str)<<endl;
return 0;
}
Function:
This c# function uses a HashTable (Dictionary) and have a performance O(2n) worstcase.
private static string FirstNoRepeatingCharacter(string aword)
{
Dictionary<string, int> dic = new Dictionary<string, int>();
for (int i = 0; i < aword.Length; i++)
{
if (!dic.ContainsKey(aword.Substring(i, 1)))
dic.Add(aword.Substring(i, 1), 1);
else
dic[aword.Substring(i, 1)]++;
}
foreach (var item in dic)
{
if (item.Value == 1) return item.Key;
}
return string.Empty;
}
Example:
string aword = "TEETER";
Console.WriteLine(FirstNoRepeatingCharacter(aword)); //print: R
I have two strings i.e. 'unique' and 'repeated'. Every character appearing for the first time, gets added to 'unique'. If it is repeated for the second time, it gets removed from 'unique' and added to 'repeated'. This way, we will always have a string of unique characters in 'unique'.
Complexity big O(n)
public void firstUniqueChar(String str){
String unique= "";
String repeated = "";
str = str.toLowerCase();
for(int i=0; i<str.length();i++){
char ch = str.charAt(i);
if(!(repeated.contains(str.subSequence(i, i+1))))
if(unique.contains(str.subSequence(i, i+1))){
unique = unique.replaceAll(Character.toString(ch), "");
repeated = repeated+ch;
}
else
unique = unique+ch;
}
System.out.println(unique.charAt(0));
}
The following code is in C# with complexity of n.
using System;
using System.Linq;
using System.Text;
namespace SomethingDigital
{
class FirstNonRepeatingChar
{
public static void Main()
{
String input = "geeksforgeeksandgeeksquizfor";
char[] str = input.ToCharArray();
bool[] b = new bool[256];
String unique1 = "";
String unique2 = "";
foreach (char ch in str)
{
if (!unique1.Contains(ch))
{
unique1 = unique1 + ch;
unique2 = unique2 + ch;
}
else
{
unique2 = unique2.Replace(ch.ToString(), "");
}
}
if (unique2 != "")
{
Console.WriteLine(unique2[0].ToString());
Console.ReadLine();
}
else
{
Console.WriteLine("No non repeated string");
Console.ReadLine();
}
}
}
}
The following solution is an elegant way to find the first unique character within a string using the new features which have been introduced as part as Java 8. This solution uses the approach of first creating a map to count the number of occurrences of each character. It then uses this map to find the first character which occurs only once. This runs in O(N) time.
import static java.util.stream.Collectors.counting;
import static java.util.stream.Collectors.groupingBy;
import java.util.Arrays;
import java.util.List;
import java.util.Map;
// Runs in O(N) time and uses lambdas and the stream API from Java 8
// Also, it is only three lines of code!
private static String findFirstUniqueCharacterPerformantWithLambda(String inputString) {
// convert the input string into a list of characters
final List<String> inputCharacters = Arrays.asList(inputString.split(""));
// first, construct a map to count the number of occurrences of each character
final Map<Object, Long> characterCounts = inputCharacters
.stream()
.collect(groupingBy(s -> s, counting()));
// then, find the first unique character by consulting the count map
return inputCharacters
.stream()
.filter(s -> characterCounts.get(s) == 1)
.findFirst()
.orElse(null);
}
Here is one more solution with o(n) time complexity.
public void findUnique(String string) {
ArrayList<Character> uniqueList = new ArrayList<>();
int[] chatArr = new int[128];
for (int i = 0; i < string.length(); i++) {
Character ch = string.charAt(i);
if (chatArr[ch] != -1) {
chatArr[ch] = -1;
uniqueList.add(ch);
} else {
uniqueList.remove(ch);
}
}
if (uniqueList.size() == 0) {
System.out.println("No unique character found!");
} else {
System.out.println("First unique character is :" + uniqueList.get(0));
}
}
I read through the answers, but did not see any like mine, I think this answer is very simple and fast, am I wrong?
def first_unique(s):
repeated = []
while s:
if s[0] not in s[1:] and s[0] not in repeated:
return s[0]
else:
repeated.append(s[0])
s = s[1:]
return None
test
(first_unique('abdcab') == 'd', first_unique('aabbccdad') == None, first_unique('') == None, first_unique('a') == 'a')
Question : First Unique Character of a String
This is the simplest solution.
public class Test4 {
public static void main(String[] args) {
String a = "GiniGinaProtijayi";
firstUniqCharindex(a);
}
public static void firstUniqCharindex(String a) {
int[] count = new int[256];
for (int i = 0; i < a.length(); i++) {
count[a.charAt(i)]++;
}
int index = -1;
for (int i = 0; i < a.length(); i++) {
if (count[a.charAt(i)] == 1) {
index = i;
break;
} // if
}
System.out.println(index);// output => 8
System.out.println(a.charAt(index)); //output => P
}// end1
}
IN Python :
def firstUniqChar(a):
count = [0] * 256
for i in a: count[ord(i)] += 1
element = ""
for items in a:
if(count[ord(items) ] == 1):
element = items ;
break
return element
a = "GiniGinaProtijayi";
print(firstUniqChar(a)) # output is P
Using Java 8 :
public class Test2 {
public static void main(String[] args) {
String a = "GiniGinaProtijayi";
Map<Character, Long> map = a.chars()
.mapToObj(
ch -> Character.valueOf((char) ch)
).collect(
Collectors.groupingBy(
Function.identity(),
LinkedHashMap::new,
Collectors.counting()));
System.out.println("MAP => " + map);
// {G=2, i=5, n=2, a=2, P=1, r=1, o=1, t=1, j=1, y=1}
Character chh = map
.entrySet()
.stream()
.filter(entry -> entry.getValue() == 1L)
.map(entry -> entry.getKey())
.findFirst()
.get();
System.out.println("First Non Repeating Character => " + chh);// P
}// main
}
how about using a suffix tree for this case... the first unrepeated character will be first character of longest suffix string with least depth in tree..
Create Two list -
unique list - having only unique character .. UL
non-unique list - having only repeated character -NUL
for(char c in str) {
if(nul.contains(c)){
//do nothing
}else if(ul.contains(c)){
ul.remove(c);
nul.add(c);
}else{
nul.add(c);
}

How can I compute the number of characters required to turn a string into a palindrome?

I recently found a contest problem that asks you to compute the minimum number of characters that must be inserted (anywhere) in a string to turn it into a palindrome.
For example, given the string: "abcbd" we can turn it into a palindrome by inserting just two characters: one after "a" and another after "d": "adbcbda".
This seems to be a generalization of a similar problem that asks for the same thing, except characters can only be added at the end - this has a pretty simple solution in O(N) using hash tables.
I have been trying to modify the Levenshtein distance algorithm to solve this problem, but haven't been successful. Any help on how to solve this (it doesn't necessarily have to be efficient, I'm just interested in any DP solution) would be appreciated.
Note: This is just a curiosity. Dav proposed an algorithm which can be modified to DP algorithm to run in O(n^2) time and O(n^2) space easily (and perhaps O(n) with better bookkeeping).
Of course, this 'naive' algorithm might actually come in handy if you decide to change the allowed operations.
Here is a 'naive'ish algorithm, which can probably be made faster with clever bookkeeping.
Given a string, we guess the middle of the resulting palindrome and then try to compute the number of inserts required to make the string a palindrome around that middle.
If the string is of length n, there are 2n+1 possible middles (Each character, between two characters, just before and just after the string).
Suppose we consider a middle which gives us two strings L and R (one to left and one to right).
If we are using inserts, I believe the Longest Common Subsequence algorithm (which is a DP algorithm) can now be used the create a 'super' string which contains both L and reverse of R, see Shortest common supersequence.
Pick the middle which gives you the smallest number inserts.
This is O(n^3) I believe. (Note: I haven't tried proving that it is true).
My C# solution looks for repeated characters in a string and uses them to reduce the number of insertions. In a word like program, I use the 'r' characters as a boundary. Inside of the 'r's, I make that a palindrome (recursively). Outside of the 'r's, I mirror the characters on the left and the right.
Some inputs have more than one shortest output: output can be toutptuot or outuputuo. My solution only selects one of the possibilities.
Some example runs:
radar -> radar, 0 insertions
esystem -> metsystem, 2 insertions
message -> megassagem, 3 insertions
stackexchange -> stegnahckexekchangets, 8 insertions
First I need to check if an input is already a palindrome:
public static bool IsPalindrome(string str)
{
for (int left = 0, right = str.Length - 1; left < right; left++, right--)
{
if (str[left] != str[right])
return false;
}
return true;
}
Then I need to find any repeated characters in the input. There may be more than one. The word message has two most-repeated characters ('e' and 's'):
private static bool TryFindMostRepeatedChar(string str, out List<char> chs)
{
chs = new List<char>();
int maxCount = 1;
var dict = new Dictionary<char, int>();
foreach (var item in str)
{
int temp;
if (dict.TryGetValue(item, out temp))
{
dict[item] = temp + 1;
maxCount = temp + 1;
}
else
dict.Add(item, 1);
}
foreach (var item in dict)
{
if (item.Value == maxCount)
chs.Add(item.Key);
}
return maxCount > 1;
}
My algorithm is here:
public static string MakePalindrome(string str)
{
List<char> repeatedList;
if (string.IsNullOrWhiteSpace(str) || IsPalindrome(str))
{
return str;
}
//If an input has repeated characters,
// use them to reduce the number of insertions
else if (TryFindMostRepeatedChar(str, out repeatedList))
{
string shortestResult = null;
foreach (var ch in repeatedList) //"program" -> { 'r' }
{
//find boundaries
int iLeft = str.IndexOf(ch); // "program" -> 1
int iRight = str.LastIndexOf(ch); // "program" -> 4
//make a palindrome of the inside chars
string inside = str.Substring(iLeft + 1, iRight - iLeft - 1); // "program" -> "og"
string insidePal = MakePalindrome(inside); // "og" -> "ogo"
string right = str.Substring(iRight + 1); // "program" -> "am"
string rightRev = Reverse(right); // "program" -> "ma"
string left = str.Substring(0, iLeft); // "program" -> "p"
string leftRev = Reverse(left); // "p" -> "p"
//Shave off extra chars in rightRev and leftRev
// When input = "message", this loop converts "meegassageem" to "megassagem",
// ("ee" to "e"), as long as the extra 'e' is an inserted char
while (left.Length > 0 && rightRev.Length > 0 &&
left[left.Length - 1] == rightRev[0])
{
rightRev = rightRev.Substring(1);
leftRev = leftRev.Substring(1);
}
//piece together the result
string result = left + rightRev + ch + insidePal + ch + right + leftRev;
//find the shortest result for inputs that have multiple repeated characters
if (shortestResult == null || result.Length < shortestResult.Length)
shortestResult = result;
}
return shortestResult;
}
else
{
//For inputs that have no repeated characters,
// just mirror the characters using the last character as the pivot.
for (int i = str.Length - 2; i >= 0; i--)
{
str += str[i];
}
return str;
}
}
Note that you need a Reverse function:
public static string Reverse(string str)
{
string result = "";
for (int i = str.Length - 1; i >= 0; i--)
{
result += str[i];
}
return result;
}
C# Recursive solution adding to the end of the string:
There are 2 base cases. When length is 1 or 2. Recursive case: If the extremes are equal, then
make palindrome the inner string without the extremes and return that with the extremes.
If the extremes are not equal, then add the first character to the end and make palindrome the
inner string including the previous last character. return that.
public static string ConvertToPalindrome(string str) // By only adding characters at the end
{
if (str.Length == 1) return str; // base case 1
if (str.Length == 2 && str[0] == str[1]) return str; // base case 2
else
{
if (str[0] == str[str.Length - 1]) // keep the extremes and call
return str[0] + ConvertToPalindrome(str.Substring(1, str.Length - 2)) + str[str.Length - 1];
else //Add the first character at the end and call
return str[0] + ConvertToPalindrome(str.Substring(1, str.Length - 1)) + str[0];
}
}

Algorithm to find first index where strings are different?

I've got a collection of strings, and I need to know the first index where they all differ. I can think of two ways to do this: (the following pseudo code is just off the top of my head and may be heavily bug-laden)
First Way:
var minLength = [go through all strings finding min length];
var set = new set()
for(i=0;i<minlength;i++)
{
for(str in strings)
{
var substring = str.substring(0,i);
if(set.contains(substring))
break; // not all different yet, increment i
set.add(substring)
}
set.clear(); // prepare for next length of substring
}
This strikes me as gross because of the use of a set data structure where it seems like one should not be needed.
Second Way:
var minLength = [go through all strings finding min length];
strings.sort();
for(i=0;i<minlength;i++)
{
boolean done = true;
char last = null;
for(str in strings)
{
char c = str[i];
if(c == last)
{
// not all different yet, increment i
done = false;
break;
}
last = c;
}
if(done)
return i;
}
But it annoys me that I have to run the sort first, because the sorting algorithm, by its very nature, has access to the information that I'm looking for.
Surely there must be a more efficient way than what I have listed above. Eventually I'd like to abstract it out to any type of array, but that will be trivial and it's simpler to think of it as a string problem.
Any help?
**UPDATE: I apparently didn't explain myself very well. If my strings are ["apple", "banana", "cucumber", "banking"], I want the function to return 3, because there were two strings ("banana" and "banking") that matched through index 0, 1, and 2, so 3 is the first index where they are all unique.
As Daniel mentioned below, a better way to state my needs is that: "I want to find index i where calling substring(0,i) on all my strings will result in all unique values."**
This is untested, but here's my attempt. (I may be making it more complicated than I have to, but I think it's a different way to look at it.)
The basic idea is to compile groups of items that match at the first element, then find the max unique index for each group, checking elements at each successive index.
int FirstUniqueIndex<T>(IEnumerable<IEnumerable<T>> myArrayCollection)
{
//just an overload so you don't have to specify index 0 all the time
return FirstUniqueIndex(myArrayCollection, 0);
}
int FirstUniqueIndex<T>(IEnumerable<IEnumerable<T>> myArrayCollection, int StartIndex)
{
/* Group the current collection by the element at StartIndex, and
* return a collection of these groups. Additionally, we're only interested
* in the groups with more than one element, so only get those.*/
var groupsWithMatches = from var item in myArrayCollection //for each item in the collection (called "item")
where item.Length > StartIndex //that are long enough
group by item[StartIndex] into g //group them by the element at StartIndex, and call the group "g"
where g.Skip(1).Any() //only want groups with more than one element
select g; //add the group to the collection
/* Now "groupsWithMatches" is an enumeration of groups of inner matches of
* your original arrays. Let's process them... */
if(groupsWithMatches.Any())
//some matches were found - check the next index for each group
//(get the maximum unique index of all the matched groups)
return groupsWithMatches.Max(group => FirstUniqueIndex(group, StartIndex + 1));
else
//no matches found, all unique at this index
return StartIndex;
}
And for the non-LINQ version of the above (I'll change it to use a List collection, but any collection will do). I'll even remove the lambda. Again untested, so try not to aim sharp implements in my direction.
int FirstUniqueIndex<T>(List<List<T>> myArrayCollection, int StartIndex)
{
/* Group the current collection by the element at StartIndex, and
* return a collection of these groups. Additionally, we're only interested
* in the groups with more than one element, so only get those.*/
Dictionary<T, List<List<T>>> groupsWithMatches = new Dictionary<T, List<List<T>>>();
//group all the items by the element at StartIndex
foreach(var item in myArrayCollection)
{
if(item.Count > StartIndex)
{
List<List<T>> group;
if(!groups.TryGetValue(item[StartIndex], out group))
{
//new group, so make it first
group = new List<List<T>>();
groups.Add(item[StartIndex], group);
}
group.Add(Item);
}
}
/* Now "groups" is an enumeration of groups of inner matches of
* your original arrays. Let's get the groups with more than one item. */
List<List<List<T>>> groupsWithMatches = new List<List<List<T>>>(groups.Count);
foreach(List<List<T> group in groupsWithMatches)
{
if(group.Count > 1)
groupsWithMatches.Add(group);
}
if(groupsWithMatches.Count > 0)
{
//some matches were found - check the next index for each group
//(get the maximum unique index of all the matched groups)
int max = -1;
foreach(List<List<T>> group in groupsWithMatches)
{
int index = FirstUniqueIndex(group, StartIndex + 1);
max = index > max ? index : max;
}
return max;
}
else
{
//no matches found, all unique at this index
return StartIndex;
}
}
have you looked at a Patricia trie? (Java implementation available on google code)
Build the trie, then traverse the data structure to find the maximum string position of all the internal nodes (black dots in the function above).
This seems like it should be an O(n) operation. I'm not sure whether your set implementation is O(n) or not -- it "smells" like O(n2) but I'm not sure.
Use the set as you proposed, that's exactly the right thing to do.
You should be able to do this without sorting, and with only looking at each character in each string once in the worst case.
here is a ruby script that puts the index to the console:
mystrings = ["apple", "banana", "cucumber", "banking"]
minlength = getMinLengthString(mystrings) #not defined here
char_set = {}
(0..minlength).each do |char_index|
char_set[mystrings[0][char_index].chr] = 1
(1..mystrings.length).each do |string_index|
comparing_char = mystrings[string_index][char_index].chr
break if char_set[comparing_char]
if string_index == (mystrings.length - 1) then
puts string_index
exit
else
char_set[comparing_char] = 1
end
end
char_set.clear
end
puts minlength
the result is 3.
Here's the same general snippet in C#, if it is more legible for you:
string[] mystrings = { "apple", "banana", "cucumber", "banking" };
//defined elsewhere...
int minlength = GetMinStringLengthFromStringArray(mystrings);
Dictionary<char, int> charSet = new Dictionary<char, int>();
for (int char_index = 0; char_index < minlength; char_index++)
{
charSet.Add(mystrings[0][char_index], 1);
for (int string_index = 1; string_index < mystrings.Length; string_index++)
{
char comparing_char = mystrings[string_index][char_index];
if (charSet.ContainsKey(comparing_char))
{
break;
}
else
{
if (string_index == mystrings.Length - 1)
{
Console.Out.WriteLine("Index is: " + string_index.ToString());
return;
}
else
{
charSet.Add(comparing_char, 1);
}
}
}
charSet.Clear();
}
Console.Out.WriteLine("Index is: " + minlength.ToString());
int i = 0;
while(true)
{
Set set = new Set();
for(int j = 0; j < strings.length; j++)
{
if(i >= strings[j].length) return i;
String chr = strings[j].charAt(i);
if(set.hasElement(chr))
break;
else
set.addElement(chr);
}
if(set.size() == strings.length)
return i;
i++;
}
Gotta check preconditions first.
EDIT: Using a set now. Changed langauge.
Here's my solution in Python:
words = ["apple", "banana", "cucumber", "banking"]
for i in range(len(min(words))):
d = defaultdict(int)
for word in words:
d[word[i]] += 1
if max(d.values()) == 1:
return i
I didn't write in anything to handle the case where no minimum index is found by the time you reach the end of the shortest word, but I'm sure you get the idea.

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