I want an algorithm to remove all occurrences of a given character from a string in O(n) complexity or lower? (It should be INPLACE editing original string only)
eg.
String="aadecabaaab";
removeCharacter='a'
Output:"decbb"
Enjoy algo:
j = 0
for i in length(a):
if a[i] != symbol:
a[j] = a[i]
j = j + 1
finalize:
length(a) = j
You can't do it in place with a String because it's immutable, but here's an O(n) algorithm to do it in place with a char[]:
char[] chars = "aadecabaaab".toCharArray();
char removeCharacter = 'a';
int next = 0;
for (int cur = 0; cur < chars.length; ++cur) {
if (chars[cur] != removeCharacter) {
chars[next++] = chars[cur];
}
}
// chars[0] through chars[4] will have {d, e, c, b, b} and next will be 5
System.out.println(new String(chars, 0, next));
Strictly speaking, you can't remove anything from a String because the String class is immutable. But you can construct another String that has all characters from the original String except for the "character to remove".
Create a StringBuilder. Loop through all characters in the original String. If the current character is not the character to remove, then append it to the StringBuilder. After the loop ends, convert the StringBuilder to a String.
Yep. In a linear time, iterate over String, check using .charAt() if this is a removeCharacter, don't copy it to new String. If no, copy. That's it.
This probably shouldn't have the "java" tag since in Java, a String is immutable and you can't edit it in place. For a more general case, if you have an array of characters (in any programming language) and you want to modify the array "in place" without creating another array, it's easy enough to do with two indexes. One goes through every character in the array, and the other starts at the beginning and is incremented only when you see a character that isn't removeCharacter. Since I assume this is a homework assignment, I'll leave it at that and let you figure out the details.
import java.util.*;
import java.io.*;
public class removeA{
public static void main(String[] args){
String text = "This is a test string! Wow abcdefg.";
System.out.println(text.replaceAll("a",""));
}
}
Use a hash table to hold the data you want to remove. log N complexity.
std::string toRemove = "ad";
std::map<char, int> table;
size_t maxR = toRemove.size();
for (size_t n = 0; n < maxR; ++n)
{
table[toRemove[n]] = 0;
}
Then parse the whole string and remove when you get a hit (thestring is an array):
size_t counter = 0;
while(thestring[counter] != 0)
{
std::map<char,int>::iterator iter = table.find(thestring[counter]);
if (iter == table.end()) // we found a valid character!
{
++counter;
}
else
{
// move the data - dont increment counter
memcpy(&thestring[counter], &thestring[counter+1], max-counter);
// dont increment counter
}
}
EDIT: I hope this is not a technical test or something like that. =S
Related
I want to make a dynamic string generator that will generate all possible unique strings from a character set with a dynamic length.
I can make this very easily using for loops but then its static and not dynamic length.
// Prints all possible strings with the length of 3
for a in allowedCharacters {
for b in allowedCharacters {
for c in allowedCharacters {
println(a+b+c)
}
}
}
But when I want to make this dynamic of length so I can just call generate(length: 5) I get confused.
I found this Stackoverflow question But the accepted answer generates strings 1-maxLength length and I want maxLength on ever string.
As noted above, use recursion. Here is how it can be done with C#:
static IEnumerable<string> Generate(int length, char[] allowed_chars)
{
if (length == 1)
{
foreach (char c in allowed_chars)
yield return c.ToString();
}
else
{
var sub_strings = Generate(length - 1, allowed_chars);
foreach (char c in allowed_chars)
{
foreach (string sub in sub_strings)
{
yield return c + sub;
}
}
}
}
private static void Main(string[] args)
{
string chars = "abc";
List<string> result = Generate(3, chars.ToCharArray()).ToList();
}
Please note that the run time of this algorithm and the amount of data it returns is exponential as the length increases which means that if you have large lengths, you should expect the code to take a long time and to return a huge amount of data.
Translation of #YacoubMassad's C# code to Swift:
func generate(length: Int, allowedChars: [String]) -> [String] {
if length == 1 {
return allowedChars
}
else {
let subStrings = generate(length - 1, allowedChars: allowedChars)
var arr = [String]()
for c in allowedChars {
for sub in subStrings {
arr.append(c + sub)
}
}
return arr
}
}
println(generate(3, allowedChars: ["a", "b", "c"]))
Prints:
aaa, aab, aac, aba, abb, abc, aca, acb, acc, baa, bab, bac, bba, bbb, bbc, bca, bcb, bcc, caa, cab, cac, cba, cbb, cbc, cca, ccb, ccc
While you can (obviously enough) use recursion to solve this problem, it quite an inefficient way to do the job.
What you're really doing is just counting. In your example, with "a", "b" and "c" as the allowed characters, you're counting in base 3, and since you're allowing three character strings, they're three digit numbers.
An N-digit number in base M can represent NM different possible values, going from 0 through NM-1. So, for your case, that's limit=pow(3, 3)-1;. To generate all those values, you just count from 0 through the limit, and convert each number to base M, using the specified characters as the "digits". For example, in C++ the code can look like this:
#include <string>
#include <iostream>
int main() {
std::string letters = "abc";
std::size_t base = letters.length();
std::size_t digits = 3;
int limit = pow(base, digits);
for (int i = 0; i < limit; i++) {
int in = i;
for (int j = 0; j < digits; j++) {
std::cout << letters[in%base];
in /= base;
}
std::cout << "\t";
}
}
One minor note: as I've written it here, this produces the output in basically a little-endian format. That is, the "digit" that varies the fastest is on the left, and the one that changes the slowest is on the right.
Given a string S and a set of n substrings. Remove every instance of those n substrings from S so that S is of the minimum length and output this minimum length.
Example 1
S = ccdaabcdbb
n = 2
substrings = ab, cd
Output
2
Explanation:
ccdaabcdbb -> ccdacdbb -> cabb -> cb (length=2)
Example 2
S = abcd
n = 2
substrings = ab,bcd
Output
1
How do I solve this problem ?
A simple Brute-force search algorithm is:
For each substring, try all possible ways to remove it from the string, then recurse.
In Pseudocode:
def min_final_length (input, substrings):
best = len(input)
for substr in substrings:
beg = 0
// find all occurrences of substr in input and recurse
while (found = find_substring(input, substr, from=beg)):
input_without_substr = input[0:found]+input[found+len(substr):len(input)]
best = min(best, min_final_length(input_without_substr,substrings))
beg = found+1
return best
Let complexity be F(S,n,l) where S is the length of the input string, n is the cardinality of the set substrings and l is the "characteristic length" of substrings. Then
F(S,n,l) ~ n * ( S * l + F(S-l,n,l) )
Looks like it is at most O(S^2*n*l).
The following solution would have an complexity of O(m * n) where m = len(S) and n is the number of substring
def foo(S, sub):
i = 0
while i < len(S):
for e in sub:
if S[i:].startswith(e):
S = S[:i] + S[i+len(e):]
i -= 1
break
else: i += 1
return S, i
If you are for raw performance and your string is very large, you can do better than brute force. Use a suffix trie (E.g, Ukkonnen trie) to store your string. Then find each substring (which us done in O(m) time, m being substring length), and store the offsets to the substrings and length in an array.
Then use the offsets and length info to actually remove the substrings by filling these areas with \0 (in C) or another placeholder character. By counting all non-Null characters you will get the minimal length of the string.
This will als handle overlapping substring, e.g. say your string is "abcd", and you have two substrings "ab" and "abcd".
I solved it using trie+dp.
First insert your substrings in a trie. Then define the state of the dp is some string, walk through that string and consider each i (for i =0 .. s.length()) as the start of some substring. let j=i and increment j as long as you have a suffix in the trie (which will definitely land you to at least one substring and may be more if you have common suffix between some substring, for example "abce" and "abdd"), whenever you encounter an end of some substring, go solve the new sub-problem and find the minimum between all substring reductions.
Here is my code for it. Don't worry about the length of the code. Just read the solve function and forget about the path, I included it to print the string formed.
struct node{
node* c[26];
bool str_end;
node(){
for(int i= 0;i<26;i++){
c[i]=NULL;
}
str_end= false;
}
};
class Trie{
public:
node* root;
Trie(){
root = new node();
}
~Trie(){
delete root;
}
};
class Solution{
public:
typedef pair<int,int>ii;
string get_str(string& s,map<string,ii>&path){
if(!path.count(s)){
return s;
}
int i= path[s].first;
int j= path[s].second;
string new_str =(s.substr(0,i)+s.substr(j+1));
return get_str(new_str,path);
}
int solve(string& s,Trie* &t, map<string,int>&dp,map<string,ii>&path){
if(dp.count(s)){
return dp[s];
}
int mn= (int)s.length();
for(int i =0;i<s.length();i++){
string left = s.substr(0,i);
node* cur = t->root->c[s[i]-97];
int j=i;
while(j<s.length()&&cur!=NULL){
if(cur->str_end){
string new_str =left+s.substr(j+1);
int ret= solve(new_str,t,dp,path);
if(ret<mn){
path[s]={i,j};
}
}
cur = cur->c[s[++j]-97];
}
}
return dp[s]=mn;
}
string removeSubstrings(vector<string>& substrs, string s){
map<string,ii>path;
map<string,int>dp;
Trie*t = new Trie();
for(int i =0;i<substrs.size();i++){
node* cur = t->root;
for(int j=0;j<substrs[i].length();j++){
if(cur->c[substrs[i][j]-97]==NULL){
cur->c[substrs[i][j]-97]= new node();
}
cur = cur->c[substrs[i][j]-97];
if(j==substrs[i].length()-1){
cur->str_end= true;
}
}
}
solve(s,t,dp,path);
return get_str(s, path);
}
};
int main(){
vector<string>substrs;
substrs.push_back("ab");
substrs.push_back("cd");
Solution s;
cout << s.removeSubstrings(substrs,"ccdaabcdbb")<<endl;
return 0;
}
I strings in the format of name:key:dataLength:data and these strings can often be chained together. for example "aNum:n:4:9879aBool:b:1:taString:s:2:Hi" this would map to an object something like:
{
aNum: 9879,
aBool: true,
aString: "Hi"
}
I have a method for parsing a string in this format but I'm not sure whether it's use of substring is the most efficient way of pprocessing the string, is there a more efficient way of processing strings in this fashion (repeatedly chopping off the front section):
Map<string, dynamic> fromString(String s){
Map<String, dynamic> _internal = new Map();
int start = 0;
while(start < s.length){
int end;
List<String> parts = new List<String>(); //0 is name, 1 is key, 2 is data length, 3 is data
for(var i = 0; i < 4; i++){
end = i < 3 ? s.indexOf(':') : num.parse(parts[2]);
parts[i] = s.substring(start, end);
start = i < 3 ? end + 1 : end;
}
var tranType = _tranTypesByKey[parts[1]]; //this is just a map to an object which has a function that can convert the data section of the string into an object
_internal[parts[0]] = tranType._fromStr(parts[3]);
}
return _internal;
}
I would try s.split(':') and process the resulting list.
If you do a lot of such operations you should consider creating benchmarks tests, try different techniques and compare them.
If you would still need this line
s = i < 3 ? s.substring(idx + 1) : s.substring(idx);
I would avoid creating a new substring in each iteration but instead just keep track of the next position.
You have to decide how important performance is relative to readability and maintainability of the code.
That said, you should not be cutting off the head of the string repeatedly. That is guaranteed to be inefficient - it'll take time that is quadratic in the number of records in your string, just creating those tail strings.
For parsing each field, you can avoid doing substrings on the length and type fields. For the length field, you can build the number yourself:
int index = ...;
// index points to first digit of length.
int length = 0;
int charCode = source.codeUnitAt(index++);
while (charCode != CHAR_COLON) {
length = 10 * length + charCode - 0x30;
charCode = source.codeUnitAt(index++);
}
// index points to the first character of content.
Since lengths are usually small integers (less than 2<<31), this is likely to be more efficient than creating a substring and calling int.parse.
The type field is a single ASCII character, so you could use codeUnitAt to get its ASCII value instead of creating a single-character string (and then your content interpretation lookup will need to switch on character code instead of character string).
For parsing content, you could pass the source string, start index and length instead of creating a substring. Then the boolean parser can also just read the code unit instead of the singleton character string, the string parser can just make the substring, and the number parser will likely have to make a substring too and call double.parse.
It would be convenient if Dart had a double.parseSubstring(source, [int from = 0, int to]) that could parse a substring as a double without creating the substring.
This is a question from one of the online coding challenge (which has completed).
I just need some logic for this as to how to approach.
Problem Statement:
We have two strings A and B with the same super set of characters. We need to change these strings to obtain two equal strings. In each move we can perform one of the following operations:
1. swap two consecutive characters of a string
2. swap the first and the last characters of a string
A move can be performed on either string.
What is the minimum number of moves that we need in order to obtain two equal strings?
Input Format and Constraints:
The first and the second line of the input contains two strings A and B. It is guaranteed that the superset their characters are equal.
1 <= length(A) = length(B) <= 2000
All the input characters are between 'a' and 'z'
Output Format:
Print the minimum number of moves to the only line of the output
Sample input:
aab
baa
Sample output:
1
Explanation:
Swap the first and last character of the string aab to convert it to baa. The two strings are now equal.
EDIT : Here is my first try, but I'm getting wrong output. Can someone guide me what is wrong in my approach.
int minStringMoves(char* a, char* b) {
int length, pos, i, j, moves=0;
char *ptr;
length = strlen(a);
for(i=0;i<length;i++) {
// Find the first occurrence of b[i] in a
ptr = strchr(a,b[i]);
pos = ptr - a;
// If its the last element, swap with the first
if(i==0 && pos == length-1) {
swap(&a[0], &a[length-1]);
moves++;
}
// Else swap from current index till pos
else {
for(j=pos;j>i;j--) {
swap(&a[j],&a[j-1]);
moves++;
}
}
// If equal, break
if(strcmp(a,b) == 0)
break;
}
return moves;
}
Take a look at this example:
aaaaaaaaab
abaaaaaaaa
Your solution: 8
aaaaaaaaab -> aaaaaaaaba -> aaaaaaabaa -> aaaaaabaaa -> aaaaabaaaa ->
aaaabaaaaa -> aaabaaaaaa -> aabaaaaaaa -> abaaaaaaaa
Proper solution: 2
aaaaaaaaab -> baaaaaaaaa -> abaaaaaaaa
You should check if swapping in the other direction would give you better result.
But sometimes you will also ruin the previous part of the string. eg:
caaaaaaaab
cbaaaaaaaa
caaaaaaaab -> baaaaaaaac -> abaaaaaaac
You need another swap here to put back the 'c' to the first place.
The proper algorithm is probably even more complex, but you can see now what's wrong in your solution.
The A* algorithm might work for this problem.
The initial node will be the original string.
The goal node will be the target string.
Each child of a node will be all possible transformations of that string.
The current cost g(x) is simply the number of transformations thus far.
The heuristic h(x) is half the number of characters in the wrong position.
Since h(x) is admissible (because a single transformation can't put more than 2 characters in their correct positions), the path to the target string will give the least number of transformations possible.
However, an elementary implementation will likely be too slow. Calculating all possible transformations of a string would be rather expensive.
Note that there's a lot of similarity between a node's siblings (its parent's children) and its children. So you may be able to just calculate all transformations of the original string and, from there, simply copy and recalculate data involving changed characters.
You can use dynamic programming. Go over all swap possibilities while storing all the intermediate results along with the minimal number of steps that took you to get there. Actually, you are going to calculate the minimum number of steps for every possible target string that can be obtained by applying given rules for a number times. Once you calculate it all, you can print the minimum number of steps, which is needed to take you to the target string. Here's the sample code in JavaScript, and its usage for "aab" and "baa" examples:
function swap(str, i, j) {
var s = str.split("");
s[i] = str[j];
s[j] = str[i];
return s.join("");
}
function calcMinimumSteps(current, stepsCount)
{
if (typeof(memory[current]) !== "undefined") {
if (memory[current] > stepsCount) {
memory[current] = stepsCount;
} else if (memory[current] < stepsCount) {
stepsCount = memory[current];
}
} else {
memory[current] = stepsCount;
calcMinimumSteps(swap(current, 0, current.length-1), stepsCount+1);
for (var i = 0; i < current.length - 1; ++i) {
calcMinimumSteps(swap(current, i, i + 1), stepsCount+1);
}
}
}
var memory = {};
calcMinimumSteps("aab", 0);
alert("Minimum steps count: " + memory["baa"]);
Here is the ruby logic for this problem, copy this code in to rb file and execute.
str1 = "education" #Sample first string
str2 = "cnatdeiou" #Sample second string
moves_count = 0
no_swap = 0
count = str1.length - 1
def ends_swap(str1,str2)
str2 = swap_strings(str2,str2.length-1,0)
return str2
end
def swap_strings(str2,cp,np)
current_string = str2[cp]
new_string = str2[np]
str2[cp] = new_string
str2[np] = current_string
return str2
end
def consecutive_swap(str,current_position, target_position)
counter=0
diff = current_position > target_position ? -1 : 1
while current_position!=target_position
new_position = current_position + diff
str = swap_strings(str,current_position,new_position)
# p "-------"
# p "CP: #{current_position} NP: #{new_position} TP: #{target_position} String: #{str}"
current_position+=diff
counter+=1
end
return counter,str
end
while(str1 != str2 && count!=0)
counter = 1
if str1[-1]==str2[0]
# p "cross match"
str2 = ends_swap(str1,str2)
else
# p "No match for #{str2}-- Count: #{count}, TC: #{str1[count]}, CP: #{str2.index(str1[count])}"
str = str2[0..count]
cp = str.rindex(str1[count])
tp = count
counter, str2 = consecutive_swap(str2,cp,tp)
count-=1
end
moves_count+=counter
# p "Step: #{moves_count}"
# p str2
end
p "Total moves: #{moves_count}"
Please feel free to suggest any improvements in this code.
Try this code. Hope this will help you.
public class TwoStringIdentical {
static int lcs(String str1, String str2, int m, int n) {
int L[][] = new int[m + 1][n + 1];
int i, j;
for (i = 0; i <= m; i++) {
for (j = 0; j <= n; j++) {
if (i == 0 || j == 0)
L[i][j] = 0;
else if (str1.charAt(i - 1) == str2.charAt(j - 1))
L[i][j] = L[i - 1][j - 1] + 1;
else
L[i][j] = Math.max(L[i - 1][j], L[i][j - 1]);
}
}
return L[m][n];
}
static void printMinTransformation(String str1, String str2) {
int m = str1.length();
int n = str2.length();
int len = lcs(str1, str2, m, n);
System.out.println((m - len)+(n - len));
}
public static void main(String[] args) {
Scanner scan = new Scanner(System.in);
String str1 = scan.nextLine();
String str2 = scan.nextLine();
printMinTransformation("asdfg", "sdfg");
}
}
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I saw this in an interview question ,
Given a sorting order string, you are asked to sort the input string based on the given sorting order string.
for example if the sorting order string is dfbcae
and the Input string is abcdeeabc
the output should be dbbccaaee.
any ideas on how to do this , in an efficient way ?
The Counting Sort option is pretty cool, and fast when the string to be sorted is long compared to the sort order string.
create an array where each index corresponds to a letter in the alphabet, this is the count array
for each letter in the sort target, increment the index in the count array which corresponds to that letter
for each letter in the sort order string
add that letter to the end of the output string a number of times equal to it's count in the count array
Algorithmic complexity is O(n) where n is the length of the string to be sorted. As the Wikipedia article explains we're able to beat the lower bound on standard comparison based sorting because this isn't a comparison based sort.
Here's some pseudocode.
char[26] countArray;
foreach(char c in sortTarget)
{
countArray[c - 'a']++;
}
int head = 0;
foreach(char c in sortOrder)
{
while(countArray[c - 'a'] > 0)
{
sortTarget[head] = c;
head++;
countArray[c - 'a']--;
}
}
Note: this implementation requires that both strings contain only lowercase characters.
Here's a nice easy to understand algorithm that has decent algorithmic complexity.
For each character in the sort order string
scan string to be sorted, starting at first non-ordered character (you can keep track of this character with an index or pointer)
when you find an occurrence of the specified character, swap it with the first non-ordered character
increment the index for the first non-ordered character
This is O(n*m), where n is the length of the string to be sorted and m is the length of the sort order string. We're able to beat the lower bound on comparison based sorting because this algorithm doesn't really use comparisons. Like Counting Sort it relies on the fact that you have a predefined finite external ordering set.
Here's some psuedocode:
int head = 0;
foreach(char c in sortOrder)
{
for(int i = head; i < sortTarget.length; i++)
{
if(sortTarget[i] == c)
{
// swap i with head
char temp = sortTarget[head];
sortTarget[head] = sortTarget[i];
sortTarget[i] = temp;
head++;
}
}
}
In Python, you can just create an index and use that in a comparison expression:
order = 'dfbcae'
input = 'abcdeeabc'
index = dict([ (y,x) for (x,y) in enumerate(order) ])
output = sorted(input, cmp=lambda x,y: index[x] - index[y])
print 'input=',''.join(input)
print 'output=',''.join(output)
gives this output:
input= abcdeeabc
output= dbbccaaee
Use binary search to find all the "split points" between different letters, then use the length of each segment directly. This will be asymptotically faster then naive counting sort, but will be harder to implement:
Use an array of size 26*2 to store the begin and end of each letter;
Inspect the middle element, see if it is different from the element left to it. If so, then this is the begin for the middle element and end for the element before it;
Throw away the segment with identical begin and end (if there are any), recursively apply this algorithm.
Since there are at most 25 "split"s, you won't have to do the search for more than 25 segemnts, and for each segment it is O(logn). Since this is constant * O(logn), the algorithm is O(nlogn).
And of course, just use counting sort will be easier to implement:
Use an array of size 26 to record the number of different letters;
Scan the input string;
Output the string in the given sorting order.
This is O(n), n being the length of the string.
Interview questions are generally about thought process and don't usually care too much about language features, but I couldn't resist posting a VB.Net 4.0 version anyway.
"Efficient" can mean two different things. The first is "what's the fastest way to make a computer execute a task" and the second is "what's the fastest that we can get a task done". They might sound the same but the first can mean micro-optimizations like int vs short, running timers to compare execution times and spending a week tweaking every millisecond out of an algorithm. The second definition is about how much human time would it take to create the code that does the task (hopefully in a reasonable amount of time). If code A runs 20 times faster than code B but code B took 1/20th of the time to write, depending on the granularity of the timer (1ms vs 20ms, 1 week vs 20 weeks), each version could be considered "efficient".
Dim input = "abcdeeabc"
Dim sort = "dfbcae"
Dim SortChars = sort.ToList()
Dim output = New String((From c In input.ToList() Select c Order By SortChars.IndexOf(c)).ToArray())
Trace.WriteLine(output)
Here is my solution to the question
import java.util.*;
import java.io.*;
class SortString
{
public static void main(String arg[])throws IOException
{
BufferedReader br=new BufferedReader(new InputStreamReader(System.in));
// System.out.println("Enter 1st String :");
// System.out.println("Enter 1st String :");
// String s1=br.readLine();
// System.out.println("Enter 2nd String :");
// String s2=br.readLine();
String s1="tracctor";
String s2="car";
String com="";
String uncom="";
for(int i=0;i<s2.length();i++)
{
if(s1.contains(""+s2.charAt(i)))
{
com=com+s2.charAt(i);
}
}
System.out.println("Com :"+com);
for(int i=0;i<s1.length();i++)
if(!com.contains(""+s1.charAt(i)))
uncom=uncom+s1.charAt(i);
System.out.println("Uncom "+uncom);
System.out.println("Combined "+(com+uncom));
HashMap<String,Integer> h1=new HashMap<String,Integer>();
for(int i=0;i<s1.length();i++)
{
String m=""+s1.charAt(i);
if(h1.containsKey(m))
{
int val=(int)h1.get(m);
val=val+1;
h1.put(m,val);
}
else
{
h1.put(m,new Integer(1));
}
}
StringBuilder x=new StringBuilder();
for(int i=0;i<com.length();i++)
{
if(h1.containsKey(""+com.charAt(i)))
{
int count=(int)h1.get(""+com.charAt(i));
while(count!=0)
{x.append(""+com.charAt(i));count--;}
}
}
x.append(uncom);
System.out.println("Sort "+x);
}
}
Here is my version which is O(n) in time. Instead of unordered_map, I could have just used a char array of constant size. i.,e. char char_count[256] (and done ++char_count[ch - 'a'] ) assuming the input strings has all ASCII small characters.
string SortOrder(const string& input, const string& sort_order) {
unordered_map<char, int> char_count;
for (auto ch : input) {
++char_count[ch];
}
string res = "";
for (auto ch : sort_order) {
unordered_map<char, int>::iterator it = char_count.find(ch);
if (it != char_count.end()) {
string s(it->second, it->first);
res += s;
}
}
return res;
}
private static String sort(String target, String reference) {
final Map<Character, Integer> referencesMap = new HashMap<Character, Integer>();
for (int i = 0; i < reference.length(); i++) {
char key = reference.charAt(i);
if (!referencesMap.containsKey(key)) {
referencesMap.put(key, i);
}
}
List<Character> chars = new ArrayList<Character>(target.length());
for (int i = 0; i < target.length(); i++) {
chars.add(target.charAt(i));
}
Collections.sort(chars, new Comparator<Character>() {
#Override
public int compare(Character o1, Character o2) {
return referencesMap.get(o1).compareTo(referencesMap.get(o2));
}
});
StringBuilder sb = new StringBuilder();
for (Character c : chars) {
sb.append(c);
}
return sb.toString();
}
In C# I would just use the IComparer Interface and leave it to Array.Sort
void Main()
{
// we defin the IComparer class to define Sort Order
var sortOrder = new SortOrder("dfbcae");
var testOrder = "abcdeeabc".ToCharArray();
// sort the array using Array.Sort
Array.Sort(testOrder, sortOrder);
Console.WriteLine(testOrder.ToString());
}
public class SortOrder : IComparer
{
string sortOrder;
public SortOrder(string sortOrder)
{
this.sortOrder = sortOrder;
}
public int Compare(object obj1, object obj2)
{
var obj1Index = sortOrder.IndexOf((char)obj1);
var obj2Index = sortOrder.IndexOf((char)obj2);
if(obj1Index == -1 || obj2Index == -1)
{
throw new Exception("character not found");
}
if(obj1Index > obj2Index)
{
return 1;
}
else if (obj1Index == obj2Index)
{
return 0;
}
else
{
return -1;
}
}
}