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In this approach, we establish a one-to-one mapping for each letter in the pattern to letters in each word. To do this, we use two maps or dictionaries: one for mapping pattern to word letters and another for mapping word to pattern letters. Both maps are used to ensure that the mapping is bijective (i.e., one-to-one).
Time Complexity: O(n * m), where n is the number of words and m is the word length.
Space Complexity: O(m), for the maps storing character mappings.
1def matchesPattern(word, pattern):
2 mapPtoW, mapWtoP = {}, {}
3 for w, p in zip(word, pattern):
4 if p not in mapPtoW and w not in mapWtoP:
5 mapPtoW[p] = w
6 mapWtoP[w] = p
7 elif mapPtoW.get(p) != w or mapWtoP.get(w) != p:
8 return False
9 return True
10
11
12def findAndReplacePattern(words, pattern):
13 return [word for word in words if matchesPattern(word, pattern)]
14This Python code leverages dictionaries to store character mappings from pattern to word and vice versa. The function matchesPattern is a helper used within findAndReplacePattern to filter out non-matching words.
In this approach, we map each character of the string to its first occurrence index in the string. This creates a unique encoding pattern for comparison. Two strings match if they have the same encoding pattern.
Time Complexity: O(n * m), where n is the number of words and m is the word length.
Space Complexity: O(m), for storing encoded strings and maps.
1using System.Collections.Generic;
using System.Linq;
public class PatternMatcher {
private string EncodePattern(string str) {
var map = new Dictionary<char, int>();
var encoded = new List<int>();
int index = 0;
foreach (char c in str) {
if (!map.ContainsKey(c)) {
map[c] = index++;
}
encoded.Add(map[c]);
}
return string.Join("", encoded);
}
public List<string> FindAndReplacePattern(string[] words, string pattern) {
string encodedPattern = EncodePattern(pattern);
return words.Where(word => EncodePattern(word) == encodedPattern).ToList();
}
}
Utilizing string encoding based on initial occurrences, this C# code identifies matching words by comparing encoded patterns of words and the pattern itself.