387. First Unique Character in a String QuestionEditorial Solution

本文介绍了一种使用C语言实现的方法,用于找出字符串中第一个不重复的字符并返回其索引位置。通过创建一个长度为26的数组来记录每个小写字母出现的次数,最终遍历字符串找到第一个只出现一次的字符。

Given a string, find the first non-repeating character in it and return it’s index. If it doesn’t exist, return -1.

Examples:

s = “leetcode”
return 0.

s = “loveleetcode”,
return 2.
Note: You may assume the string contain only lowercase letters.

思路,统计每个每个字母出现的次数到一个数组中,数组大小为26个小写字母。

int firstUniqChar(char* s) {

    int i;
    char *str;

    int count[26];
    memset(count, 0, 26 * sizeof(int));

    for(str = s; *str != '\0'; str++) {
       i = *str - 'a';
       count[i]++;
    }

    for(str = s; *str != '\0'; str++) {
       i = *str - 'a';
       if(count[i] == 1)
        return str - s;
    }

    return -1;
}
翻译并整理latex渲染: First, let's see how many zebra-Like numbers less than or equal to 1018 exist. It turns out there are only 30 of them, and based on some zebra-like number zi , the next one can be calculated using the formula zi+1=4⋅zi+1 . Then, we have to be able to quickly calculate the zebra value for an arbitrary number x . Since each subsequent zebra-like number is approximately 4 times larger than the previous one, intuitively, it seems like a greedy algorithm should be optimal: for any number x , we can determine its zebra value by subtracting the largest zebra-like number that does not exceed x , until x becomes 0 . Let's prove the correctness of the greedy algorithm: Assume that y is the smallest number for which the greedy algorithm does not work, meaning that in the optimal decomposition of y into zebra-like numbers, the largest zebra-like number zi that does not exceed y does not appear at all. If the greedy algorithm works for all numbers less than y , then in the decomposition of the number y , there must be at least one number zi&minus;1 . And since y&minus;zi&minus;1 can be decomposed greedily and will contain at least 3 numbers zi&minus;1 , we will end up with at least 4 numbers zi&minus;1 in the decomposition. Moreover, there will be at least 5 numbers in the decomposition because 4⋅zi&minus;1<zi , which means it is also less than y . Therefore, if the fifth number is 1 , we simply combine 4⋅zi&minus;1 with 1 to obtain zi ; otherwise, we decompose the fifth number into 4 smaller numbers plus 1 , and we also combine this 1 with 4⋅zi&minus;1 to get zi . Thus, the new decomposition of the number y into zebra-like numbers will have no more numbers than the old one, but it will include the number zi — the maximum zebra-like number that does not exceed y . This means that y can be decomposed greedily. We have reached a contradiction; therefore, the greedy algorithm works for any positive number. Now, let's express the greedy decomposition of the number x in a more convenient form. We will represent the decomposition as a string s of length 30 consisting of digits, where the i -th character will denote how many zebra numbers zi are present in this decomposition. Let's take a closer look at what such a string might look like: si&isin;{0,1,2,3,4} ; if si=4 , then for any j<i , the character sj=0 (this follows from the proof of the greedy algorithm). Moreover, any number generates a unique string of this form. This is very similar to representing a number in a new numeric system, which we will call zebroid. In summary, the problem has been reduced to counting the number of numbers in the interval [l,r] such that the sum of the digits in the zebroid numeral system equals x . This is a standard problem that can be solved using dynamic programming on digits. Instead of counting the suitable numbers in the interval [l,r] , we will count the suitable numbers in the intervals [1,l] and [1,r] and subtract the first from the second to get the answer. Let dp[ind][sum][num_less_m][was_4] be the number of numbers in the interval [1,m] such that: they have ind+1 digits; the sum of the digits equals sum ; num_less_m=0 if the prefix of ind+1 digits of the number m is lexicographically greater than these numbers, otherwise num_less_m=1 ; was_4=0 if there has not been a 4 in the ind+1 digits of these numbers yet, otherwise was_4=1 . Transitions in this dynamic programming are not very difficult — they are basically appending a new digit at the end. The complexity of the solution is O(log2A) , if we estimate the number of zebra-like numbers up to A=1018 as logA .
最新发布
08-26
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