357. Count Numbers with Unique Digits

本文介绍了一种算法解决方案,用于解决LeetCode上Count Numbers with Unique Digits的问题。该问题要求统计在指定范围内没有重复数字的所有整数的数量。文章通过排列组合的方法进行解答,并提供了一个高效的C++实现。

题目:Count Numbers with Unique Digits

原题链接:https://leetcode.com/problems/count-numbers-with-unique-digits/
Given a non-negative integer n, count all numbers with unique digits, x, where 0 ≤ x < 10^n.
Example:
Given n = 2, return 91. (The answer should be the total numbers in the range of 0 ≤ x < 100, excluding [11,22,33,44,55,66,77,88,99])
给出一个非负整数n,统计从0到10的n次方(左闭右开区间)中所有满足每以为都和其他位不相同的数字的个数。
例如n等于,则返回91。

这是一道排列组合,把所有范围内的数按照一位数,二位数,三位数这样来讨论,其中i位数一共有 9 * 9 * 8 *……这么多种可能,其中最高位不能是0,所以最高位是9种,然后从次高位开始往下依次是9种,8种。。。一直到1。注意,要是位数大于10的话是肯定会有重复的数字的,所以其实如果n >= 10,结果应该是一样的。然后把从一位数到2位数到n(或者十)位数的都统计一下再相加就可以了,代码如下:

class Solution {
public:
    // 这个函数统计n位数的情况下应该会有多少符合条件的组合
    int getTemp(int n) { 
        int temp = 9;
        int i = 0;
        while(--n) {
            temp *= (9 - i);
            i++;
        }
        return temp;
    }
    int countNumbersWithUniqueDigits(int n) {
        if (n == 0) return 1;
        int ans = 1;
        for(int i = 1; i <= n; ++i) {
            ans += getTemp(i);
        }
        return ans;
    }
};
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−1 . And since y−zi−1 can be decomposed greedily and will contain at least 3 numbers zi−1 , we will end up with at least 4 numbers zi−1 in the decomposition. Moreover, there will be at least 5 numbers in the decomposition because 4⋅zi−1<zi , which means it is also less than y . Therefore, if the fifth number is 1 , we simply combine 4⋅zi−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−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∈{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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