algorithm

问题 I've written a piece of java code that when given an array (arrayX), works out the prefix averages of that array and outputs them in another array (arrayA). I am supposed to count the primitive operations and calculate the Big-O notation (which i'm guessing is the overall number of calculations). I have included the java code and what I believe to be the number of primitive operations next to each line, but I am unsure whether I have counted them correctly. Thanks in advance and sorry for my

问题 Assuming I have two arrays A and B (Both with equal number of elements) int A[] = {40,50,70}; int B[] = {80,60,45}; I have to rearrange array A in such a way that maximum number of elements in Array A are greater than their respective elements in array B. In this case, rearranging A as {40,70,50} would yield the required result. What would be the most optimal way of going this? 回答1: I would use something like: std::vector<int> f(std::vector<int> A, const std::vector<int>& B) { std::vector<std

问题 Problem Statement: Given a matrix of people(denoted by small alphabets) and bikes(denoted by capital alphabets), find the nearest bike for a given person. How will you change your solution if you have to find bikes for a set of people? (assuming multiple bikes can be at the same distance from 1 person)? I know Dijkstra's algorithm and Bellman Ford's algorithm, but curious about the implementation here. Or can it be solved by BFS(Breadth First Search)? 回答1: To assign a single bike to a single

问题 Problem Statement: Given a matrix of people(denoted by small alphabets) and bikes(denoted by capital alphabets), find the nearest bike for a given person. How will you change your solution if you have to find bikes for a set of people? (assuming multiple bikes can be at the same distance from 1 person)? I know Dijkstra's algorithm and Bellman Ford's algorithm, but curious about the implementation here. Or can it be solved by BFS(Breadth First Search)? 回答1: To assign a single bike to a single

问题 I would like your opinion on the time and space complexity of this algorithm I implemented (in Python) to calculate the complexity of algorithm to print all valid (i.e., properly opened and closed) combinations of n-pairs of parentheses (see all valid combinations of n-pair of parenthesis) def find_par_n(n): s = set(["()"]) for i in range(2, n + 1): set_to_add = set() for str_ in s: set_temp = set() ana = set() for j in range(len(str_) + 1): str_c = str_[0:j] + '(' + str_[j:] if str_c in ana:

问题 I need a data structure in c++ STL for performing insertion, searching and retrieval of kth element in log(n) (Note: k is a variable and not a constant) I have a class like class myClass{ int id; //other variables }; and my comparator is just based on this id and no two elements will have the same id. Is there a way to do this using STL or I've to write log(n) functions manually to maintain the array in sorted order at any point of time? 回答1: Afaik, there is no such datastructure. Of course,

问题 I have a matrix, for example, 5x5. [,1] [,2] [,3] [,4] [,5] [1,] 22 -2 -2 -2 2 [2,] -2 22 2 2 2 [3,] -2 2 22 2 2 [4,] -2 2 2 22 2 [5,] 2 2 2 2 22. As you can see, the matrix is symmetric. Above the main diagonal, there are 4+3+2+1=10 positions, and I find via combn all the possible (permutation) matrices, which have (-2) 3 times in these 10 positions. That means 10!/3!*7!=120 matrices. But some of them are equivalent. So,my problem is how to find the non-equivalent matrices from the 120. I am

问题 I have a matrix, for example, 5x5. [,1] [,2] [,3] [,4] [,5] [1,] 22 -2 -2 -2 2 [2,] -2 22 2 2 2 [3,] -2 2 22 2 2 [4,] -2 2 2 22 2 [5,] 2 2 2 2 22. As you can see, the matrix is symmetric. Above the main diagonal, there are 4+3+2+1=10 positions, and I find via combn all the possible (permutation) matrices, which have (-2) 3 times in these 10 positions. That means 10!/3!*7!=120 matrices. But some of them are equivalent. So,my problem is how to find the non-equivalent matrices from the 120. I am

问题 I'm trying to implement an AI for Tic Tac Toe that is smart enough to never lose. I've tried two different algorithms but the AI still makes mistakes. I started with this minimax alpha-beta pruning algorithm. Here's a live demo: http://iioengine.com/ttt/minimax.htm It runs without error, but if you take the bottom left corner first, then either of the other two squares on the bottom row - the AI doesn't see that coming. I'm sure this isn't a flaw in the minimax algorithm - can anyone see an

问题 I'm trying to implement an AI for Tic Tac Toe that is smart enough to never lose. I've tried two different algorithms but the AI still makes mistakes. I started with this minimax alpha-beta pruning algorithm. Here's a live demo: http://iioengine.com/ttt/minimax.htm It runs without error, but if you take the bottom left corner first, then either of the other two squares on the bottom row - the AI doesn't see that coming. I'm sure this isn't a flaw in the minimax algorithm - can anyone see an