chat

🔍

question:You are given two sorted arrays `arr1` and `arr2`, each containing `n` integers. Your task is to merge these two arrays into a single sorted array without using any additional space for another array. Instead, merge the second array into the first one, modifying the first array in-place to include all elements from both arrays. # Task Write a function `merge_arrays(arr1, arr2)` that takes two lists of integers `arr1` and `arr2`, and modifies `arr1` in-place to contain all elements from both arrays in sorted order. The function returns nothing. # Examples: `arr1 = [1, 3, 5]` `arr2 = [2, 4, 6]` `merge_arrays(arr1, arr2)` `arr1` should become `[1, 2, 3, 4, 5, 6]` `arr1 = [1, 2, 6]` `arr2 = [3, 4, 5]` `merge_arrays(arr1, arr2)` `arr1` should become `[1, 2, 3, 4, 5, 6]` # Notes - The first array `arr1` has enough length to hold all elements from both `arr1` and `arr2`. - You can assume that the given arrays `arr1` and `arr2` will always be initially sorted in ascending order. - The second array `arr2` should be considered as an "append-only" extension of the first array `arr1`.

answer:def merge_arrays(arr1, arr2): Merge second sorted array arr2 into the first sorted array arr1 in-place. n = len(arr1) - len(arr2) # The original length of arr1 m = len(arr2) # Start merging from the end i = n - 1 # Index of last element in initial arr1 j = m - 1 # Index of last element in arr2 k = n + m - 1 # Index of last position in the merged array (i.e., arr1) # Merge in reverse order while i >= 0 and j >= 0: if arr1[i] > arr2[j]: arr1[k] = arr1[i] i -= 1 else: arr1[k] = arr2[j] j -= 1 k -= 1 # If there are remaining elements in arr2, copy them while j >= 0: arr1[k] = arr2[j] k -= 1 j -= 1

question:In a distant galaxy, there exists a network of space stations connected by bidirectional hyper-routes. Each space station is represented as a node, and each hyper-route is represented as an edge with a certain travel time. Space travelers want to explore this network efficiently, starting from a given space station, visiting all the stations exactly once, and returning to the starting station. This is known as the Traveling Space Traveler problem. However, due to space-time anomalies, the travel time between some space stations can change dynamically. Travelers must be prepared to adapt their travel plans based on the latest travel times. -----Input----- The first line of the input contains an integer T denoting the number of test cases. The description of T test cases follows. - The first line of each test case contains an integer N denoting the number of space stations. - The second line of each test case contains an integer M denoting the number of hyper-routes. - The next M lines, each line contains 3 space-separated integers U, V, and W denoting a hyper-route between space station U and space station V with travel time W. - The last line of each test case contains an integer S denoting the starting space station for the traveler. -----Output----- For each test case, output a single line containing the minimum travel time needed to visit all the space stations exactly once and return to the starting station S. If it is not possible to visit all space stations and return to the starting station, print -1. -----Constraints----- - 1 ≤ T ≤ 5 - 2 ≤ N ≤ 10 - 1 ≤ M ≤ N*(N-1)/2 - 1 ≤ U, V ≤ N - 1 ≤ W ≤ 100 - The input guarantees that there are no duplicate hyper-routes and no self-loops. -----Example----- Input: 2 4 6 1 2 10 1 3 15 1 4 20 2 3 35 2 4 25 3 4 30 1 3 3 1 2 5 2 3 10 3 1 5 1 Output: 80 20 -----Explanation----- Example case 1. Starting at space station 1, the traveler can visit the stations in the order 1 -> 2 -> 3 -> 4 -> 1 with a total travel time of 10 + 35 + 30 + 5 = 80 units. Example case 2. Starting at space station 1, the traveler can visit the stations in the order 1 -> 2 -> 3 -> 1 with a total travel time of 5 + 10 + 5 = 20 units.

answer:from itertools import permutations def tsp_min_travel_time(n, m, edges, start): graph = {i: {} for i in range(1, n + 1)} for u, v, w in edges: graph[u][v] = w graph[v][u] = w all_nodes = set(range(1, n + 1)) all_nodes.remove(start) min_travel_time = float('inf') for perm in permutations(all_nodes): total_time = 0 current_node = start for next_node in perm: total_time += graph[current_node].get(next_node, float('inf')) current_node = next_node total_time += graph[current_node].get(start, float('inf')) if total_time < min_travel_time: min_travel_time = total_time return min_travel_time if min_travel_time < float('inf') else -1 def solve_tsp_problem(test_cases): results = [] for case in test_cases: n, m, edges, start = case min_time = tsp_min_travel_time(n, m, edges, start) results.append(min_time) return results

question:Given an array of integers nums and an integer k, write a function to determine if there are two distinct indices i and j in the array such that nums[i] == nums[j] and the absolute difference between i and j is at most k. Example 1: Input: nums = [1,2,3,1], k = 3 Output: True Explanation: There is a pair of values (nums[0], nums[3]) where nums[0] == nums[3] and the difference between 0 and 3 is 3, which is at most k. Example 2: Input: nums = [1,0,1,1], k = 1 Output: True Explanation: There is a pair of values (nums[2], nums[3]) where nums[2] == nums[3] and the difference between 2 and 3 is 1, which is at most k. Example 3: Input: nums = [1,2,3,1,2,3], k = 2 Output: False Explanation: There is no pair of values in nums that meets the criteria. Note: The input array only contains integers. The length of the given array is in the range [1, 10,000]. The value of k is in the range [1, 10,000].

answer:def contains_nearby_duplicate(nums, k): Determine if there are two distinct indices i and j in the array nums such that nums[i] == nums[j] and the absolute difference between i and j is at most k. index_map = {} for i, num in enumerate(nums): if num in index_map and i - index_map[num] <= k: return True index_map[num] = i return False

question:Write a program to simulate a basic bank account management system. Your program should be able to handle the following operations: 1. Create a new account with a unique account number, initial balance, and account holder's name. 2. Deposit a specified amount into a particular account. 3. Withdraw a specified amount from a particular account, ensuring the account has sufficient funds. 4. Check the balance of a particular account by the account number. Use the following constraints and requirements: - Account number should be unique and a positive integer. - Initial balance and transactions (deposits and withdrawals) should be non-negative numbers. - Ensure that withdrawals do not exceed the current balance. - Provide appropriate error messages for invalid operations or inputs. Write appropriate methods to handle the above functionalities and demonstrate the creation and manipulation of at least two accounts in your main method.

answer:class BankAccount: accounts = {} def __init__(self, account_number, holder_name, initial_balance=0): if account_number <= 0 or initial_balance < 0: raise ValueError("Account number must be positive, and initial balance must be non-negative.") if account_number in BankAccount.accounts: raise ValueError("Account number must be unique.") self.account_number = account_number self.holder_name = holder_name self.balance = initial_balance BankAccount.accounts[account_number] = self def deposit(self, amount): if amount < 0: raise ValueError("Deposit amount must be non-negative.") self.balance += amount def withdraw(self, amount): if amount < 0: raise ValueError("Withdrawal amount must be non-negative.") if amount > self.balance: raise ValueError("Insufficient funds.") self.balance -= amount def check_balance(self): return self.balance