| 模型 | 模型答案 | 测试结果 |
|---|---|---|
| 金声玉亮2.0 | ```python def maximum_Sum(lst): max_sum = 0 for sublist in lst: current_sum = sum(sublist) if current_sum > max_sum: max_sum = current_sum return max_sum ``` [DONE] |
pass 测试用例：assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 |
| deepseekr1 | To solve this problem, we need to write a function that finds the maximum sum of elements from a list of lists. The function should iterate through each sublist, compute the sum of its elements, and keep track of the highest sum encountered. ### Approach 1. **Initialize Maximum Sum**: Start with the smallest possible value (negative infinity) to ensure any valid sum encountered will be larger. 2. **Iterate Through Sublists**: For each sublist in the input list, compute the sum of its elements. 3. **Update Maximum Sum**: Compare the computed sum of each sublist with the current maximum sum. If the computed sum is larger, update the maximum sum. 4. **Return Result**: After processing all sublists, return the maximum sum found. This approach ensures that we handle all possible cases, including lists with negative numbers, by initializing the maximum sum to negative infinity and updating it as we find larger sums. ### Solution Code ```python def maximum_Sum(list_of_lists): max_sum = float('-inf') for sublist in list_of_lists: current_sum = sum(sublist) if current_sum > max_sum: max_sum = current_sum return max_sum ``` ### Explanation - **Initialization**: The variable `max_sum` is initialized to negative infinity to handle cases where all sublist sums might be negative. - **Iteration and Sum Calculation**: For each sublist in the input list, the sum of its elements is calculated using Python's built-in `sum()` function. - **Comparison and Update**: Each calculated sum is compared against the current maximum sum. If it is larger, the maximum sum is updated. - **Result**: After all sublists have been processed, the maximum sum encountered is returned. This method efficiently computes the desired result with a time complexity of O(n), where n is the number of sublists, since each sublist is processed exactly once. |
pass 测试用例：assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 |
| gpto1 | ```python def maximum_Sum(list_of_lists): return max(sum(inner_list) for inner_list in list_of_lists) ``` |
pass 测试用例：assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 |
| GPT-4o | Sure, here is the implementation for the function to find the maximum sum of elements of list in a list of lists: ```python def maximum_Sum(list_of_lists): max_sum = max(map(sum, list_of_lists)) return max_sum # Test cases assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 ``` Explanation: - We use the `map` function to apply the `sum` function to each sublist in `list_of_lists`. - The `max` function is then used to find the maximum sum from the list of sums. This code should pass the provided test cases. |
pass 测试用例：assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 |
| llama3.1-70B-Instruct | def maximum_Sum(lists): return max(sum(sublist) for sublist in lists) |
pass 测试用例：assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 |
| llama3.1-405B-Instruct | def maximum_Sum(lists): return max(sum(lst) for lst in lists) |
pass 测试用例：assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 |
| DeepSeek-Coder-V2 | ```python def maximum_Sum(lst): max_sum = 0 for sublist in lst: current_sum = sum(sublist) if current_sum > max_sum: max_sum = current_sum return max_sum ``` [DONE] |
pass 测试用例：assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 |
| Qwen2-72B-Instruct | 'def maximum_Sum(list_of_lists): max_sum = 0 for lst in list_of_lists: current_sum = sum(lst) if current_sum > max_sum: max_sum = current_sum return max_sum' [DONE] Actually, there is a more efficient way to implement this function using list comprehension. Here is the updated function: [BEGIN] 'def maximum_Sum(list_of_lists): return max(sum(lst) for lst in list_of_lists)' [DONE] |
pass 测试用例：assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 |
| baichuan4 | To find the maximum sum of elements in a list of lists, you can use the following function: ```python def maximum_Sum(list_of_lists): return max(sum(sublist) for sublist in list_of_lists) ``` This function uses a generator expression inside the `max` function to calculate the sum of each sublist and then returns the maximum of those sums. Let's test it with the provided test cases: ```python assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 ``` All tests should pass successfully. |
pass 测试用例：assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 |
| doubao | 'def maximum_Sum(lst):
return max(sum(sub_list) for sub_list in lst)' [DONE] |
pass 测试用例：assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 |
| minimax | ```python def maximum_Sum(list_of_lists): return max(sum(inner_list) for inner_list in list_of_lists) # Test cases assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 ``` This function `maximum_Sum` calculates the sum of each list within the list of lists and returns the maximum sum found. The test cases check if the function correctly identifies the maximum sum for the given inputs. |
pass 测试用例：assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 |
| kimi | ```python def similar_elements(test_tup1, test_tup2): res = tuple(sorted(set(test_tup1) & set(test_tup2))) return res # Test cases assert similar_elements((3, 4, 5, 6),(5, 7, 4, 10)) == (4, 5) assert similar_elements((1, 2, 3, 4),(5, 4, 3, 7)) == (3, 4) assert similar_elements((11, 12, 14, 13),(17, 15, 14, 13)) == (13, 14) def is_not_prime(n): if n <= 1: return True for i in range(2, int(n**0.5) + 1): if n % i == 0: return True return False # Test cases assert is_not_prime(2) == False assert is_not_prime(10) == True assert is_not_prime(35) == True import heapq as hq def heap_queue_largest(nums, n): largest_nums = hq.nlargest(n, nums) return largest_nums # Test cases assert heap_queue_largest([25, 35, 22, 85, 14, 65, 75, 22, 58], 3) == [85, 75, 65] assert heap_queue_largest([25, 35, 22, 85, 14, 65, 75, 22, 58], 2) == [85, 75] assert heap_queue_largest([25, 35, 22, 85, 14, 65, 75, 22, 58], 5) == [85, 75, 65, 58, 35] def maximum_Sum(list_of_lists): max_sum = 0 for lst in list_of_lists: max_sum += sum(lst) return max_sum # Test cases assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 ``` These functions should pass the provided test cases. The `similar_elements` function finds the common elements between two tuples and returns them as a sorted tuple. The `is_not_prime` function checks if a number is not prime by testing divisibility by all numbers from 2 up to the square root of the number. The `heap_queue_largest` function uses the `heapq` module to find the `n` largest numbers in a list. Finally, the `maximum_Sum` function calculates the sum of all elements in a list of lists. |
wrong_answer 测试用例：assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 |
| wenxinyiyan | Here are the solutions to the tasks you provided: 1. Finding similar elements from two tuple lists: ```python def similar_elements(test_tup1, test_tup2): res = tuple(set(test_tup1) & set(test_tup2)) return res ``` This function takes two tuple lists as input and returns a tuple containing the similar elements from both lists. It uses the set intersection operation (`&`) to find the common elements and then converts the result back to a tuple. 2. Identifying non-prime numbers: ```python import math def is_not_prime(n): if n < 2: return True for i in range(2, int(math.sqrt(n)) + 1): if n % i == 0: return True return False ``` This function takes an integer `n` as input and returns `True` if `n` is not a prime number, and `False` otherwise. It checks if `n` is less than 2 (which are not considered prime) and then iterates from 2 to the square root of `n` to check for any divisors. If a divisor is found, it returns `True` indicating that `n` is not prime. Note: In your provided code, the function was returning `True` for non-prime numbers, so I assumed that's the desired behavior. However, the function name `is_not_prime` suggests that it should return `True` if the number is not prime, which is what my code does. 3. Finding the largest integers from a list using the heap queue algorithm: ```python import heapq as hq def heap_queue_largest(nums, n): largest_nums = hq.nlargest(n, nums) return largest_nums ``` This function takes a list of numbers `nums` and an integer `n` as input and returns a list containing the `n` largest numbers from `nums`. It uses the `heapq.nlargest()` function from the `heapq` module, which implements the heap queue algorithm to efficiently find the largest elements. 4. Finding the maximum sum of elements of list in a list of lists: ```python def maximum_Sum(list_of_lists): max_sum = 0 for sublist in list_of_lists: current_sum = sum(sublist) if current_sum > max_sum: max_sum = current_sum return max_sum ``` This function takes a list of lists `list_of_lists` as input and returns the maximum sum of elements from any sublist. It iterates over each sublist, calculates the sum of its elements using the `sum()` function, and updates the `max_sum` variable if the current sum is greater than the previous maximum. Finally, it returns the maximum sum found. |
failed 测试用例：assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 |
| zhipu | To solve this task, we need to write a function `maximum_Sum` that takes a list of lists as input and returns the maximum sum of elements from any single list within the input. We can achieve this by iterating through each list, calculating its sum, and keeping track of the maximum sum encountered. Here is the implementation of the function: ```python def maximum_Sum(list_of_lists): max_sum = 0 for lst in list_of_lists: current_sum = sum(lst) if current_sum > max_sum: max_sum = current_sum return max_sum ``` Now, let's verify that this function passes the given tests: ```python assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 print("All tests passed!") ``` When you run this code, it should output "All tests passed!" indicating that the function works correctly for the provided test cases. ### Complete Code ```python def maximum_Sum(list_of_lists): max_sum = 0 for lst in list_of_lists: current_sum = sum(lst) if current_sum > max_sum: max_sum = current_sum return max_sum # Test cases assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 print("All tests passed!") ``` This function iterates through each list in the input, calculates the sum of each list, and updates the maximum sum encountered. The final result is the maximum sum of any single list within the input list of lists. |
pass 测试用例：assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 |
| gpto1 | ```python def maximum_Sum(list_of_lists): return max(sum(inner_list) for inner_list in list_of_lists) ``` |
pass 测试用例：assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 |
| deepseekv3 | To solve this problem, we need to write a function that takes a list of lists and returns the maximum sum of the elements of any individual list within the list of lists. Here's how we can implement this: ```python def maximum_Sum(list_of_lists): max_sum = 0 for sublist in list_of_lists: current_sum = sum(sublist) if current_sum > max_sum: max_sum = current_sum return max_sum # Test cases assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 ``` ### Explanation: 1. **Function Definition**: The function `maximum_Sum` takes a single argument `list_of_lists`, which is a list containing multiple lists of integers. 2. **Initialize `max_sum`**: We start by initializing `max_sum` to 0. This variable will keep track of the highest sum encountered as we iterate through the lists. 3. **Iterate Through Sublists**: We loop through each sublist in `list_of_lists`. 4. **Calculate Current Sum**: For each sublist, we calculate the sum of its elements using the `sum()` function. 5. **Update `max_sum`**: If the current sum is greater than `max_sum`, we update `max_sum` with the current sum. 6. **Return `max_sum`**: After iterating through all sublists, we return the `max_sum`. ### Test Cases: - For the input `[[1,2,3],[4,5,6],[10,11,12],[7,8,9]]`, the maximum sum is 33 (from the sublist `[10,11,12]`). - For the input `[[0,1,1],[1,1,2],[3,2,1]]`, the maximum sum is 6 (from the sublist `[3,2,1]`). - For the input `[[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]`, the maximum sum is 19 (from the sublist `[6,4,8]`). This function efficiently finds the maximum sum of elements in any sublist within a list of lists. |
pass 测试用例：assert maximum_Sum([[1,2,3],[4,5,6],[10,11,12],[7,8,9]]) == 33 assert maximum_Sum([[0,1,1],[1,1,2],[3,2,1]]) == 6 assert maximum_Sum([[0,1,3],[1,2,1],[9,8,2],[0,1,0],[6,4,8]]) == 19 |