金声玉亮2.0模型评测报告

问题

You are an expert Python programmer, and here is your task: Write a function to find the similar elements from the given two tuple lists. Your code should pass these tests:

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)

[BEGIN]
'def similar_elements(test_tup1, test_tup2):
res = tuple(set(test_tup1) & set(test_tup2))
return (res)'
[DONE]

You are an expert Python programmer, and here is your task: Write a python function to identify non-prime numbers. Your code should pass these tests:

assert is_not_prime(2) == False
assert is_not_prime(10) == True
assert is_not_prime(35) == True

[BEGIN]
'import math
def is_not_prime(n):
result = False
for i in range(2,int(math.sqrt(n)) + 1):
if n % i == 0:
result = True
return result'
[DONE]

You are an expert Python programmer, and here is your task: Write a function to find the largest integers from a given list of numbers using heap queue algorithm. Your code should pass these tests:

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]

[BEGIN]
'import heapq as hq
def heap_queue_largest(nums,n):
largest_nums = hq.nlargest(n, nums)
return largest_nums'
[DONE]

You are an expert Python programmer, and here is your task: Write a function to sort a given matrix in ascending order according to the sum of its rows. Your code should pass these tests:

assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]]
assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]]
assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]

[BEGIN]

答案

模型	模型答案	测试结果
金声玉亮2.0	```python def sort_matrix(matrix): # Calculate the sum of each row and pair it with the row index row_sums = [(sum(row), i) for i, row in enumerate(matrix)] # Sort the row sums based on the sum row_sums.sort(key=lambda x: x[0]) # Reconstruct the matrix based on the sorted row indices sorted_matrix = [matrix[i] for _, i in row_sums] return sorted_matrix ``` [DONE]	pass 测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]
deepseekr1	To solve this problem, we need to sort a given matrix in ascending order based on the sum of each row. The goal is to return a new matrix where the rows are ordered from the smallest sum to the largest sum. ### Approach The approach to solve this problem involves the following steps: 1. Calculate the Sum of Each Row: For each row in the matrix, compute the sum of its elements. 2. Sort Rows by Sum: Use the computed sums to sort the rows in ascending order. The sorting should maintain the stability of rows with equal sums, meaning their original order is preserved if their sums are the same. To achieve this efficiently, we can utilize Python's built-in `sorted` function, which allows specifying a custom key for sorting. The key here will be the sum of each row. This approach ensures that the rows are sorted based on their sums in ascending order. ### Solution Code ```python def sort_matrix(matrix): return sorted(matrix, key=lambda row: sum(row)) ``` ### Explanation 1. Calculate Row Sums: The `sorted` function uses a lambda function `lambda row: sum(row)` as the key. This lambda function computes the sum of each row, which is then used to determine the order of rows. 2. Sorting: The `sorted` function sorts the rows based on their sums. By default, `sorted` sorts in ascending order, which matches the requirement of the problem. 3. Return Sorted Matrix: The sorted list of rows is returned as the new matrix. This approach efficiently sorts the matrix rows using built-in functions, ensuring clarity and conciseness in the solution. The time complexity of this approach is O(n log n), where n is the number of rows in the matrix, due to the sorting step. This is efficient and suitable for typical use cases.	pass 测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]
gpto1	'def sort_matrix(matrix): return sorted(matrix, key=sum)'	failed 测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]
GPT-4o	```python def sort_matrix(matrix): # Sort the matrix based on the sum of rows sorted_matrix = sorted(matrix, key=sum) return sorted_matrix ``` To ensure that the function works correctly, let's test it against the provided assertions: ```python # Test cases assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]]) == [[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]]) == [[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]]) == [[2, 1, 4], [6, 4, 3], [5, 8, 9]] print("All tests passed!") ``` This code defines the `sort_matrix` function and tests it with the provided test cases to ensure correctness.	pass 测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]
llama3.1-70B-Instruct	def sort_matrix(matrix): return sorted(matrix, key=sum)	pass 测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]
llama3.1-405B-Instruct	def sort_matrix(matrix): return sorted(matrix, key=sum)	pass 测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]
DeepSeek-Coder-V2	```python def sort_matrix(matrix): # Calculate the sum of each row and pair it with the row index row_sums = [(sum(row), i) for i, row in enumerate(matrix)] # Sort the row sums based on the sum row_sums.sort(key=lambda x: x[0]) # Reconstruct the matrix based on the sorted row indices sorted_matrix = [matrix[i] for _, i in row_sums] return sorted_matrix ``` [DONE]	pass 测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]
Qwen2-72B-Instruct	'def sort_matrix(matrix): row_sums = [(sum(row), row) for row in matrix] sorted_rows = sorted(row_sums, key=lambda x: x[0]) sorted_matrix = [row for _, row in sorted_rows] return sorted_matrix' [DONE]	pass 测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]
baichuan4	To sort a given matrix in ascending order according to the sum of its rows, you can use the following function: ```python def sort_matrix(matrix): # Calculate the sum of each row row_sums = [sum(row) for row in matrix] # Create a sorted list of row indices based on the row sums sorted_indices = sorted(range(len(matrix)), key=lambda i: row_sums[i]) # Create a new matrix with the rows in the sorted order sorted_matrix = [matrix[i] for i in sorted_indices] return sorted_matrix ``` This function first calculates the sum of each row in the input matrix. Then, it creates a sorted list of row indices based on these sums. Finally, it creates a new matrix with the rows in the sorted order. Let's test the function with the provided test cases: ```python assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]]) == [[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]]) == [[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5, 8, 9], [6, 4, 3], [2, 1, 4]]) == [[2, 1, 4], [6, 4, 3], [5, 8, 9]] ``` The function passes all the tests, so it seems to be working correctly.	pass 测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]
doubao	def sort_matrix(matrix): return sorted(matrix, key=sum) [DONE]	pass 测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]
minimax	```python def sort_matrix(matrix): # Sort the matrix based on the sum of each row matrix.sort(key=lambda row: sum(row)) return matrix # Test cases assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]]) == [[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]]) == [[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5, 8, 9], [6, 4, 3], [2, 1, 4]]) == [[2, 1, 4], [6, 4, 3], [5, 8, 9]] ``` This function `sort_matrix` takes a matrix (a list of lists) as input and returns a new matrix sorted in ascending order based on the sum of its rows. The `sort` method is used with a key function that calculates the sum of each row. The test cases check if the function correctly sorts the matrices as specified.	pass 测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]
kimi	Sure, let's write the functions one by one. 1. Function to find similar elements from two tuple lists: ```python def similar_elements(test_tup1, test_tup2): res = tuple(sorted(set(test_tup1) & set(test_tup2))) return res ``` 2. Function to identify non-prime numbers: ```python import math def is_not_prime(n): if n <= 1: return True for i in range(2, int(math.sqrt(n)) + 1): if n % i == 0: return True return False ``` 3. Function to find the largest integers from a given list of numbers using heap queue algorithm: ```python import heapq def heap_queue_largest(nums, n): largest_nums = heapq.nlargest(n, nums) return largest_nums ``` 4. Function to sort a given matrix in ascending order according to the sum of its rows: ```python def sort_matrix(matrix): return sorted(matrix, key=lambda x: sum(x)) ``` Now let's test the functions: ```python # Test for similar_elements function 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) # Test for is_not_prime function assert is_not_prime(2) == False assert is_not_prime(10) == True assert is_not_prime(35) == True # Test for heap_queue_largest function 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] # Test for sort_matrix function assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]]) == [[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]]) == [[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]]) == [[2, 1, 4], [6, 4, 3], [5, 8, 9]] ``` If you run these tests, they should all pass without any assertion errors.	failed 测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]
wenxinyiyan	'def sort_matrix(matrix): sorted_matrix = sorted(matrix, key=lambda x: sum(x)) return sorted_matrix' [DONE] Explanation: The `sort_matrix` function takes a matrix (list of lists) as input and returns a new matrix with its rows sorted in ascending order based on the sum of their elements. The `sorted` function is used to sort the rows, and the `key` parameter is set to a lambda function that calculates the sum of each row. This ensures that the rows are sorted according to their sums. Note: The provided code snippets are enclosed in single quotes (' ') to indicate that they are strings. However, in actual implementation, you should remove the quotes and execute the code as Python statements. Here's the corrected version of the `sort_matrix` function without the quotes: ```python def sort_matrix(matrix): sorted_matrix = sorted(matrix, key=lambda x: sum(x)) return sorted_matrix ``` Now you can call the `sort_matrix` function with your test cases to verify the output.	pass 测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]
zhipu	To achieve the task of sorting a matrix based on the sum of its rows, we can follow these steps: 1. Calculate the sum of each row. 2. Use the calculated sums to sort the rows of the matrix. 3. Return the sorted matrix. Here is the Python function that implements this logic: ```python def sort_matrix(matrix): # Calculate the sum of each row and store it along with the row row_sums = [(sum(row), row) for row in matrix] # Sort the list of tuples based on the sum (first element of each tuple) sorted_row_sums = sorted(row_sums, key=lambda x: x[0]) # Extract the sorted rows from the list of tuples sorted_matrix = [row for _, row in sorted_row_sums] return sorted_matrix # Test cases assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]]) == [[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]]) == [[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5, 8, 9], [6, 4, 3], [2, 1, 4]]) == [[2, 1, 4], [6, 4, 3], [5, 8, 9]] print("All tests passed!") ``` This function first creates a list of tuples where each tuple contains the sum of a row and the row itself. It then sorts this list based on the sums. Finally, it extracts the rows from the sorted list of tuples to form the sorted matrix. You can run this code to verify that it passes the provided test cases.	pass 测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]
gpto1	'def sort_matrix(matrix): return sorted(matrix, key=sum)'	failed 测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]
deepseekv3	To solve the problem of sorting a matrix in ascending order according to the sum of its rows, we can follow these steps: 1. Calculate the sum of each row: For each row in the matrix, calculate the sum of its elements. 2. Sort the matrix based on row sums: Use the calculated sums to sort the rows of the matrix. 3. Return the sorted matrix: After sorting, return the matrix in the desired order. Here's the Python function that implements this logic: ```python def sort_matrix(matrix): # Sort the matrix based on the sum of each row sorted_matrix = sorted(matrix, key=lambda row: sum(row)) return sorted_matrix # Test cases assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]]) == [[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]]) == [[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5, 8, 9], [6, 4, 3], [2, 1, 4]]) == [[2, 1, 4], [6, 4, 3], [5, 8, 9]] print("All test cases passed!") ``` ### Explanation: - `sorted(matrix, key=lambda row: sum(row))`: This line sorts the matrix. The `key` argument specifies that the sorting should be based on the sum of each row. The `lambda row: sum(row)` function calculates the sum of the elements in each row. - Test Cases: The provided test cases ensure that the function works correctly by comparing the output to the expected results. This function will correctly sort the matrix in ascending order based on the sum of its rows.	pass 测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]] assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]] assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]

模型

模型答案

测试结果

金声玉亮2.0

```python
def sort_matrix(matrix):
# Calculate the sum of each row and pair it with the row index
row_sums = [(sum(row), i) for i, row in enumerate(matrix)]
# Sort the row sums based on the sum
row_sums.sort(key=lambda x: x[0])
# Reconstruct the matrix based on the sorted row indices
sorted_matrix = [matrix[i] for _, i in row_sums]
return sorted_matrix
```
[DONE]

pass
测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]]
assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]]
assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]

deepseekr1

To solve this problem, we need to sort a given matrix in ascending order based on the sum of each row. The goal is to return a new matrix where the rows are ordered from the smallest sum to the largest sum.

### Approach
The approach to solve this problem involves the following steps:
1. **Calculate the Sum of Each Row**: For each row in the matrix, compute the sum of its elements.
2. **Sort Rows by Sum**: Use the computed sums to sort the rows in ascending order. The sorting should maintain the stability of rows with equal sums, meaning their original order is preserved if their sums are the same.

To achieve this efficiently, we can utilize Python's built-in `sorted` function, which allows specifying a custom key for sorting. The key here will be the sum of each row. This approach ensures that the rows are sorted based on their sums in ascending order.

### Solution Code
```python
def sort_matrix(matrix):
return sorted(matrix, key=lambda row: sum(row))
```

### Explanation
1. **Calculate Row Sums**: The `sorted` function uses a lambda function `lambda row: sum(row)` as the key. This lambda function computes the sum of each row, which is then used to determine the order of rows.
2. **Sorting**: The `sorted` function sorts the rows based on their sums. By default, `sorted` sorts in ascending order, which matches the requirement of the problem.
3. **Return Sorted Matrix**: The sorted list of rows is returned as the new matrix.

This approach efficiently sorts the matrix rows using built-in functions, ensuring clarity and conciseness in the solution. The time complexity of this approach is O(n log n), where n is the number of rows in the matrix, due to the sorting step. This is efficient and suitable for typical use cases.

gpto1

'def sort_matrix(matrix):
return sorted(matrix, key=sum)'

failed
测试用例：assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]])==[[1, 1, 1], [1, 2, 3], [2, 4, 5]]
assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]])==[[-2, 4, -5], [1, -1, 1], [1, 2, 3]]
assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]])==[[2, 1, 4], [6, 4, 3], [5, 8, 9]]

GPT-4o

```python
def sort_matrix(matrix):
# Sort the matrix based on the sum of rows
sorted_matrix = sorted(matrix, key=sum)
return sorted_matrix
```

To ensure that the function works correctly, let's test it against the provided assertions:

```python
# Test cases
assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]]) == [[1, 1, 1], [1, 2, 3], [2, 4, 5]]
assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]]) == [[-2, 4, -5], [1, -1, 1], [1, 2, 3]]
assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]]) == [[2, 1, 4], [6, 4, 3], [5, 8, 9]]

print("All tests passed!")
```

This code defines the `sort_matrix` function and tests it with the provided test cases to ensure correctness.

llama3.1-70B-Instruct

def sort_matrix(matrix):
return sorted(matrix, key=sum)

llama3.1-405B-Instruct

def sort_matrix(matrix):
return sorted(matrix, key=sum)

DeepSeek-Coder-V2

Qwen2-72B-Instruct

'def sort_matrix(matrix):
row_sums = [(sum(row), row) for row in matrix]
sorted_rows = sorted(row_sums, key=lambda x: x[0])
sorted_matrix = [row for _, row in sorted_rows]
return sorted_matrix'
[DONE]

baichuan4

To sort a given matrix in ascending order according to the sum of its rows, you can use the following function:

```python
def sort_matrix(matrix):
# Calculate the sum of each row
row_sums = [sum(row) for row in matrix]

# Create a sorted list of row indices based on the row sums
sorted_indices = sorted(range(len(matrix)), key=lambda i: row_sums[i])

# Create a new matrix with the rows in the sorted order
sorted_matrix = [matrix[i] for i in sorted_indices]

return sorted_matrix
```

This function first calculates the sum of each row in the input matrix. Then, it creates a sorted list of row indices based on these sums. Finally, it creates a new matrix with the rows in the sorted order.

Let's test the function with the provided test cases:

```python
assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]]) == [[1, 1, 1], [1, 2, 3], [2, 4, 5]]
assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]]) == [[-2, 4, -5], [1, -1, 1], [1, 2, 3]]
assert sort_matrix([[5, 8, 9], [6, 4, 3], [2, 1, 4]]) == [[2, 1, 4], [6, 4, 3], [5, 8, 9]]
```

The function passes all the tests, so it seems to be working correctly.

doubao

def sort_matrix(matrix):
return sorted(matrix, key=sum)
[DONE]

minimax

```python
def sort_matrix(matrix):
# Sort the matrix based on the sum of each row
matrix.sort(key=lambda row: sum(row))
return matrix

# Test cases
assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]]) == [[1, 1, 1], [1, 2, 3], [2, 4, 5]]
assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]]) == [[-2, 4, -5], [1, -1, 1], [1, 2, 3]]
assert sort_matrix([[5, 8, 9], [6, 4, 3], [2, 1, 4]]) == [[2, 1, 4], [6, 4, 3], [5, 8, 9]]
```

This function `sort_matrix` takes a matrix (a list of lists) as input and returns a new matrix sorted in ascending order based on the sum of its rows. The `sort` method is used with a key function that calculates the sum of each row. The test cases check if the function correctly sorts the matrices as specified.

kimi

Sure, let's write the functions one by one.

1. Function to find similar elements from two tuple lists:

```python
def similar_elements(test_tup1, test_tup2):
res = tuple(sorted(set(test_tup1) & set(test_tup2)))
return res
```

2. Function to identify non-prime numbers:

```python
import math

def is_not_prime(n):
if n <= 1:
return True
for i in range(2, int(math.sqrt(n)) + 1):
if n % i == 0:
return True
return False
```

3. Function to find the largest integers from a given list of numbers using heap queue algorithm:

```python
import heapq

def heap_queue_largest(nums, n):
largest_nums = heapq.nlargest(n, nums)
return largest_nums
```

4. Function to sort a given matrix in ascending order according to the sum of its rows:

```python
def sort_matrix(matrix):
return sorted(matrix, key=lambda x: sum(x))
```

Now let's test the functions:

```python
# Test for similar_elements function
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)

# Test for is_not_prime function
assert is_not_prime(2) == False
assert is_not_prime(10) == True
assert is_not_prime(35) == True

# Test for heap_queue_largest function
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]

# Test for sort_matrix function
assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]]) == [[1, 1, 1], [1, 2, 3], [2, 4, 5]]
assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]]) == [[-2, 4, -5], [1, -1, 1], [1, 2, 3]]
assert sort_matrix([[5,8,9],[6,4,3],[2,1,4]]) == [[2, 1, 4], [6, 4, 3], [5, 8, 9]]
```

If you run these tests, they should all pass without any assertion errors.

wenxinyiyan

'def sort_matrix(matrix):
sorted_matrix = sorted(matrix, key=lambda x: sum(x))
return sorted_matrix'
[DONE]

Explanation:
The `sort_matrix` function takes a matrix (list of lists) as input and returns a new matrix with its rows sorted in ascending order based on the sum of their elements. The `sorted` function is used to sort the rows, and the `key` parameter is set to a lambda function that calculates the sum of each row. This ensures that the rows are sorted according to their sums.

Note: The provided code snippets are enclosed in single quotes (' ') to indicate that they are strings. However, in actual implementation, you should remove the quotes and execute the code as Python statements.

Here's the corrected version of the `sort_matrix` function without the quotes:

```python
def sort_matrix(matrix):
sorted_matrix = sorted(matrix, key=lambda x: sum(x))
return sorted_matrix
```
Now you can call the `sort_matrix` function with your test cases to verify the output.

zhipu

To achieve the task of sorting a matrix based on the sum of its rows, we can follow these steps:

1. Calculate the sum of each row.
2. Use the calculated sums to sort the rows of the matrix.
3. Return the sorted matrix.

Here is the Python function that implements this logic:

```python
def sort_matrix(matrix):
# Calculate the sum of each row and store it along with the row
row_sums = [(sum(row), row) for row in matrix]

# Sort the list of tuples based on the sum (first element of each tuple)
sorted_row_sums = sorted(row_sums, key=lambda x: x[0])

# Extract the sorted rows from the list of tuples
sorted_matrix = [row for _, row in sorted_row_sums]

return sorted_matrix

# Test cases
assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]]) == [[1, 1, 1], [1, 2, 3], [2, 4, 5]]
assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]]) == [[-2, 4, -5], [1, -1, 1], [1, 2, 3]]
assert sort_matrix([[5, 8, 9], [6, 4, 3], [2, 1, 4]]) == [[2, 1, 4], [6, 4, 3], [5, 8, 9]]

print("All tests passed!")
```

This function first creates a list of tuples where each tuple contains the sum of a row and the row itself. It then sorts this list based on the sums. Finally, it extracts the rows from the sorted list of tuples to form the sorted matrix.

You can run this code to verify that it passes the provided test cases.

gpto1

'def sort_matrix(matrix):
return sorted(matrix, key=sum)'

deepseekv3

To solve the problem of sorting a matrix in ascending order according to the sum of its rows, we can follow these steps:

1. **Calculate the sum of each row**: For each row in the matrix, calculate the sum of its elements.
2. **Sort the matrix based on row sums**: Use the calculated sums to sort the rows of the matrix.
3. **Return the sorted matrix**: After sorting, return the matrix in the desired order.

Here's the Python function that implements this logic:

```python
def sort_matrix(matrix):
# Sort the matrix based on the sum of each row
sorted_matrix = sorted(matrix, key=lambda row: sum(row))
return sorted_matrix

# Test cases
assert sort_matrix([[1, 2, 3], [2, 4, 5], [1, 1, 1]]) == [[1, 1, 1], [1, 2, 3], [2, 4, 5]]
assert sort_matrix([[1, 2, 3], [-2, 4, -5], [1, -1, 1]]) == [[-2, 4, -5], [1, -1, 1], [1, 2, 3]]
assert sort_matrix([[5, 8, 9], [6, 4, 3], [2, 1, 4]]) == [[2, 1, 4], [6, 4, 3], [5, 8, 9]]

print("All test cases passed!")
```

### Explanation:
- **`sorted(matrix, key=lambda row: sum(row))`**: This line sorts the matrix. The `key` argument specifies that the sorting should be based on the sum of each row. The `lambda row: sum(row)` function calculates the sum of the elements in each row.
- **Test Cases**: The provided test cases ensure that the function works correctly by comparing the output to the expected results.

This function will correctly sort the matrix in ascending order based on the sum of its rows.