以下是一个示例解决方案,使用Python编程语言:
def average_rows_and_columns(matrix):
num_rows = len(matrix)
num_cols = len(matrix[0])
row_averages = []
for row in matrix:
row_sum = sum(row)
row_avg = row_sum / num_cols
row_averages.append(row_avg)
col_averages = []
for col in range(num_cols):
col_sum = sum(matrix[row][col] for row in range(num_rows))
col_avg = col_sum / num_rows
col_averages.append(col_avg)
return row_averages, col_averages
# 示例用法
matrix = [
[1, 2, 3],
[4, 5, 6],
[7, 8, 9]
]
row_averages, col_averages = average_rows_and_columns(matrix)
print("Row averages:", row_averages)
print("Column averages:", col_averages)
输出结果:
Row averages: [2.0, 5.0, 8.0]
Column averages: [4.0, 5.0, 6.0]
这个示例中,我们定义了一个名为average_rows_and_columns
的函数,它接受一个二维矩阵作为输入,并返回按行和列求得的平均值列表。首先,我们获取矩阵的行数和列数。然后,我们使用两个循环分别计算每一行和每一列的和,并计算平均值。最后,我们将这些平均值存储在row_averages
和col_averages
列表中,并将它们作为结果返回。
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