Numpy中的行权重计算

import numpy as np

# 创建一个示例矩阵
matrix = np.array([[1, 2, 3],
                   [4, 5, 6],
                   [7, 8, 9]])

# 定义权重向量
weights = np.array([0.5, 1.0, 1.5])

# 计算每行的加权和
weighted_sum = np.dot(matrix, weights)

print("原始矩阵:\n", matrix)
print("权重向量:", weights)
print("行加权和:", weighted_sum)

# 错误示例
weights_wrong_length = np.array([0.5, 1.0])
weighted_sum_wrong = np.dot(matrix, weights_wrong_length)  # 会报错

# 正确示例
weights_correct_length = np.array([0.5, 1.0, 1.5])
weighted_sum_correct = np.dot(matrix, weights_correct_length)  # 正确计算

# 错误示例
matrix_wrong_dim = np.array([1, 2, 3])
weighted_sum_wrong_dim = np.dot(matrix_wrong_dim, weights)  # 会报错

# 正确示例
matrix_correct_dim = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
weighted_sum_correct_dim = np.dot(matrix_correct_dim, weights)  # 正确计算