在Scipy中，如何检查两个稀疏矩阵之间的差异？

import numpy as np
from scipy.sparse import coo_matrix, csr_matrix

# 示例稀疏矩阵 A 和 B
data_A = np.array([1, 2, 3])
row_A = np.array([0, 1, 2])
col_A = np.array([0, 1, 2])
A = coo_matrix((data_A, (row_A, col_A)), shape=(3, 3))

data_B = np.array([1, 2, 4])
row_B = np.array([0, 1, 2])
col_B = np.array([0, 1, 2])
B = coo_matrix((data_B, (row_B, col_B)), shape=(3, 3))

# 转换为相同的稀疏格式（例如CSR）
A_csr = A.tocsr()
B_csr = B.tocsr()

# 计算差异矩阵
diff_matrix = A_csr - B_csr

# 提取非零差异元素及其位置
diff_data = diff_matrix.data
diff_row = diff_matrix.indices
diff_col = np.where(diff_matrix != 0)[1]

print("非零差异元素及其位置：")
for i in range(len(diff_data)):
    print(f"位置 ({diff_row[i]}, {diff_col[i]}) 的差异值为 {diff_data[i]}")