题解 | 实现压缩行稀疏矩阵（CSR）格式转换

import numpy as np
from scipy.sparse import csr_matrix
def compressed_row_sparse_matrix(dense_matrix):
    dense_np=np.array(dense_matrix)
    csr=csr_matrix(dense_np)
    vals=csr.data.tolist()
    col_idx=csr.indices.tolist()
    row_ptr=csr.indptr.tolist()
    return vals, col_idx, row_ptr
if __name__ == "__main__":
    dense_matrix = eval(input())
    vals, col_idx, row_ptr = compressed_row_sparse_matrix(dense_matrix)
    print(vals)
    print(col_idx)
    print(row_ptr)