题解 | 实现压缩行稀疏矩阵（CSR）格式转换

import numpy as np
import scipy.sparse
def compressed_row_sparse_matrix(dense_matrix):
    csr_matrix = scipy.sparse.csr_matrix(dense_matrix)
    vals = csr_matrix.data.tolist()
    col_idx = csr_matrix.indices.tolist()
    row_ptr = csr_matrix.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)