题解 | 实现压缩行稀疏矩阵（CSR）格式转换

# def compressed_row_sparse_matrix(dense_matrix):
#     vals=[]
#     col_idx=[]
#     row_ptr=[0]
#     for row in dense_matrix:
#         for col,val in enumerate(row):
#             if val!=0:
#                 vals.append(val)
#                 col_idx.append(col)
#         row_ptr.append(len(vals))    
#     return vals, col_idx, row_ptr
from scipy.sparse import csr_matrix
def compressed_row_sparse_matrix(dense_matrix):
   csr=csr_matrix(dense_matrix)
   return csr.data.tolist(),csr.indices.tolist(),csr.indptr.tolist()


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)