def create_matrix(len, rows, cols):
    matrix_list = []
    for i in range(len):
        matrix = []
        for j in range(rows * cols):
            matrix.append((i + 1) * 10 + (j + 1))
        matrix = np.reshape(matrix, (rows, cols))
        matrix_list.append(matrix)
    matrix_list = np.array(matrix_list, dtype='ubyte')
    return matrix_list

# 生成矩阵测试
matrix = create_matrix(2, 3, 4)
# 类型
print(type(matrix))
# 维度
print(matrix.shape)
# 输出
print(matrix)

<class 'numpy.ndarray'>
(2, 3, 4)
[[[11 12 13 14]
  [15 16 17 18]
  [19 20 21 22]]

 [[21 22 23 24]
  [25 26 27 28]
  [29 30 31 32]]]

def write_matrix(matrix, filename):
    type2code_dict = {'uint8': 0x08, 'int8': 0x09, 'int16': 0x0B, 'int32': 0x0C, 'float32': 0x0D, 'float64': 0x0E}
    # 以字节方式打开文件句柄
    with open(filename, 'wb') as f:
        # 维度
        shapes = matrix.shape
        # 文件头
        # 按照要求存储文件。大端优先，占位，数据类型，维度数量
        file_head_fmt = '>HBB'
        file_head = struct.pack(file_head_fmt, 0, 8, len(shapes))
        # 查看类型
        print(type(file_head))
        # 参看文件头
        print(file_head)
        f.write(file_head)

        file_head_fmt = '>I'
        # 顺序将维度存储到文件
        for i in shapes:
            file_head = struct.pack(file_head_fmt, i)
            f.write(file_head)
        # 将矩阵存储到文件
        f.write(matrix)

write_matrix(matrix, 'D:/matrix.idx')

<class 'bytes'>
b'\x00\x00\x08\x03'

def read_matrix(filename):
    code2type_dict = {0x08: 'B', 0x09: 'b', 0x0B: 'h', 0x0c: 'i', 0x0D: 'f', 0x0E: 'd'}
    with open(filename, 'rb') as f:
        data_buff = f.read()
        off_set = 0
        file_head_fmt = '>HBB'
        _, elem_code, dimlen = struct.unpack_from(file_head_fmt, data_buff, off_set)
        off_set += struct.calcsize(file_head_fmt)

        # {}是字符串的占位符
        file_head_fmt = '>{}I'.format(dimlen)
        shapes = struct.unpack_from(file_head_fmt, data_buff, off_set)
        off_set += struct.calcsize(file_head_fmt)

        # 矩阵的维度的连乘，代表一共有几个元素值
        data_fmt = '>' + str(np.prod(shapes)) + code2type_dict[elem_code]
        matrix = struct.unpack_from(data_fmt, data_buff, off_set)
        matrix = np.reshape(matrix, shapes).astype('uint8')
    return matrix

matrix2 = read_matrix('D:/matrix.idx')
print(type(matrix2))
print(matrix2.shape)
print(matrix2)

<class 'numpy.ndarray'>
(2, 3, 4)
[[[11 12 13 14]
  [15 16 17 18]
  [19 20 21 22]]

 [[21 22 23 24]
  [25 26 27 28]
  [29 30 31 32]]]