假设我有四个不同数据类型的列表。我也有一个二维矩阵。我想把它们按列合并。
例如，在下面的源代码中：

train_x_111 == ['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j']
train_y_111 == ['abcd', 'bcde', 'cdef', 'defg', 'efgh', 'fghi', 'ghij', 'hijk', 'ijkl', 'jklm']
train_z_111 == [[0.0, 0.1, 0.2, 0.3],
 [0.1, 0.2, 0.3, 0.4],
 [0.2, 0.3, 0.4, 0.5],
 [0.3, 0.4, 0.5, 0.6],
 [0.4, 0.5, 0.6, 0.7],
 [0.5, 0.6, 0.7, 0.8],
 [0.6, 0.7, 0.8, 0.9],
 [ 0.7, 0.8, 0.9, 1.0],
 [0.8, 0.9, 1.0, 1.1],
 [0.9, 1.0, 1.1, 1.2]]

字符串
我希望在文本文件中输出以下内容：

源码.py

if __name__ == "__main__":
    train_x_111, train_y_111, train_z_111 = load_data() # load_data() returns three TF tensors

    features_data_int_2d = np.array(train_x_111, dtype=int)
    sum_int_1d = np.sum(features_data_int_2d, axis=1)
    sum_int_1d = sum_int_1d.reshape(-1, 1)

    sum_data_1d_obj = sum_int_1d.astype(np.object_)
    features_data_2d_obj = np.array(train_x_111, dtype=np.object_)
    classes_data_1d_obj = np.array(train_y_111, dtype=np.object_)
    classes_data_1d_obj = classes_data_1d_obj.reshape(10,1)
    classes_string_1d_obj = np.array(train_z_111, dtype=np.object_)
    classes_string_1d_obj = classes_string_1d_obj.reshape(10, 1)

    sum_matrix = np.concatenate((sum_data_1d_obj, classes_data_1d_obj), axis=-1)
    sum_matrix = np.concatenate((sum_matrix, classes_string_1d_obj), axis=-1)
    sum_matrix = np.concatenate((sum_matrix, features_data_int_2d), axis=-1)

    sum_matrix = sum_matrix.encode('ascii')
    print(sum_matrix)
    np.savetxt("my_file.txt", sum_matrix, fmt='%s', delimiter='\t')

型

错误输出

C:\ProgramData\Miniconda3\python.exe C:/Users/pc/source/repos/my_project/data_hashing.py
Traceback (most recent call last):
  File "C:\Users\pc\source\repos\my_project\data_hashing.py", line 151, in <module>
    sum_matrix = sum_matrix.encode('ascii')
AttributeError: 'numpy.ndarray' object has no attribute 'encode'

Process finished with exit code 1

型
如何将对象元素的NumPy数组编码为ASCII？