可以用reshape方法,但是感覺flatten方法更好
pridict_y[[14.394563]
[ 4.5585423]
[10.817445]
[12.291978]
[26.076233]
[20.033213]
[11.320534]
[14.528755]
[11.454205]
[ 9.153889]
[12.769189]
[ 5.7419834]
[25.451023]
[18.215645]
[21.743513]
[ 8.488817]
[17.128687]
[17.53172]
[ 4.953989]
[11.3504]
[ 7.5612407]
[ 4.2715034]
[20.316795]
[17.732632]
[ 4.2850647]
[ 6.971166]
[11.657596]
[24.968727]
[13.93272]]
pridict_y.reshape(29,)
和pridict_y.flatten()
結果都是
array([14.394563 , 4.5585423, 10.817445 , 12.291978 , 26.076233,
20.033213 , 11.320534 , 14.528755 , 11.454205 , 9.153889,
12.769189 , 5.7419834, 25.451023 , 18.215645 , 21.743513,
8.488817 , 17.128687 , 17.53172 , 4.953989 , 11.3504,
7.5612407, 4.2715034, 20.316795 , 17.732632 , 4.2850647,
6.971166 , 11.657596 , 24.968727 , 13.93272 ], dtype=float32)
**或參考:【python】numpy庫ndarray多維陣列的維度變換方法:reshape、resize、swapaxes、flatten等詳解與例項
numpy庫對多維陣列有非常靈巧的處理方式,主要的處理方法有:
in [22]: a = np.arange(20)
#原陣列不變
in [23]: a.reshape([4,5])
out[23]:
array([[ 0, 1, 2, 3, 4],
[ 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14],
[15, 16, 17, 18, 19]])
in [24]: a
out[24]:
array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
17, 18, 19])
#修改原陣列
in [25]: a.resize([4,5])
in [26]: a
out[26]:
array([[ 0, 1, 2, 3, 4],
[ 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14],
[15, 16, 17, 18, 19]])
in [27]: a.swapaxes(1,0)
out[27]:
array([[ 0, 5, 10, 15],
[ 1, 6, 11, 16],
[ 2, 7, 12, 17],
[ 3, 8, 13, 18],
[ 4, 9, 14, 19]])
in [29]: a.flatten()
out[29]:
array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
17, 18, 19])
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