NumPy
reshapeの使い方
>>> a = np.arange(16).reshape((2,8))
>>> a
array([[ 0, 1, 2, 3, 4, 5, 6, 7],
[ 8, 9, 10, 11, 12, 13, 14, 15]])
>>> a.reshape((4,4))
array([[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11],
[12, 13, 14, 15]])
transposeの使い方
>>> a = np.arange(120).reshape((2,3,4,5))
>>> a
array([[[[ 0, 1, 2, 3, 4],
[ 5, 6, 7, 8, 9],
[ 10, 11, 12, 13, 14],
[ 15, 16, 17, 18, 19]],
[[ 20, 21, 22, 23, 24],
[ 25, 26, 27, 28, 29],
[ 30, 31, 32, 33, 34],
[ 35, 36, 37, 38, 39]],
[[ 40, 41, 42, 43, 44],
[ 45, 46, 47, 48, 49],
[ 50, 51, 52, 53, 54],
[ 55, 56, 57, 58, 59]]],
[[[ 60, 61, 62, 63, 64],
[ 65, 66, 67, 68, 69],
[ 70, 71, 72, 73, 74],
[ 75, 76, 77, 78, 79]],
[[ 80, 81, 82, 83, 84],
[ 85, 86, 87, 88, 89],
[ 90, 91, 92, 93, 94],
[ 95, 96, 97, 98, 99]],
[[100, 101, 102, 103, 104],
[105, 106, 107, 108, 109],
[110, 111, 112, 113, 114],
[115, 116, 117, 118, 119]]]])
>>> a.transpose((0,1,2,3)).shape
(2, 3, 4, 5)
>>> a.transpose((0,1,3,2)).shape
(2, 3, 5, 4)
>>> a.transpose((0,2,1,3)).shape
(2, 4, 3, 5)
>>> a.transpose((0,2,3,1)).shape
(2, 4, 5, 3)
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