numpy.reshape
2300 ワード
numpy.reshape(a,newshape,order=’C’)公式解釈:Gives a new shape to an array without changing its data.
いくつかの例を見る
arrは次のとおりです.
[[[[ 0, 1, 2], [ 3, 4, 5], [ 6, 7, 8], [ 9, 10, 11], [ 12, 13, 14]],
arr_rは、
[[[[ 0, 1, 2, 3, 4], [ 5, 6, 7, 8, 9], [ 10, 11, 12, 13, 14]],
あなたの中には、C++と同じRowMajorの性質があることがわかります.
注意arr.transpose()とarr.reshape()の違い:transposeは座標軸を回転させるだけで、各軸の長さは変わらず、方向を変えただけです.reshape()は、要素をRowMajor基準で再配置します.
いくつかの例を見る
l=range(120)
import numpy as np
arr=np.array(l)
arr=arr.reshape(2,4,5,3)
arrは次のとおりです.
[[[[ 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]]]]
arr_r = arr.reshape(2,4,3,5)
arr_rは、
[[[[ 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]]]]
あなたの中には、C++と同じRowMajorの性質があることがわかります.
注意arr.transpose()とarr.reshape()の違い:transposeは座標軸を回転させるだけで、各軸の長さは変わらず、方向を変えただけです.reshape()は、要素をRowMajor基準で再配置します.