NumPy> [1, 2, 3, 4, 5, 6, 7, 8, 9] avec 3 ndarrays ([1,4,7], [2,5,8], [3,6,9]) Implémentation à diviser en> {Comment utiliser slice / reshape () + Méthode de translocation matricielle}

GeForce GTX 1070 (8GB)
ASRock Z170M Pro4S [Intel Z170chipset]
Ubuntu 14.04 LTS desktop amd64
TensorFlow v0.11
cuDNN v5.1 for Linux
CUDA v8.0
Python 2.7.6
IPython 5.1.0 -- An enhanced Interactive Python.
gcc (Ubuntu 4.8.4-2ubuntu1~14.04.3) 4.8.4
GNU bash, version 4.3.8(1)-release (x86_64-pc-linux-gnu)

import numpy as np

alist = [1, 2, 3, 4, 5, 6, 7, 8, 9]

xs = np.array([])
ys = np.array([])
zs = np.array([])

for idx, elem in enumerate(alist):
    print('%d:%s' % (idx, elem))
    if idx % 3 == 0:
        xs = np.append(xs, elem)
    elif idx % 3 == 1:
        ys = np.append(ys, elem)
    else:
        zs = np.append(zs, elem)

print(xs)
print(ys)
print(zs)

$ python test_python_170409a.py 
0:1
1:2
2:3
3:4
4:5
5:6
6:7
7:8
8:9
[ 1.  4.  7.]
[ 2.  5.  8.]
[ 3.  6.  9.]

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