- Pythonでの数値計算を高速化
- 大量のデータ処理をする時の速度を上げたい時は，Pythonのリストではなく NumPyの配列 (ndarray) を使用
- ndarray 配列
- 1次元 (ベクトル) : numpy.array
2次元 (行列) : numpy.matrix
3次元以上 (「テンソル」)
<![CDATA[$ python
>>> import numpy as np
>>> a = np.matrix([[0,1,2],[3,4,5]])
>>> b = np.matrix([[0,1],[2,3],[4,5]])
>>> c = np.matmul(a,b)
>>> a
[[0 1 2]
[3 4 5]]
>>> b
[[0 1]
[2 3]
[4 5]]
>>> c
[[10 13]
[28 40]]
>>> a = np.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])
>>> a_2_3_4 = a.reshape([2,3,4])
>>> a_2_3_4
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]]])
>>> a_2_2_2_3 = a.reshape([2,2,2,3])
>>> a_2_2_2_3
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]]]])>>>
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