141130(2)

NumPy


sum, meanの使い方

>>> a = np.arange(24).reshape((2,3,4))
>>> 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]]])
>>> a.sum()
276
>>> a.mean()
11.5
>>> a.sum(0)
array([[12, 14, 16, 18],
       [20, 22, 24, 26],
       [28, 30, 32, 34]])
>>> a.mean(axis=0)
array([[  6.,   7.,   8.,   9.],
       [ 10.,  11.,  12.,  13.],
       [ 14.,  15.,  16.,  17.]])
>>> a.sum(1)
array([[12, 15, 18, 21],
       [48, 51, 54, 57]])
>>> a.mean(axis=1)
array([[  4.,   5.,   6.,   7.],
       [ 16.,  17.,  18.,  19.]])
>>> a.sum(2)
array([[ 6, 22, 38],
       [54, 70, 86]])
>>> a.mean(axis=2)
array([[  1.5,   5.5,   9.5],
       [ 13.5,  17.5,  21.5]])

load, savez, loadtxtの使い方

>>> ary1 = np.arange(10)
>>> ary2 = np.arange(3)
>>> np.savez('data', a = ary1, b = ary2)
>>> npz = np.load('data.npz')
>>> npz['a']
array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
>>> npz['b']
array([0, 1, 2])

(data.txt
 1, 2, 3
 10,20,30
 が保存している状況で)
>>> ary = np.loadtxt('data.txt', delimiter=',')
>>> ary
array([[  1.,   2.,   3.],
       [ 10.,  20.,  30.]])