[Numpy] Fancy index

In [2]:

import numpy as np

 

In [4]:

test_array = np.array([1, 4, 0, 2, 3, 8, 9, 7], float)
test_array > 3

Out[4]:

array([False,  True, False, False, False,  True,  True,  True])

 

In [6]:

test_array[test_array>3]

Out[6]:

array([4., 8., 9., 7.])

 

In [8]:

condition = test_array < 3
test_array[condition]

Out[8]:

array([1., 0., 2.])

 

In [10]:

A = np.array([
[12, 13, 14, 12, 16, 14, 11, 10,  9],
[11, 14, 12, 15, 15, 16, 10, 12, 11],
[10, 12, 12, 15, 14, 16, 10, 12, 12],
[ 9, 11, 16, 15, 14, 16, 15, 12, 10],
[12, 11, 16, 14, 10, 12, 16, 12, 13],
[10, 15, 16, 14, 14, 14, 16, 15, 12],
[13, 17, 14, 10, 14, 11, 14, 15, 10],
[10, 16, 12, 14, 11, 12, 14, 18, 11],
[10, 19, 12, 14, 11, 12, 14, 18, 10],
[14, 22, 17, 19, 16, 17, 18, 17, 13],
[10, 16, 12, 14, 11, 12, 14, 18, 11],
[10, 16, 12, 14, 11, 12, 14, 18, 11],
[10, 19, 12, 14, 11, 12, 14, 18, 10],
[14, 22, 12, 14, 11, 12, 14, 17, 13],
[10, 16, 12, 14, 11, 12, 14, 18, 11]])
B = A < 15
B.astype(np.int)

Out[10]:

array([[1, 1, 1, 1, 0, 1, 1, 1, 1],
       [1, 1, 1, 0, 0, 0, 1, 1, 1],
       [1, 1, 1, 0, 1, 0, 1, 1, 1],
       [1, 1, 0, 0, 1, 0, 0, 1, 1],
       [1, 1, 0, 1, 1, 1, 0, 1, 1],
       [1, 0, 0, 1, 1, 1, 0, 0, 1],
       [1, 0, 1, 1, 1, 1, 1, 0, 1],
       [1, 0, 1, 1, 1, 1, 1, 0, 1],
       [1, 0, 1, 1, 1, 1, 1, 0, 1],
       [1, 0, 0, 0, 0, 0, 0, 0, 1],
       [1, 0, 1, 1, 1, 1, 1, 0, 1],
       [1, 0, 1, 1, 1, 1, 1, 0, 1],
       [1, 0, 1, 1, 1, 1, 1, 0, 1],
       [1, 0, 1, 1, 1, 1, 1, 0, 1],
       [1, 0, 1, 1, 1, 1, 1, 0, 1]])

 

In [15]:

a = np.array([2, 4, 6, 8], float)
b = np.array([0,0,1,3,2,1], int)

 

In [13]:

a[a>5]

Out[13]:

array([6., 8.])

 

In [17]:

a.take(b) #index에 해당하는 값을 가져옴

Out[17]:

array([2., 2., 4., 8., 6., 4.])

 

In [18]:

a = np.array([[1,4], [9, 16]], float)
b = np.array([0,0,1,1,0], int)
c = np.array([0,1,1,1,1], int)
a[b, c]

Out[18]:

array([ 1.,  4., 16., 16.,  4.])

 

In [19]:

a = np.array([[1, 4], [9, 16]], float)
a[b]

Out[19]:

array([[ 1.,  4.],
       [ 1.,  4.],
       [ 9., 16.],
       [ 9., 16.],
       [ 1.,  4.]])