numpy_fancy_2.py

numpy_fancy_2.py

import numpy as np

# sow a fix seed to make trial and error more predictable
np.random.seed(0)

# create a 10 x 3 NumPy array
a = np.random.rand(10,3)

# do the fancy indexing: for each row, extract the element that is closest to 0.5
a2 = a[np.arange(a.shape[0]), np.argsort(np.abs(a - 0.5))[:,0]]

# array([ 0.5488135 ,  0.54488318,  0.43758721,  0.52889492,  0.56804456,
#         0.83261985,  0.77815675,  0.46147936,  0.63992102,  0.52184832])