gha gha - 1 month ago 14
Python Question

Numpy: Get random set of rows from 2D array

I have a very large 2D array which looks something like this:

a=
[[a1, b1, c1],
[a2, b2, c2],
...,
[an, bn, cn]]


Using numpy, is there an easy way to get a new 2D array with e.g. 2 random rows from the initial array a (without replacement)?

e.g.

b=
[[a4, b4, c4],
[a99, b99, c99]]

Answer
>>> A = np.random.randint(5, size=(10,3))
>>> A
array([[1, 3, 0],
       [3, 2, 0],
       [0, 2, 1],
       [1, 1, 4],
       [3, 2, 2],
       [0, 1, 0],
       [1, 3, 1],
       [0, 4, 1],
       [2, 4, 2],
       [3, 3, 1]])
>>> idx = np.random.randint(10, size=2)
>>> idx
array([7, 6])
>>> A[idx,:]
array([[0, 4, 1],
       [1, 3, 1]])

Putting it together for a general case:

A[np.random.randint(A.shape[0], size=2), :]

For non replacement (numpy 1.7.0+):

A[np.random.choice(A.shape[0], 2, replace=False), :]

I do not believe there is a good way to generate random list without replacement before 1.7. Perhaps you can setup a small definition that ensures the two values are not the same.