Kurt Peek Kurt Peek - 1 month ago 7x
Python Question

Using Numpy's random.choice without replacement

According to the http://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.random.choice.html, using the

replace = False
with Numpy's
method should make the sample without replacement. However, this does not seem to work for me:

In [33]: import numpy as np

In [34]: arr = range(5)

In [35]: number = np.random.choice(arr, replace = False)

In [36]: arr
Out[36]: [0, 1, 2, 3, 4]

The array
is still
after sampling, and not missing a (random) number as I would expect. How could I sample a number from
without replacement?


As mentioned in one of the comments, np.choice selects with or without replacement, a series of numbers from a sequence. But it does not modify the sequence.

Easy alternative arr = range(5) # numbers below will never contain repeated numbers (replace=False) numbers = np.random.choice(arr, 3, replace=False)

The behaviour I think you want would be:

arr = range(5)
all_but_one = np.random.choice(arr, len(arr) -1, replace=False)

so you would select N-1 numbers without replacement (to avoid repetitions), effectively removing a random element from the iterable.

More efficient alternative

arr = range(5)
random_index = np.random.randint(0, len(arr))