Filling a numpy array with x random values

Question

I have a numpy array of size x, which I need to fill with 700 true.

For example:

a = np.zeros(5956)

If I want to fill this with 70 % True, I can write this:

msk = np.random.rand(len(a)) < 0.7
b = spam_df[msk]

But what if I need exactly 700 true, and the rest false?

You want to fill it with 700 elements that are true or you want to fill 70% of array values to True — Filip Młynarski
– Filip Młynarski, Commented Nov 17, 2018 at 17:58
I want to fill the array with exactly 700 true values that are randomly distributed in the array of 5956 values. Hence 800 true and 5956-800 false — Oeyvind
– Oeyvind, Commented Nov 17, 2018 at 18:02
Generate 700 random values (without replacement) from the 5956 range, and use those to set values of a to 1. — hpaulj
– hpaulj, Commented Nov 17, 2018 at 18:14

Filip Młynarski · Accepted Answer · 2018-11-17 18:17:51Z

4

import numpy as np

x = 5956
a = np.zeros((x), dtype=bool)

random_places = np.random.choice(x, 700, replace=False)
a[random_places] = True

answered Nov 17, 2018 at 18:17

Filip Młynarski

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Comments

cph_sto · Accepted Answer · 2018-11-18 12:25:55Z

2

import numpy as np
zeros = np.zeros(5956-700, dtype=bool)
ones=np.ones(700, dtype=bool)
arr=np.concatenate((ones,zeros), axis=0, out=None)
np.random.shuffle(arr)#Now, this array 'arr' is shuffled, with 700 Trues and rest False

Example - there should be 5 elements in an array with 3 True and rest False.

ones= np.ones(3, dtype=bool)   #array([True, True, True])
zeros= np.zeros(5-3, dtype=bool)   #array([False, False])
arr=np.concatenate((ones,zeros), axis=0, out=None)   #arr - array([ True,  True,  True, False, False])
np.random.shuffle(arr)    # now arr - array([False,  True,  True,  True, False])

edited Nov 18, 2018 at 12:25

answered Nov 17, 2018 at 18:14

cph_sto

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2 Comments

Warren Weckesser Over a year ago

FYI: It would be bit more efficient to write arr = np.zeros(5956, dtype=bool); arr[:700] = 1 and then shuffle arr.

cph_sto Over a year ago

fair argument Warren :)

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