Numpy array multiple condition boolean

Question

I want my array to pass two conditions. If I try to do this with just one I don't have any problems but if I'll give code two conditions python crashes. Here is my code:

import numpy as np
from collections import deque

queue = deque([], maxlen=10)

queue.appendleft(31)
queue.appendleft(32)
queue.appendleft(33)

cond1 = 35
cond2 = 30

A_1 = np.array(queue)

print(cond2 > A_1 < cond1)
# print(A_1 > 30)  # works
# array([ True,  True,  True], dtype=bool)

print(((cond2 > A_1 < cond1).sum() == A_1.size).astype(np.int))
# print(((A_1 > 30).sum() == A_1.size).astype(np.int))  # works
# 1

Numpy does not support shorthand operators. Please explicitly state them like this: (cond2 > A_1) & (A_1 < cond1) — cs95
– cs95, Commented May 27, 2018 at 7:20
Also, I don't understand what the second condition is doing, but it doesn't look correct to me. — cs95
– cs95, Commented May 27, 2018 at 7:21
I understand that, but I don't understand what ((cond2 > A_1 < cond1).sum() == A_1.size).astype(np.int) is trying to do. — cs95
– cs95, Commented May 27, 2018 at 7:24
Oh, okay, that makes sense. Anyway, the solution in my first comment should work, in case you didn't see it yet. — cs95
– cs95, Commented May 27, 2018 at 7:27
Well, yea, you switched it up: (cond1 > A_1) & (A_1 < cond2)... does that make more sense now? — cs95
– cs95, Commented May 27, 2018 at 7:30

Simeon Ikudabo · Accepted Answer · 2018-05-27 07:28:12Z

4

Here is a random example:

import numpy as np

np.random.seed(123456)

array = np.array(np.random.randn(12))

print((array < 1) & (array > 0))

And numpy you have to put the conditions in parenthesis, and then use the & operator for an and condition. For an or condition you use the | operator and then follow the same format. This will get you an array of Boolean values.

answered May 27, 2018 at 7:28

Simeon Ikudabo

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2 Comments

Hsin Over a year ago

Thanks for answer. It doesn't work with my example. Everything returns False.

Simeon Ikudabo Over a year ago

@Hsin This is just pseudo code. You may have zero examples in your code that return if you set the condition to the specific ones that I specified. If you set the conditions to the ones that YOU want, what does your code return?

Blownhither Ma · Accepted Answer · 2018-05-27 07:38:17Z

1

It should be something like np.logical_and(A_1 < cond1, A_1 > cond2)

If you want to check if all the elements satisfy, just np.all(np.logical_and(A_1 < cond1, A_1 > cond2))

cond2 > A_1 < cond1 won't work as desired because cond2 > A_1 returns a bool array. Compare boolean values with cond1 is not wanted according to your description. To be explicit, one can use np.logical_and.

edited May 27, 2018 at 7:38

answered May 27, 2018 at 7:26

Blownhither Ma

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