Easy way to test if each element in an numpy array lies between two values?

I was wondering if there was a syntactically simple way of checking if each element in a numpy array lies between two numbers.

In other words, just as numpy.array([1,2,3,4,5]) < 5 will return array([True, True, True, True, False]), I was wondering if it was possible to do something akin to this:

1 < numpy.array([1,2,3,4,5]) < 5

... to obtain ...

array([False, True, True, True, False])

I understand that I can obtain this through logical chaining of boolean tests, but I'm working through some rather complex code and I was looking for a syntactically clean solution.

Any tips?

One solution would be:

import numpy as np
a = np.array([1, 2, 3, 4, 5])
(a > 1) & (a < 5)
# array([False,  True,  True,  True, False])

Another would be to use numpy.any, Here is an example

import numpy as np
a = np.array([1,2,3,4,5])
np.any((a < 1)|(a > 5 ))

You can also center the matrix and use the distance to 0

upper_limit = 5
lower_limit = 1
a = np.array([1,2,3,4,5])
your_mask = np.abs(a- 0.5*(upper_limit+lower_limit))<0.5*(upper_limit-lower_limit)

One thing to keep in mind is that the comparison will be symmetric on both sides, so it can do 1<x<5 or 1<=x<=5, but not 1<=x<5

In multi-dimensional arrays you could use the np.any() option suggested or comparison operators, while using & and and will raise an error.

Example (on multi-dim array) using comparison operators

import numpy as np

arr = np.array([[1,5,1],
                [0,1,0],
                [0,0,0],
                [2,2,2]])

Now use == if you want to check if the array values are inside a range, i.e A < arr < B, or != if you want to check if the array values are outside a range, i.e arr < A and arr > B :

(arr<1) != (arr>3)
> array([[False,  True, False],
         [ True, False,  True],
         [ True,  True,  True],
         [False, False, False]])

(arr>1) == (arr<4)
> array([[False, False, False],
         [False, False, False],
         [False, False, False],
         [ True,  True,  True]])