Numpy Array Element-Comparison to Float64

Question

I am trying to return an array (element-wise) of True/False values on a numpy array comparsion to a float64 static variable. Input and desired output array is 1x10 (column x row)

array = np.random.randint(10, size=(10,1))

Attempt 1:

bool = np.any((array >= min)&(array <= max))

Attempt 2:

bool = np.logical_and((array >= min),(array <= max))

Attempt 3:

bool = np.any([(array >= min)&(array <= max)])

Attempt 4:

bool = np.array(np.any([(array >= min)&(array <= max)]))

All four of the above methods produce this output in the interpreter

print(bool) = True

When desired output looks something like:

print(bool) = [True
               False
               True
               True
               False
               False
               True
               False
               False
               True]

Thank you in advance for any insight you can provide me!

print your original array, notice that every individual value is wrapped in an array, is this intentional? — Adam.Er8
– Adam.Er8, Commented Jul 1, 2019 at 12:55
No it was not, I am as you call "noob" haha especially with numpy — moader808
– moader808, Commented Jul 1, 2019 at 13:13
OK so you actually just want size to be (10) and not (10,1) :), and then there's no need for .ravel() in my answer. — Adam.Er8
– Adam.Er8, Commented Jul 1, 2019 at 13:15

Adam.Er8 · Accepted Answer · 2019-07-01 13:00:15Z

1

you can use .ravel() to get your output in the desired shape.

try this:

import numpy as np

array = np.random.randint(10, size=(10, 1))

min = 2.2
max = 6.6
result = ((array >= min) & (array <= max)).ravel()

print(result)

Output (example, as it is random):

[False True True True True True False False False True]

answered Jul 1, 2019 at 13:00

Adam.Er8

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1 Comment

moader808 Over a year ago

just confirmed in compiler that .ravel option works! Neat find, didn't know this option existed. Very useful

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