Comparing Numpy arrays like bit mask

Question

I want to compare numpy array two scale and data

for exaple

scale = [1,0,0,0,1,0,0,0,1,0,0,0] first and fifth and ninth bit is 1

data1 = [8,2,0,1,0,0,1,0,1,0,0,0] -> NG, because fifth bit is `0`
data2 = [8,0,0,0,1,0,1,0,1,0,0,0] -> OK, because first ,fifth, ninth bit is more than 0

What I want to check is

Every positions where scale is 1 should be more than 0 in data

Is there any good numpy function to do this??

why not compare scale to (data2>0)? if (scale == (data2>0)).all(): print('OK'); else: print('NG') — yann ziselman
– yann ziselman, Commented Aug 3, 2021 at 10:42

Rizquuula · Accepted Answer · 2021-08-03 10:56:34Z

2

Step by step using Numpy:

Convert to boolean, will return true when value > 0
Bitwise AND
Check equality

import numpy as np

scale = [1,0,0,0,1,0,0,0,1,0,0,0]
data1 = [8,2,0,1,0,0,1,0,1,0,0,0]
data2 = [8,0,0,0,1,0,1,0,1,0,0,0]

scale= np.array(scale, dtype=bool)
data1= np.array(data1, dtype=bool)
data2= np.array(data2, dtype=bool)

and1 = np.bitwise_and(scale, data1)
and2 = np.bitwise_and(scale, data2)

is_match1 = np.array_equal(scale, and1)
is_match2 = np.array_equal(scale, and2)

print(is_match1) # False
print(is_match2) # True

answered Aug 3, 2021 at 10:56

Rizquuula

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1 Comment

whitebear Over a year ago

Thank you bitwise_and is quite new to me. and very helpful

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