I have a boolean numpy array which I need to convert it to binary, therefore where there is true it should be 255 and where it is false it should be 0.
Can someone point me out how to write the code?
1
-
1That seems to be an odd way to define binary.Merlin1896– Merlin189607/18/2020 06:00:48Commented Jul 18, 2020 at 6:00
Add a comment
|
4 Answers
x = np.array([True, False, True, True, False])
x.astype(int)*255
answered Jul 18, 2020 at 5:56
Example:
BA = np.random.randint(0,2,10,dtype=bool)
BA
# array([False, True, True, True, False, True, False, True, True,
# True])
Method 1 (faster):
-BA.view('u1')
# array([ 0, 255, 255, 255, 0, 255, 0, 255, 255, 255], dtype=uint8)
Method 2 (safer):
-BA.astype('u1')
# array([ 0, 255, 255, 255, 0, 255, 0, 255, 255, 255], dtype=uint8)
answered Jul 18, 2020 at 6:15
just multiply by 255
In [81]: arr = np.array([True, False, True, False],dtype=bool)
In [82]: arr * 255
Out[82]: array([255, 0, 255, 0])
answered Jul 18, 2020 at 7:03
Let x be your data in numpy array Boolean format.
Try
np.where(x,255,0)
