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numpy.ma.make_mask() function | Python

  • Last Updated : 20 Jun, 2021

numpy.ma.make_mask() function is used to create a boolean mask from an array. 
This function can accept any sequence that is convertible to integers, or nomask. It does not require that contents must be 0s and 1s, values of 0 are interpreted as False, everything else as True. Return m as a boolean mask. 
 

Syntax : numpy.ma.make_mask(m, copy = False, shrink = True, dtype = bool )
Parameters : 
arr : [ array_like] Potential mask. 
copy : [bool, optional] Whether to return a copy of m (True) or m itself (False). 
shrink : [bool, optional] Whether to shrink m to nomask if all its values are False. 
dtype : [dtype, optional] Data-type of the output mask. By default, the output mask has a dtype of MaskType (bool).
Return : [ndarray] A boolean mask derived from m. 
 

Code #1 : 
 

Python3




# Python program explaining
# numpy.ma.make_mask() function
 
# importing numpy as geek 
# and numpy.ma module as ma
import numpy as geek
import numpy.ma as ma
 
m = [1, 1, 0, 1]
 
gfg = ma.make_mask(m)
 
print (gfg)

Output : 
 

[ True  True False  True]

  
Code #2 : 
 



Python3




# Python program explaining
# numpy.ma.make_mask() function
 
# importing numpy as geek 
# and numpy.ma module as ma
import numpy as geek
import numpy.ma as ma
 
m = [2, -3, 0, 1]
 
gfg = ma.make_mask(m)
 
print (gfg)

Output : 
 

[ True  True False  True]

  
Code #3 : 
 

Python3




# Python program explaining
# numpy.ma.make_mask() function
 
# importing numpy as geek 
# and numpy.ma module as ma
import numpy as geek
import numpy.ma as ma
 
m = [True, True, True, False]
 
gfg = ma.make_mask(m)
 
print (gfg)

Output : 
 

[ True  True  True False]

 

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