numpy.ma.masked_all_like() function | Python

numpy.ma.masked_all_like() function | Python

Last Updated : 05 May, 2020

numpy.ma.masked_all_like() function return an empty masked array of the same shape and dtype as the array arr, where all the data are masked.

Syntax : numpy.ma.masked_all_like(arr) Parameter : arr : [ndarray] An array describing the shape and dtype of the required MaskedArray. Return : [MaskedArray] A masked array with all data masked.

Code #1 :

# Python program explaining
# numpy.ma.masked_all_like() function

# importing numpy as geek 
# and numpy.ma module as ma 
import numpy as geek 
import numpy.ma as ma 

arr = geek.zeros((4, 4), dtype = geek.float32)

gfg = ma.masked_all_like(arr)

print (gfg)

 
# Python program explaining
# numpy.ma.masked_all_like() function​# importing numpy as geek # and numpy.ma module as ma import numpy as geek import numpy.ma as ma ​arr = geek.zeros((4, 4), dtype = geek.float32)​gfg = ma.masked_all_like(arr)​print (gfg)

Output :

[[-- -- -- --]
 [-- -- -- --]
 [-- -- -- --]
 [-- -- -- --]]

Code #2 :

# Python program explaining
# numpy.ma.masked_all_like() function

# importing numpy as geek 
# and numpy.ma module as ma 
import numpy as geek 
import numpy.ma as ma 

arr = geek.zeros((4, 3), dtype = geek.float32)

gfg = ma.masked_all_like(arr)

print (gfg)

 
# Python program explaining
# numpy.ma.masked_all_like() function​# importing numpy as geek # and numpy.ma module as ma import numpy as geek import numpy.ma as ma ​arr = geek.zeros((4, 3), dtype = geek.float32)​gfg = ma.masked_all_like(arr)​print (gfg)

Output :

[[-- -- --]
 [-- -- --]
 [-- -- --]
 [-- -- --]]

numpy.ma.masked_all_like() function | Python

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