numpy.ma.mask_or() function | Python (original) (raw)

Last Updated : 22 Apr, 2020

numpy.ma.mask_or() function combine two masks with the logical_or operator. The result may be a view on m1 or m2 if the other is nomask (i.e. False).

Syntax : numpy.ma.mask_or(m1, m2, copy = False, shrink = True)

Parameters :
m1, m2 : [ array_like] Input masks.
copy : [bool, optional] If copy is False and one of the inputs is nomask, return a view of the other input mask. Defaults to False
shrink : [bool, optional] Whether to shrink the output to nomask if all its values are False. Defaults to True.

Return : The result masks values that are masked in either m1 or m2.

Code #1 :

import numpy as geek

import numpy.ma as ma

m1 = geek.ma.make_mask([ 1 , 1 , 0 , 1 ])

m2 = geek.ma.make_mask([ 1 , 0 , 0 , 0 ])

gfg = geek.ma.mask_or(m1, m2)

print (gfg)

Output :

[ True True False True]

Code #2 :

import numpy as geek

import numpy.ma as ma

m1 = geek.ma.make_mask([ 1 , 0 , 0 , 0 ])

m2 = geek.ma.make_mask([ 1 , 1 , 0 , 1 ])

gfg = geek.ma.mask_or(m1, m2)

print (gfg)

Output :

[ True True False True]

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