numpy.ma.make_mask() function | Python

numpy.ma.fix_invalid() function | Python

Last Updated : 05 May, 2020

numpy.ma.fix_invalid() function return input with invalid data masked and replaced by a fill value. Where invalid data means values of nan, inf, etc.

Syntax : numpy.ma.fix_invalid(arr, mask = False, copy = True, fill_value = None) Parameter : arr : [array_like] Input array. mask : [sequence, optional] Must be convertible to an array of booleans with the same shape as data. True indicates a masked data. copy : [bool, optional] Whether to use a copy of a (True) or to fix a in place (False). Default is True. fill_value : [scalar, optional] Value used for fixing invalid data. Default is None, in which case the arr.fill_value is used. Return : [MaskedArray] The input array with invalid entries fixed.

Code #1 :

Python3

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

# importing numpy as geek 
import numpy as geek 
 
arr = geek.ma.array([1., -1, geek.nan, geek.inf],
                              mask =[1] + [0]*3)

gfg = geek.ma.fix_invalid(arr)

print (gfg)

Output :

[-- -1.0 -- --]

Code #2 :

Python3

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

# importing numpy as geek 
import numpy as geek 
 
arr = geek.ma.array([1., -1, geek.nan,
                    geek.inf, -1, geek.nan],
                          mask =[1] + [0]*5)

gfg = geek.ma.fix_invalid(arr)

print (gfg)

Output :

[-- -1.0 -- -- -1.0 --]

numpy.ma.make_mask() function | Python

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