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

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 :

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 :

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 --]

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