Skip to content
Related Articles

Related Articles

Improve Article

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 :






# 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 :




# 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 --]

 Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.  

To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course. And to begin with your Machine Learning Journey, join the Machine Learning – Basic Level Course




My Personal Notes arrow_drop_up
Recommended Articles
Page :