Numpy MaskedArray.masked_invalid () function | python

numpy.MaskedArray.masked_invalid() is used to mask an array containing invalid values ​​(NaNs or infs). This function is a shortcut to masked_where with condition = ~ (numpy.isfinite (arr)) .

Syntax: numpy.ma.masked_invalid (arr, copy = True)

Parameters:
arr: [ndarray] Input array which we want to mask.
copy: [bool] If True (default) make a copy of arr in the result. If False modify arr in place and return a view.

Return: [MaskedArray] The resultant array after masking.

Code # 1:

# Python program explaining
# numpy. MaskedArray.masked_invalid () method

 
# import numy as a geek
# and the numpy.ma module as ma

import numpy as geek

import numpy.ma as ma

 
# create an input array with invalid values ​​

in_arr = geek.ar ray ([ 1 , 2 , geek.nan, - 1 , geek. inf])

print ( "Input array: " , in_arr)

  
# apply MaskedArray.masked_invalid
# methods for entering an array

mask_arr = ma.masked_invalid (in_arr)

print ( "Masked array:" , mask_arr)

Output:

 Input array: [1.2 . nan -1. inf] Masked array: [1.0 2.0 - -1.0 -] 

Code # 2:

# Python program explaining
# numpy.MaskedArray.masked_invalid () method

 
# import numy as geek
# and the numpy.ma module as ma

import numpy as geek

import numpy.ma as ma

 
# create input array with invalid element

in_arr = geek.array ([ 5e8 , 3e - 5 , geek.nan, 4e4 , 5e2 ])

print ( "Input array:" , in_arr)

 
# apply MaskedArray.masked_invalid
# methods for entering an array

mask_arr = ma.masked_invalid (in_arr)

print ( "Masked array:" , mask_arr)

Output :

 Input array: [5.e + 08 3.e-05 nan 4 .e + 04 5.e + 02] Masked array: [500000000.0 3e-05 - 40000.0 500.0]