Numpy MaskedArray.maximum_fill_value () function | python



numpy.MaskedArray.maximum_fill_value() is used to return the minimum value that the d-type of an object can represent.

Syntax: numpy.ma.maximum_fill_value(obj)

Parameters:
obj: [ndarray, dtype or scalar] The array data-type or scalar for which the minimum fill value is returned.

Return: [scalar] The minimum fill value.

Code # 1:

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

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

import  numpy as geek 

import numpy.ma as ma 

 
# create input array

in_arr = geek.array ([ 1 3 5 , - 3 ], dtype = `float` )

print ( "Input array : " , in_arr) 

  
# We are now creating a masked array.
  # invalidating the post.

mask_arr = ma.masked_array (in_arr, mask = [ 1 , 0 , 0 , 0 ]) 

print ( "Masked array:" , mask_arr) 

 
# apply MaskedArray .maximum_fill_value
# masked array methods

out_val = ma.maximum_fill_value (mask_arr) 

print   ( "Minimum filled value:" , out_val) 

Output:

 Input array: [1. 3. 5. - 3.] Masked array: [- 3.0 5.0 -3.0] Minimum filled value: -inf 

Code # 2:

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

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

import numpy as geek 

import numpy.ma as ma 

  
# create input about array

in_arr = geek.array ([[ 1 , 2 ], [ 3 , - 1 ], [ 5 , - 3 ]])

print ( "Input array:" , in_arr) 

  
# Now we create a masked array.
# invalidating the post.

mask_arr = ma.masked_array (in_a rr, mask = [[[ 1 , 0 ], [ 1 , 0 ], [ 0 , 0 ]]) 

print ( "Masked array:" , mask_arr) 

 
# apply MaskedArray.maximum_fill_value
# methods of the masked array

out_val = ma.maximum_fill_value (mask_arr) 

print ( "Minim um filled value: " , out_val) 

Output:

 Input array: [[1 2] [3 -1] [5 -3]] Masked array: [[- 2] [- -1 ] [5 -3]] Minimum filled value: -2147483648