Numpy MaskedArray.maximum_fill_value() function | Python

numpy.MaskedArray.maximum_fill_value() function is used to return the minimum value that can be represented by the dtype of an object.

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 :

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# Python program explaining
# numpy.MaskedArray.maximum_fill_value() method 
    
# importing numpy as geek  
# and numpy.ma module as ma 
import numpy as geek 
import numpy.ma as ma 
    
# creating input array  
in_arr = geek.array([135, -3], dtype ='float')
print ("Input array : ", in_arr) 
    
# Now we are creating a masked array. 
# by making  entry as invalid.  
mask_arr = ma.masked_array(in_arr, mask =[1, 0, 0, 0]) 
print ("Masked array : ", mask_arr) 
    
# applying MaskedArray.maximum_fill_value    
# methods to masked array
out_val = ma.maximum_fill_value(mask_arr) 
print ("Minimum filled value : ", out_val) 

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Output:

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

 

Code #2 :

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# Python program explaining
# numpy.MaskedArray.maximum_fill_value() method 
    
# importing numpy as geek  
# and numpy.ma module as ma 
import numpy as geek 
import numpy.ma as ma 
    
# creating input array  
in_arr = geek.array([[1, 2], [ 3, -1], [ 5, -3]])
print ("Input array : ", in_arr) 
    
# Now we are creating a masked array. 
# by making  entry as invalid.  
mask_arr = ma.masked_array(in_arr, mask =[[1, 0], [ 1, 0], [ 0, 0]]) 
print ("Masked array : ", mask_arr) 
    
# applying MaskedArray.maximum_fill_value    
# methods to masked array
out_val = ma.maximum_fill_value(mask_arr) 
print ("Minimum filled value : ", out_val)  

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Output:

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



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