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Numpy MaskedArray.minimum_fill_value() function | Python
  • Last Updated : 29 Oct, 2019

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

Syntax : numpy.ma.minimum_fill_value(obj)

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

Return : [ scalar ] The maximum fill value.

Code #1 :






# Python program explaining
# numpy.MaskedArray.minimum_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.minimum_fill_value    
# methods to masked array
out_val = ma.minimum_fill_value(mask_arr) 
print ("Maximum filled value : ", out_val) 
Output:
Input array :  [ 1.  3.  5. -3.]
Masked array :  [-- 3.0 5.0 -3.0]
Maximum filled value :  inf

 

Code #2 :




# Python program explaining
# numpy.MaskedArray.minimum_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]], dtype ='int')
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.minimum_fill_value    
# methods to masked array
out_val = ma.minimum_fill_value(mask_arr) 
print ("Maximum filled value : ", out_val) 
Output:
Input array :  [[ 1  2]
 [ 3 -1]
 [ 5 -3]]
Masked array :  [[-- 2]
 [-- -1]
 [5 -3]]
Maximum filled value :  2147483647

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