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([ 1 , 3 , 5 , - 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) |
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) |
Input array : [[ 1 2] [ 3 -1] [ 5 -3]] Masked array : [[-- 2] [-- -1] [5 -3]] Maximum filled value : 2147483647