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 :
# 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, 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.maximum_fill_value    # methods to masked array 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
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Code #2 :
# 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)  |
Output:
Input array : [[ 1 2] [ 3 -1] [ 5 -3]] Masked array : [[-- 2] [-- -1] [5 -3]] Minimum filled value : -2147483648
