Numpy MaskedArray masked_outside() function | Python

numpy.MaskedArray.masked_outside() function is used to mask an array outside of a given interval. This function is a Shortcut to masked_where, where condition is True for arr outside the interval [v1, v2] (arr <v1)|(arr > v2). The boundaries v1 and v2 can be given in either order.

Syntax : numpy.ma.masked_outside(arr, v1, v2, copy=True)

Parameters:
arr : [ndarray] Input array which we want to mask.
v1, v2 : [int] Lower and upper range.
copy : [bool] If True (default) make a copy of arr in the result. If False modify arr in place and return a view.

Return : [ MaskedArray] The resultant array after masking.

Code #1 :

# Python program explaining
# numpy.MaskedArray.masked_outside() 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, 2])
print ("Input array : ", in_arr)

# applying MaskedArray.masked_outside methods
mask_arr = ma.masked_outside(in_arr, -1, 1)
print ("Masked array : ", mask_arr)

Output:

Input array :  [ 1  2  3 -1  2]
Masked array :  [1 -- -- -1 --]

Code #2 :

# Python program explaining
# numpy.MaskedArray.masked_outside() 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([5e8, 3e-5, -45.0, 4e4, 5e2])
print ("Input array : ", in_arr)

# applying MaskedArray.masked_outside methods
mask_arr = ma.masked_outside(in_arr, 5e2, 5e8)
print ("Masked array : ", mask_arr)

Output:

Input array :  [ 5.0e+08  3.0e-05 -4.5e+01  4.0e+04  5.0e+02]
Masked array :  [500000000.0 -- -- 40000.0 500.0]