Numpy MaskedArray.masked_inside() function | Python (original) (raw)

Last Updated : 27 Sep, 2019

In many circumstances, datasets can be incomplete or tainted by the presence of invalid data. For example, a sensor may have failed to record a data, or recorded an invalid value. The numpy.ma module provides a convenient way to address this issue, by introducing masked arrays.Masked arrays are arrays that may have missing or invalid entries.numpy.MaskedArray.masked_inside() function is used to mask an array inside a given interval.This function is a Shortcut to masked_where, where condition is True for arr inside the interval [v1, v2] (v1 <= arr <= v2). The boundaries v1 and v2 can be given in either order.

Syntax : numpy.ma.masked_inside(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 :

Python3 `

Python program explaining

numpy.MaskedArray.masked_inside() 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_inside methods

to input array in the range[-1, 1]

mask_arr = ma.masked_inside(in_arr, -1, 1) print ("Masked array : ", mask_arr)

`

Output:

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

Code #2 :

Python3 `

Python program explaining

numpy.MaskedArray.masked_inside() 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_inside methods

to input array in the range[5e2, 5e8]

mask_arr = ma.masked_inside(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 : [-- 3e-05 -45.0 -- --]