  NumPy | Python Methods and Functions

`numpy.MaskedArray.masked_where()` is used to mask the array in which the condition is met. Returns arr as an array masked where the condition is True. Any masked arr or condition values ​​are also masked in the output.

Syntax: ` numpy.ma.masked_where (condition, arr, copy = True) `

Parameters:
arr: [ndarray] Input array which we want to mask.
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 result of masking arr where condition is True ..

Code # 1:

 ` # Python program explaining ` ` # numpy.MaskedArray.masked_where () method ` ` `  ` # import numy like a geek ` ` # and the numpy.ma module like ma ` ` import ` ` numpy as geek ` ` import ` ` numpy.ma as ma `   ` # create input array ` ` in_arr ` ` = ` ` geek.array ([` ` 1 ` `, ` ` 2 ` `, ` ` 3 ` `, ` ` - ` ` 1 ` `, ` ` 2 ` `]) ` ` print ` ` (` ` "Input array:" ` `, in_arr) ` ` `  ` # applying MaskedArray.masked_where methods # to enter an array where the value is & lt; = 1 `` mask_arr = ma.masked_where (in_arr & lt; = 1 , in_arr) print ( "Masked arra y: " , mask_arr) `

Output:

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

Code # 2:

 ` # Python program explaining ` ` # numpy.MaskedArray.masked_where () method `   ` # import numy as a geek ` ` # and the numpy.ma module as ma ` ` import ` ` numpy as geek ` ` import ` ` numpy.ma as ma `   ` # create input array in_arr1 ` ` in_arr1 ` ` = ` ` geek.arange (` ` 4 ` `) ` ` print ` ` (` ` "1st Input array:" ` `, in_arr1 ) `   ` # applying MaskedArray.masked_where methods ` ` # to enter in_arr1 array, where value = 1 ` ` mask_arr1 ` ` = ` ` ma.masked_where (in_arr1 ` ` = ` ` = ` ` 1 ` `, in_arr1) ` ` print ` ` (` ` "1st Masked array:" ` `, mask_arr1) `   ` # create input array in_arr2 ` ` in_arr2 ` ` = ` ` geek.arange (` ` 4 ` `) ` ` print ` ` (` ` "2nd Input array:" ` `, in_arr2) `   ` # applying the MaskedArray.masked_where methods ` ` # to enter an in_arr2 array where value = 1 ` ` mask_arr2 ` ` = ` ` ma.masked_where (in_arr2 ` ` = ` ` = ` ` 3 ` `, in_arr2) ` ` print ` ` (` ` "2nd Masked array: "` `, mask_arr2) ` ` `  ` # applying the MaskedArray.masked_where methods ` ` # up to the 1st masked array, where the second masked array ` ` # used as a condition ` ` res_arr ` ` = ` ` ma.masked_where (mask_arr1 ` ` = ` ` = ` ` 3 ` `, mask_arr2) ` ` print ` ` (` ` "Resultant Masked array:" ` `, res_arr) `

Output:

` 1st Input array: [0 1 2 3] 1st Masked array: [0 - 2 3] 2nd Input array: [ 0 1 2 3] 2nd Masked array: [0 1 2 -] Resultant Masked array: [0 - 2 -] `