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.
numpy.ma.masked_where (condition, arr, copy = True)
condition: [array_like] Masking condition. When condition tests floating point values for equality, consider using masked_values instead.
arr: [ndarray] Input array which we want to mask.
copy: strong > [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:
Input array: [1 2 3 -1 2] Masked array: [- 2 3 - 2]
Code # 2:
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 -]