How to mask an array inside a given interval in NumPy
Overview
The masked_inside() function in NumPy is used to mask an array inside a given interval.
Syntax
This is the syntax of the masked_inside() function:
ma.masked_inside(x, v1, v2)
Syntax of the ma.masked_inside() function
Parameter values
The masked_inside() function takes the following parameter values:
x: This is the input array.v1andv2: These represent the boundaries for which the values of the given array are to be masked. Both values are not excluded when masking.
Return value
The masked_inside() function returns a masked array with values that fall within the specified intervals that are masked.
Example
# A code to illustrate the masked_inside() function# importing the necessary librariesimport numpy as npimport numpy.ma as ma# creating an input arraymy_array = np.array([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])# masking the values starting from 3 to 7mask_array =ma.masked_inside(my_array, 3, 7)print(mask_array)
Explanation
- Lines 4–5: We import the necessary library and module.
- Line 8: We create an input array called
my_array. - Line 11: We use the
masked_greater_equal()function to mask the values from3to7. We assign the result to a variable calledmask_array. - Line 13: We print the value of the masked array,
mask_array, to the console.