Update Mask in NumPy Masked array to include additional elements

Last update on March 26 2025 13:13:02 (UTC/GMT +8 hours)

18. Modify Existing Mask

Write a NumPy program that creates a masked array and changes the mask to include additional elements.

Sample Solution:

Python Code:

import numpy as np
import numpy.ma as ma

# Create a 2D NumPy array of shape (5, 5) with random integers
array_2d = np.random.randint(0, 100, size=(5, 5))

# Define an initial condition to mask elements less than 20
initial_condition = array_2d < 20

# Create a masked array from the 2D array using the initial condition
masked_array = ma.masked_array(array_2d, mask=initial_condition)

# Define an additional condition to mask elements greater than 80
additional_condition = array_2d > 80

# Update the mask to include additional elements
masked_array.mask = masked_array.mask | additional_condition

# Print the original array, the initial masked array, and the updated masked array
print('Original 2D array:\n', array_2d)
print('Initial masked array (values < 20 are masked):\n', masked_array)
print('Updated masked array (values < 20 or > 80 are masked):\n', masked_array)

Output:

Original 2D array:
 [[28 91 10 92 58]
 [45 35 89 92  4]
 [26 82 69 70 18]
 [29 85  3 15 84]
 [80  7 68 83 81]]
Initial masked array (values < 20 are masked):
 [[28 -- -- -- 58]
 [45 35 -- -- --]
 [26 -- 69 70 --]
 [29 -- -- -- --]
 [80 -- 68 -- --]]
Updated masked array (values < 20 or > 80 are masked):
 [[28 -- -- -- 58]
 [45 35 -- -- --]
 [26 -- 69 70 --]
 [29 -- -- -- --]
 [80 -- 68 -- --]]

Explanation:

• Import Libraries:
• Imported numpy as "np" for array creation and manipulation.
• Imported numpy.ma as "ma" for creating and working with masked arrays.
• Create 2D NumPy Array:
• Create a 2D NumPy array named array_2d with random integers ranging from 0 to 99 and a shape of (5, 5).
• Define Initial Condition:
• Define an initial condition to mask elements in the array that are less than 20.
• Create Masked Array:
• Create a masked array from the 2D array using ma.masked_array, applying the initial condition as the mask. Elements less than 20 are masked.
• Define Additional Condition:
• Define an additional condition to mask elements in the array that are greater than 80.
• Update Mask:
• Updated the mask to include additional elements by combining the initial mask with the additional condition using logical OR (|).
• Print the original 2D array, the initially masked array, and the updated masked array to verify the operation.

For more Practice: Solve these Related Problems:

• Write a Numpy program to create a masked array and then update the mask to include additional elements based on a new threshold.
• Write a Numpy program to modify the mask of an existing masked array by unmasking elements that meet a revised condition.
• Write a Numpy program to change the mask of a 2D array dynamically and then compare the before and after masked data.
• Write a Numpy program to merge two masks on a single array using logical operations and then apply the combined mask.

Python-Numpy Code Editor:

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