Find Maximum value in Masked NumPy array ignoring Masked elements
NumPy: Masked Arrays Exercise-10 with Solution
Write a NumPy program to create a masked array and find the maximum value, ignoring the masked elements.
Sample Solution:
Python Code:
import numpy as np
import numpy.ma as ma
# Create a 2D NumPy array of shape (4, 4) with random integers
array_2d = np.random.randint(0, 100, size=(4, 4))
# Define the condition to mask elements greater than 50
condition = array_2d > 50
# Create a masked array from the 2D array using the condition
masked_array = ma.masked_array(array_2d, mask=condition)
# Find the maximum value in the masked array, ignoring the masked elements
max_value = masked_array.max()
# Print the original array, the masked array, and the maximum value
print('Original 2D array:\n', array_2d)
print('Masked array (elements > 50 are masked):\n', masked_array)
print('Maximum value (ignoring masked elements):', max_value)
Output:
Original 2D array: [[ 5 8 65 37] [18 63 62 93] [65 92 48 17] [32 8 1 13]] Masked array (elements > 50 are masked): [[5 8 -- 37] [18 -- -- --] [-- -- 48 17] [32 8 1 13]] Maximum value (ignoring masked elements): 48
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 (4, 4).
- Define Condition:
- Define a condition to mask elements in the array that are greater than 50.
- Create Masked Array:
- Create a masked array from the 2D array using ma.masked_array, applying the condition as the mask. Elements greater than 50 are masked.
- Find Maximum Value:
- Use the max method of the masked array to find the maximum value, ignoring the masked elements.
- Print the original 2D array, the masked array, and the maximum value, ignoring the masked elements.
Python-Numpy Code Editor:
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