Extract smaller Subarrays using integer Indexing in NumPy

Last update on December 21 2024 07:36:48 (UTC/GMT +8 hours)

NumPy: Advanced Indexing Exercise-17 with Solution

Extracting Subarrays with Integer Indexing:

Write a NumPy program that creates a 4D NumPy array and uses integer indexing to extract smaller subarrays.

Sample Solution:

Python Code:

import numpy as np

# Create a 4D NumPy array of shape (4, 4, 4, 4) with random integers
array_4d = np.random.randint(0, 100, size=(4, 4, 4, 4))

# Define indices to extract subarrays
depth_indices = np.array([0, 2])
row_indices = np.array([1, 3])
col_indices = np.array([0, 2])
slice_indices = np.array([1, 3])

# Use integer indexing to extract smaller subarrays
subarray = array_4d[depth_indices[:, np.newaxis, np.newaxis, np.newaxis],
                    row_indices[:, np.newaxis, np.newaxis],
                    col_indices[:, np.newaxis],
                    slice_indices]

# Print the original array shape and the extracted subarray
print('Original 4D array shape:', array_4d.shape)
print('Extracted subarray shape:', subarray.shape)
print('Extracted subarray:\n', subarray)

Output:

Original 4D array shape: (4, 4, 4, 4)
Extracted subarray shape: (2, 2, 2, 2)
Extracted subarray:
 [[[[38 79]
   [15 79]]

  [[22  6]
   [28 90]]]


 [[[61 18]
   [43 69]]

  [[20 59]
   [65 89]]]]

Explanation:

• Import Libraries:
• Imported numpy as "np" for array creation and manipulation.
• Create 4D NumPy Array:
• Create a 4D NumPy array named array_4d with random integers ranging from 0 to 99 and a shape of (4, 4, 4, 4).
• Define Indices:
• Defined depth_indices, row_indices, col_indices, and slice_indices to specify the indices for extracting subarrays along each axis.
• Integer Indexing:
• Used integer indexing to extract subarrays from 'array_4d' based on the specified indices for each axis.
• Print Results:
• Print the shape of the original 4D array, the shape of the extracted subarray, and the extracted subarray itself to verify the operation.

Python-Numpy Code Editor: