Boolean Indexing on higher dimensions in NumPy arrays

Last update on August 29 2025 12:47:02 (UTC/GMT +8 hours)

19. 5D Array & Boolean Indexing Across Dimensions

NumPy: Advanced Indexing Exercise-19 with Solution

Boolean Indexing on Higher Dimensions:

Write a NumPy program that creates a 5D NumPy array. Use boolean indexing to select elements along specific dimensions based on conditions applied to other dimensions.

Sample Solution:

Python Code:

import numpy as np

# Create a 5D NumPy array of shape (3, 4, 2, 3, 5) with random integers
array_5d = np.random.randint(0, 100, size=(3, 4, 2, 3, 5))

# Define a condition on the entire 5D array
# For example, select elements where the values are greater than 50
condition = array_5d > 50

# Use boolean indexing to select elements along specific dimensions based on the condition
selected_elements = array_5d[condition]

# Print the shape of the original array, the condition array, and the selected elements
print('Original 5D array shape:', array_5d.shape)
print('Condition (elements > 50):\n', condition)
print('Selected elements based on condition:\n', selected_elements)
print('Shape of selected elements:', selected_elements.shape)

Output:

Original 5D array shape: (3, 4, 2, 3, 5)
Condition (elements > 50):
 [[[[[False  True False False False]
    [ True  True False  True False]
    [False  True False  True  True]]

   [[ True  True  True False  True]
    [False False  True  True False]
    [ True False False False  True]]]


  [[[ True False False False  True]
    [ True  True False False  True]
    [False  True False False False]]

   [[False False False  True  True]
    [ True  True  True  True  True]
    [ True  True  True False False]]]


  [[[False False False  True False]
    [ True  True False False False]
    [ True False False False  True]]

   [[False False  True  True  True]
    [ True False False  True  True]
    [False  True  True False False]]]


  [[[ True False  True  True  True]
    [ True False False  True False]
    [ True False False False  True]]

   [[False False  True False  True]
    [ True False  True  True False]
    [False False  True False False]]]]



 [[[[ True  True  True False False]
    [ True  True  True  True  True]
    [ True  True  True False False]]

   [[False  True False False False]
    [ True False False  True  True]
    [ True False  True  True False]]]


  [[[False  True False  True  True]
    [False False  True False  True]
    [False False False False False]]

   [[False  True  True  True False]
    [False False False False  True]
    [False  True False  True  True]]]


  [[[ True False False  True  True]
    [ True  True False False False]
    [ True False False  True False]]

   [[ True False  True False False]
    [ True False  True  True  True]
    [False False False False False]]]


  [[[False  True False  True  True]
    [ True False False False False]
    [False  True  True  True  True]]

   [[False False  True  True False]
    [ True  True  True  True  True]
    [False False False  True  True]]]]



 [[[[False  True False  True  True]
    [False False False False False]
    [False  True False  True False]]

   [[ True False False False False]
    [False False False False  True]
    [False False False  True  True]]]


  [[[ True False False  True  True]
    [ True  True  True False  True]
    [ True  True False False  True]]

   [[False False  True  True  True]
    [False False  True False False]
    [False  True  True False  True]]]


  [[[ True False  True  True  True]
    [ True False False False False]
    [False False  True False False]]

   [[False  True  True  True  True]
    [False  True False False  True]
    [False False  True  True  True]]]


  [[[False False False False False]
    [ True  True  True False  True]
    [ True False False  True False]]

   [[ True  True  True  True  True]
    [ True False False  True  True]
    [False  True  True False False]]]]]
Selected elements based on condition:
 [99 71 55 88 81 74 69 58 71 51 97 73 69 77 62 68 53 72 67 99 91 51 61 53
 68 67 58 51 83 96 78 72 98 60 58 73 67 90 63 52 67 90 64 98 97 73 58 84
 68 55 84 73 66 55 62 78 84 62 53 76 73 95 96 63 79 84 59 64 74 82 71 96
 57 87 57 98 54 80 93 76 66 55 79 80 58 72 91 59 89 81 55 60 94 87 53 69
 52 53 95 99 94 99 74 58 92 81 99 56 70 72 51 54 51 76 51 82 96 77 55 88
 77 94 78 79 99 93 85 87 80 66 85 54 71 97 71 86 96 72 67 87 97 93 83 74
 69 92 96 68 92 98 72 94 56 99 93 68 56 97 95 98 73 88 71 52 74 78 99 76
 71 90 53 54 90 82 67]
Shape of selected elements: (175,)

Explanation:

• Import Libraries:
• Imported numpy as "np" for array creation and manipulation.
• Create 5D NumPy Array:
• Create a 5D NumPy array named array_5d with random integers ranging from 0 to 99 and a shape of (3, 4, 2, 3, 5).
• Define Condition:
• Define a condition to select elements in the array that are greater than 50 using boolean indexing.
• Boolean Indexing:
• Applied boolean indexing to select elements from array_5d that meet the defined condition.
• Print Results:
• Print the shape of the original 5D array, the boolean condition array, and the selected elements, including the shape of the selected elements to verify the operation.

For more Practice: Solve these Related Problems:

• Create a 5D array and use boolean indexing to select elements from one dimension based on conditions applied to another dimension.
• Write a function that filters a 5D array for slices where the sum along a specific axis exceeds a threshold.
• Implement a solution that applies a multi-dimensional boolean mask to a 5D array and returns the flattened indices of matching elements.
• Test the boolean indexing on a 5D array with mixed values to ensure correct selection across complex dimensions.

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• NumPy Advanced Indexing Exercises Home ↩
• NumPy Exercises Home ↩

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