Compute sum of all elements in 1D array using np.add.reduce

Last update on March 26 2025 13:14:21 (UTC/GMT +8 hours)

9. Ufunc: Sum Reduction with np.add.reduce

ufunc Reduce Method:

Write a NumPy program that uses the np.add.reduce ufunc to compute the sum of all elements in a 1D array.

Sample Solution:

Python Code:

import numpy as np

# Create a 1D NumPy array of integers
array_1d = np.array([1, 2, 3, 4, 5])

# Use the np.add.reduce ufunc to compute the sum of all elements in the array
sum_of_elements = np.add.reduce(array_1d)

# Print the original array and the sum of its elements
print('Original 1D array:', array_1d)
print('Sum of all elements using np.add.reduce:', sum_of_elements)

Output:

Original 1D array: [1 2 3 4 5]
Sum of all elements using np.add.reduce: 15

Explanation:

• Import Libraries:
• Imported numpy as "np" for array creation and manipulation.
• Create 1D NumPy Array:
• Create a 1D NumPy array named ‘array_1d’ with integers [1, 2, 3, 4, 5].
• Use np.add.reduce ufunc:
• Used the np.add.reduce ufunc to compute the sum of all elements in 'array_1d'. The reduce method applies the np.add ufunc cumulatively to the elements of the array, resulting in the sum.
• Print Results:
• Print the original array and the sum of its elements computed using 'np.add.reduce'.

For more Practice: Solve these Related Problems:

• Write a Numpy program to compute the sum of a 1D array using np.add.reduce and then compare it with np.sum for consistency.
• Write a Numpy program to use np.add.reduce to sum elements conditionally based on a mask array.
• Write a Numpy program to apply np.add.reduce on segmented parts of a 1D array and then combine the results.
• Write a Numpy program to implement np.add.reduce on a large array and analyze its performance versus a standard summation loop.

Python-Numpy Code Editor:

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