Compute Square Root of each element using np.sqrt in NumPy

Last update on March 26 2025 13:14:24 (UTC/GMT +8 hours)

2. Ufunc: Square Root Calculation

Using Built-in ufuncs:

Write a NumPy program that uses the np.sqrt ufunc to compute the square root of each element in a 2D NumPy array.

Sample Solution:

Python Code:

import numpy as np

# Create a 2D NumPy array of shape (3, 3) with random integers
array_2d = np.random.randint(1, 100, size=(3, 3))

# Use the np.sqrt ufunc to compute the square root of each element in the array
sqrt_array = np.sqrt(array_2d)

# Print the original array and the resulting array
print('Original 2D array:\n', array_2d)
print('Square root of each element:\n', sqrt_array)

Output:

Original 2D array:
 [[ 4  7 77]
 [69 25 96]
 [29 92  7]]
Square root of each element:
 [[2.         2.64575131 8.77496439]
 [8.30662386 5.         9.79795897]
 [5.38516481 9.59166305 2.64575131]]

Explanation:

• Import Libraries:
• Imported numpy as "np" for array creation and manipulation.
• Create 2D NumPy Array:
• Create a 2D NumPy array named ‘array_2d’ with random integers ranging from 1 to 99 and a shape of (3, 3).
• Compute Square Root Using np.sqrt:
• Used the np.sqrt "ufunc" to compute the square root of each element in the 2D array.
• Print Results:
• Print the original 2D array and the resulting array with the square root of each element.

For more Practice: Solve these Related Problems:

• Write a Numpy program to use the np.sqrt ufunc on a 2D array and then filter out any non-real results.
• Write a Numpy program to compute the square roots of elements in a 2D array and then compare the results with element-wise exponentiation.
• Write a Numpy program to apply np.sqrt on a 2D array with embedded negative values using a custom error handling routine.
• Write a Numpy program to combine np.sqrt with np.where to conditionally compute square roots only for positive elements in a 2D array.

Python-Numpy Code Editor:

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