.sqrt()

In NumPy, the .sqrt() method is used to calculate the positive square root of a number or the elements of an array. It is commonly employed in mathematical computations such as solving quadratic equations, applying the Pythagorean Theorem, modelling normal distributions, and more.

Syntax

numpy.sqrt(array, out=None, where=True)

• array: A number or array-like structure containing the elements to which the method is to be applied.
• out (Optional): The array where the result is to be stored. If not provided, a new array is created and used for storing the results.
• where (Optional): The condition (array of boolean values) that determines the elements on which the method is to be applied.
  • If the condition is True for a particular element, the square root is computed for that element.
  • If the condition is False for a particular element, the square root is not computed for that element and the original element is retained.
  • If not provided, the square root is computed for all elements.

Example

The below example shows the .sqrt() method in use:

# Importing the 'numpy' library as 'np'
import numpy as np

# Computing the square root of only those elements in the array which is greater than or equal to 5
result = np.sqrt([9,-4,25], where=np.array([9,-4,25]) >= 5)

print(result)

The output of the above code is shown below:

[3.00000000e+000 6.50227506e-310 5.00000000e+000]

Codebyte Example

In this codebyte example, the .sqrt() method only computes the square root of the elements of the array which are greater than 0:

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