NumPy: Compute the reciprocal for all elements in a given array

NumPy Mathematics: Exercise-39 with Solution

Write a NumPy program to compute the reciprocal for all elements in a given array.

Sample Solution:

Python Code:

# Importing the NumPy library
import numpy as np

# Creating an array containing floating-point numbers
x = np.array([1., 2., .2, .3])

# Displaying the original array x
print("Original array: ")
print(x)

# Calculating the reciprocal of each element in array x using np.reciprocal()
r1 = np.reciprocal(x)

# Calculating the reciprocal of each element in array x using the reciprocal operator (1/x)
r2 = 1/x

# Checking if the results from np.reciprocal() and the reciprocal operator are equal using np.array_equal()
assert np.array_equal(r1, r2)

# Displaying the reciprocals for all elements of the array obtained using np.reciprocal()
print("Reciprocal for all elements of the said array:")
print(r1) 

Sample Output:

Original array: 
[1.  2.  0.2 0.3]
Reciprocal for all elements of the said array:
[1.         0.5        5.         3.33333333]

Explanation:

In the above code –

x = np.array([1., 2., .2, .3]): This line creates a NumPy array x with four float elements. The four elements in the array are 1.0, 2.0, 0.2, and 0.3.

r1 = np.reciprocal(x): np.reciprocal(x) returns the reciprocal of each element of the input array x. The reciprocal of an element x is defined as 1/x. For example, if x is [1., 2., .2, .3], then np.reciprocal(x) will return [1.,0.5, 5., 3.33333333]

r2 = 1/x: 1/x also calculates the reciprocal of each element in x. Since the operation 1/x is performed element-wise, it returns an array of the same shape as x with each element's reciprocal value.

assert np.array_equal(r1, r2): The resulting arrays from both methods, r1 and r2 respectively, are compared using np.array_equal() function to check if they have equal elements. As r1 and r2 are equal assert returns true.

Python-Numpy Code Editor:

Previous: Write a NumPy program to compute numerical negative value for all elements in a given array.

Next: Write a NumPy program to compute xy, element-wise where x, y are two given arrays.