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