NumPy exp()

In this tutorial, you will learn about the numpy.exp() method with the help of examples.

The exp() function is used to calculate the exponential values of the elements in an array.

Example

import numpy as np

array1 = np.array([1, 2, 3, 4, 5])

# use of exp() to calculate the exponential values of each elements in array1
result = np.exp(array1)

print(result)

# Output : [  2.71828183   7.3890561   20.08553692  54.59815003 148.4131591 ]

exp() Syntax

The syntax of exp() is:

numpy.exp(array)

exp() Arguments

The exp() function takes one argument:

array - the input array

exp() Return Value

The exp() function returns an array that contains the exponential values of the elements in the input array.

Example 1: Use of exp() to Calculate Natural Logarithm

import numpy as np

# create a 2-D array
array1 = np.array([[1, 2, 3], 
                                [4, 5, 6]])

# use exp() to calculate the exponential values each element in array1
result = np.exp(array1)

print(result)

Output

[[  2.71828183   7.3890561   20.08553692]
 [ 54.59815003 148.4131591  403.42879349]]

Here, we have used the np.exp() function to calculate the exponential values of each element in the 2-D array named array1.

The resulting array result contains the exponential values.

Example 2: Graphical Representation of exp()

To provide a graphical representation of the exponential function, let's plot the exponential curve using matplotlib, a popular data visualization library in Python.

To use matplotlib, we'll first import it as plt.

import numpy as np
import matplotlib.pyplot as plt

# generate x values from -5 to 5 with a step of 0.1
x = np.arange(-5, 5, 0.1)

# compute the exponential values of x
y = np.exp(x)

# Plot the exponential curve
plt.plot(x, y)
plt.xlabel('x')
plt.ylabel('exp(x)')
plt.title('Exponential Function')
plt.grid(True)
plt.show()

Output