# How to Use NumPy Exponential Function

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• Post category:NumPy

NumPy `exp()` in Python is a mathematical function used to calculate the exponential values of all the elements present in the input array. This function takes four arguments which are `array`, `out`, `where`, `dtype`, and returns an array containing all the exponential values of the input array.

In this article, I will explain syntax and how to use the `numpy.exp()` function on single and multi-dimension arrays.

## 1. Quick Examples of NumPy Exponential Function

If you are in a hurry, below are some quick examples of how to use the NumPy exponential function.

``````
# Below are the quick examples

# Example 1: Get the exponential Value of single element
arr = np.exp(3)

# Example 2: Get the exponential values of multiple elements of 1-d array
arr = [2, 5, 8]
arr2 = np.exp(arr)

# Example 3: Get the exponential values of 2-D numpy array elements
arr = np.array([[4, 6, 3, 7], [8, 5, 2, 9]])
arr2 = np.exp(arr)

# Example 4: Use numpy.exp() function to graphical representation
arr = [1, 1.4, 1.8, 2, 2.6, 3]
out_array = np.exp(arr)
arr2 = [1, 1.3, 1.6, 2.3, 2.8, 3]
plt.plot(arr, arr2, color = 'green', marker = "*")

# Yellow for numpy.exp()
plt.plot(out_array, arr2, color = 'yellow', marker = "o")
plt.title("numpy.exp()")
plt.xlabel("X")
plt.ylabel("Y")
plt.show()
``````

## 2. Syntax of numpy.exp()

Following is the syntax of the `numpy.exp()` function.

``````
#Syntax of numpy.exp()
numpy.exp(arr, out = None, where = True, casting = ‘same_kind’, order = ‘K’, dtype = None)
``````

### 2.1 Parameters of numpy.exp()

• `arr :` Input array.
• `out :` An array where the result is stored. When provided, it must have the shape of the inputs.
• `where:` optional
• `dtype `– Type of the returned array and it is optional.

### 2.2 Return Value of numpy.exp()

This function returns an array containing all the exponential values of all elements of the input array.

## 3. Use NumPy exp() to get Exponential Value

This mathematical Python NumPy `exp()` function is used to calculate the exponential values of all the elements present in the input array.

``````
import numpy as np

# get the exponential Value of single element
arr = np.exp(3)
print(arr)

# Output
# 20.085536923187668
``````

### 3.2 Get the Exponential Values of Multiple Elements of 1-D Array

To calculate the exponential values of integer array elements by using the `numpy.exp()` function. For example,

``````
# Create an 1D input array
arr = [2, 5, 8]

# Get the exponential values of multiple elements of 1-d array
arr2 = np.exp(arr)
print (arr2)

# Output
# [   7.3890561   148.4131591  2980.95798704]
``````

## 4. Get the Exponential Values of 2-D NumPy Array Elements

Let’s use a 2-Dimensional array and get the exponential values for all elements in the array. Let’s create a 2-D NumPy array using numpy.array().

``````
# creating an 2D input array
arr = np.array([[4, 6, 3, 7], [8, 5, 2, 9]])

# get the exponential values of 2-D numpy array elements
arr2 = np.exp(arr)
print(arr2)

# Output
# [[5.45981500e+01 4.03428793e+02 2.00855369e+01 1.09663316e+03]
#  [2.98095799e+03 1.48413159e+02 7.38905610e+00 8.10308393e+03]]
``````

## 5. Use numpy.exp() Function to Graphical Representation

We can use NumPy `exp()` function and represent the value graphically using the MatLab library.

``````
import numpy as np
import matplotlib.pyplot as plt

# Use numpy.exp() function to graphical representation
arr = [1, 1.4, 1.8, 2, 2.6, 3]
out_array = np.exp(arr)
arr2 = [1, 1.3, 1.6, 2.3, 2.8, 3]
plt.plot(arr, arr2, color = 'green', marker = "*")

# yellow for numpy.exp()
plt.plot(out_array, arr2, color = 'yellow', marker = "o")
plt.title("numpy.exp()")
plt.xlabel("X")
plt.ylabel("Y")
plt.show()
``````

Yields below output.

You can see the Parabolic graph of the exp() function in Numpy.

## 6. Conclusion

In this article, I have explained how to use Python `numpy.exp()` function and how to calculate the exponential value of every element in the given array with examples by using 1-D and 2-D arrays.

Happy Learning!!

## References 