.exp()

The np.exp() function in NumPy computes the exponential of all elements in the input array. The exponential function, np.exp(x), returns e^x, where e is Euler’s number with an approximate value of 2.71828. As a part of NumPy, a widely used library for numerical computing in Python, this function is particularly useful in scientific computations where exponential functions are common.

Syntax

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

Parameters:

• arr: The input array or list for computing the exponential.
• out: The location to store the result. It must be broadcastable to the shape of arr.
• where: The condition to be checked. When True, the function is applied and when False, the original values are retained.
• casting: Controls the type of data casting that may occur.
• order: Defines the memory layout order of the result: C for C-order, F for Fortran-order, A for automatic, and K for input layout.
• dtype: Overrides the data type of the resultant array.

Return Value:

The np.exp() function returns a new array containing the exponential of all elements in the input array.

Note: In the np.exp() function, the only mandatory parameter is arr. All other parameters, including out, where, casting, order, and dtype, are optional and have default values.

Example 1: Using .exp() with an Array

This example uses the np.exp() function to compute the exponential of all elements in the given array:

import numpy as np

# Create an array
arr = np.array([0, 1, 2, 3])

# Compute the exponential of all elements in the array
result = np.exp(arr)

# Print the result
print("Exponential of input array:", result)

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The output for the example will be:

Exponential of input array: [ 1.          2.71828183  7.3890561  20.08553692]

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Example 2: Using .exp() with a Positive Number

This example uses the np.exp() function to compute the exponential of a positive number:

import numpy as np

# Compute the exponential of 5
result = np.exp(5)

# Print the result
print("Exponential of 5:", result)

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The output for the example will be:

Exponential of 5: 148.4131591025766

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Codebyte Example: Using .exp() with a Negative Number

This codebyte example uses the np.exp() function to compute the exponential of a negative number:

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Frequently Asked Questions

1. Can I use np.exp() with a list?

Yes, np.exp() can be used with a list; it automatically converts the list to a NumPy array and applies the exponential function element-wise.

2. Does NumPy exp work with complex numbers?

Yes, np.exp() supports complex numbers and returns the exponential of each complex input using Euler’s formula.

3. What is the difference between math exp and NumPy exp?

math.exp() works only with single scalar values, while np.exp() can handle arrays, lists, and complex numbers, applying the function element-wise.