Python NumPy real Function

🎓 Top 15 Udemy Courses (80-90% Discount): My Udemy Courses - Ramesh Fadatare — All my Udemy courses are real-time and project oriented courses.

▶️ Subscribe to My YouTube Channel (178K+ subscribers): Java Guides on YouTube

▶️ For AI, ChatGPT, Web, Tech, and Generative AI, subscribe to another channel: Ramesh Fadatare on YouTube

The real function in Python's NumPy library is used to extract the real part of complex numbers in an array. This function is essential in various fields such as signal processing, control systems, and scientific computing where dealing with complex numbers is required.

Table of Contents

1. Introduction
2. Importing the numpy Module
3. real Function Syntax
4. Understanding real
5. Examples
   • Basic Usage
   • Applying real to Arrays
   • Handling Special Values
6. Real-World Use Case
7. Conclusion
8. Reference

Introduction

The real function in Python's NumPy library allows you to extract the real part of complex numbers in an array. This function is particularly useful in numerical computations where only the real part of complex numbers is needed.

Importing the numpy Module

Before using the real function, you need to import the numpy module, which provides the array object.

import numpy as np

real Function Syntax

The syntax for the real function is as follows:

np.real(val)

Parameters:

• val: The input array containing complex numbers.

Returns:

• An array containing the real parts of the complex numbers in the input array.

Understanding real

The real function extracts the real part of each element in the input array. For complex numbers, it returns the real part, and for real numbers, it returns the numbers themselves.

Examples

Basic Usage

To demonstrate the basic usage of real, we will extract the real part of a single complex number.

Example

import numpy as np

# Complex number
z = 1 + 2j

# Extracting the real part
real_part = np.real(z)
print(f"Real part: {real_part}")

Output:

Real part: 1.0

Applying real to Arrays

This example demonstrates how to apply the real function to an array of complex numbers.

Example

import numpy as np

# Array of complex numbers
z = np.array([1 + 2j, 3 + 4j, 5 + 6j])

# Extracting the real parts
real_parts = np.real(z)
print(f"Real parts: {real_parts}")

Output:

Real parts: [1. 3. 5.]

Handling Special Values

This example demonstrates how real handles special values such as purely real numbers and zero.

Example

import numpy as np

# Array with special complex numbers
z = np.array([1 + 0j, 0 + 1j, 1, 0])

# Extracting the real parts
real_parts = np.real(z)
print(f"Real parts: {real_parts}")

Output:

Real parts: [1. 0. 1. 0.]

Real-World Use Case

Signal Processing: Extracting Real Part of Signals

In signal processing, the real function can be used to extract the real part of a complex signal, which is crucial for analyzing real-valued signals derived from complex data.

Example

import numpy as np

# Example complex signal
complex_signal = np.array([1 + 1j, 0.707 + 0.707j, 0 + 1j, -0.707 + 0.707j])

# Extracting the real part of the signal
real_signal = np.real(complex_signal)
print(f"Real Signal: {real_signal}")

Output:

Real Signal: [ 1.     0.707  0.    -0.707]

Conclusion

The real function in Python's NumPy library is used for extracting the real part of complex numbers in an array. This function is useful in various numerical and data processing applications, particularly those involving complex numbers and signal processing. Proper usage of this function can enhance the accuracy and efficiency of your computations.

Reference

Python NumPy real Function