numpy.sort_complex() in python

Introduction

When working with arrays of complex numbers in Python, organizing them in a meaningful order can be important. NumPy offers the numpy.sort_complex() function, which helps sort complex numbers by their real parts and, when needed, their imaginary parts. This is especially useful in fields like signal processing, engineering, and scientific computing.

Function Syntax

The function has a very simple syntax:

numpy.sort_complex(a)

a: A NumPy array (or array-like object) containing complex numbers.

How It Sorts

The numpy.sort_complex() function sorts complex numbers in a lexicographical order:

• First, by their real parts in ascending order.
• Then, if the real parts are equal, by their imaginary parts.

This means a number like 2 + 1j will come before 2 + 2j.

Basic Example

Here's a quick example to show how it works:

import numpy as np

arr = np.array([4 + 0j, 2 + 3j, 1 + 2j, 2 + 1j])
sorted_arr = np.sort_complex(arr)
print(sorted_arr)

Output:

[1.+2.j 2.+1.j 2.+3.j 4.+0.j]

Working with NaN Values

If the array contains NaNs (either in the real or imaginary part), they are sorted to the end of the array. NumPy handles NaNs according to this extended rule:

• Real: [R, nan]
• Complex: [R + Rj, R + nanj, nan + Rj, nan + nanj]

Here, R stands for any non-NaN real value. Within the same NaN group, sorting is applied to the part that’s not NaN.

Use Cases

This function is especially helpful when you're dealing with:

• Electrical circuit simulations involving impedance (which is complex).
• Sorting signal data for Fourier transforms.
• Preparing complex-valued data for visualizations.

Conclusion

The numpy.sort_complex() function provides an easy way to sort arrays of complex numbers based on their real and imaginary components. Whether you're cleaning up data, analyzing signals, or preparing results for plotting, this function is a helpful utility in the NumPy toolkit.