👀 Views: 1064 💬 Answers: 1 📅 Created: 2025-06-11

numpy complex-numbers diff data-analysis Python

I'm working with an scenario when using `np.diff` on an array of complex numbers... Specifically, I expected the output to reflect the differences in both the real and imaginary parts, but it seems like the results are only considering the magnitude. Here’s a simplified version of what I’m doing: ```python import numpy as np complex_array = np.array([1+2j, 3+4j, 5+6j]) differences = np.diff(complex_array) print(differences) ``` When I run this code, I get the output: ``` array([2.+2.j, 2.+2.j]) ``` However, I was expecting to see the differences calculated as follows: - For the first element: (3+4j) - (1+2j) = 2 + 2j - For the second element: (5+6j) - (3+4j) = 2 + 2j So far, I’ve confirmed that the output matches my expectations, but when I try to apply further operations on the result, such as finding the magnitude: ```python magnitudes = np.abs(differences) print(magnitudes) ``` I get: ``` array([2.82842712, 2.82842712]) ``` This output seems correct, but when I visualize the differences using a plot, they appear to be offset in a way that I didn’t expect, leading to confusion in interpreting the data. Is there a specific behavior I should be aware of when using `np.diff` with complex numbers? I thought the function should handle complex values similarly to real values. Am I misunderstanding how the differences are being computed or how to interpret the result? Any insights or best practices for working with differences in complex arrays would be greatly appreciated.