PyQtGraph VS matplotlib

PyQtGraph - Interactive and realtime 2D/3D/Image plotting and science/engineering widgets.

Image, 3D, or data visualization applications using OpenCV and the SciPy ecosystem. The Graphics View Framework can display an image and let the user interact with it, and the Python ecosystem is very rich for image processing, data analysis, and visualization. For example, LabelMe for image labeling, PyQtGraph for scientific graphics, or custom QWidget integration in Maya.

I don't think that's related to your error though - from the backtrace, it looks like the plotWidget has plotItem attribute that's somehow been assiged to itself (or maybe some other PlotWidget) , so is just endlessly recursing as it tries to proxy the same attribute lookup (presumably 'clear') to itself. Looking at the source, the plotitem is either created as a new PlotItem() object if not provided, or passed in to the constructor, so I'd check how this gets initialised - eg. does this get set as a property in your .ui file? Are you setting it to the widget itself somehow?

I did something like this recently but I used pyqtgraph: https://www.pyqtgraph.org/

Ah, I agree, Matplotlib is for publication, so slow and pretty. For fast, I use pyqtgraph, which can do that 10 million point plot interaction. And since it's QT, it integrates seamlessly into QT applications.

Github: https://github.com/matplotlib/matplotlib

as suggested here.

Tool: Matplotlib Pyplot

The issue was described here: https://github.com/matplotlib/matplotlib/issues/8409, but the "solution" was just "this is fixed" which was not helpful to me.

Matplotlib: Matplotlib is a 2D plotting library that allows you to create visualizations of your data. It's a powerful tool for data analysis, but the syntax can be complex and the customization options can be overwhelming. GitHub - https://github.com/matplotlib/matplotlib

A quick google shows: this history.txt:

Let's take a small subset i.e 20 data points of our prediction and compare it with actual output using matplotlib library

I will think more about what I want to say next, but for now, I would like to say that I need the super-particles and PIC methods as I think that is the way forward for me. Are there ways to implement these methods in matplotlib, Visit or Paraview? Do I take existing code and import it into those programs to visualize it? Or can I directly program/simulate something in those visualizion tools without needing to import any code?