quibbler VS matplotlib

I have been playing with this new open-source package for interactive data analysis called Quibbler (https://github.com/Technion-Kishony-lab/quibbler). Real fun to use and very little to learn - it just magically brings your standard Python code and analysis to life - automatically making your analysis and plots live and interactive! If you are interested in interactive data analysis/exploration with Python, I recommend trying it out.

Excited to launch "Quibbler", an open-source Python package for interactive data analysis. Fun to use. Nothing to learn. Your standard code effortlessly comes to life! With the amazing Maor Kern and Maor Kleinberger.

https://github.com/Technion-Kishony-lab/quibbler

See also our QUIBBLE COMPETITION:

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?