Hi Keyron,

For:

> Working on symbolic control systems and refactoring the old plots sounds
very fun, and I am interested in seeing how SymPy interoperates with NumPy
and Matplotlib. I align with the mission to make this system more
accessible, but I am less sure about where to start here - any pointers
would be greatly appreciated!

The key thing is that SymPy's control module should be unique from NumPy
based control tools in that it provides symbolic solutions. This new PR is
a nice example
https://github.com/sympy/sympy/pull/27717#issuecomment-2740523770 showing
how to compute the symbolic expressions that guarantee stability, rather
than trying to calculate numerically whether a system is stable. Of course
all symbolics in SymPy can be evaluated with numbers but the solutions our
control library makes should be useful on its own.

For plotting, we should be using SymPy's plotting package for the plots so
that we continually improve SymPy plot() to handle more advanced plots of
symbolic functions. Ideally the control package would generate its plots
with SymPy plot().

Jason
moorepants.info
+01 530-601-9791


On Wed, Mar 19, 2025 at 8:22 AM Keyron Linarez <keyronlina...@gmail.com>
wrote:

> Hello! My name is Keyron and I am a senior at Pomona College in Claremont,
> California. I am majoring in computer science with a minor in mathematics,
> and I am very interested in working with SymPy through GSoC. I love how
> community-oriented SymPy is, and I’d love to be a part of it while
> improving my programming and open-source skills!
>
> I have about 4 years of Python experience, gained through a combination of
> personal projects, reinforcement learning research, and data science work
> in my college courses. I am most comfortable in Python, but I am also
> proficient with Rust and Scala.
>
> I am very interested in control theory and machine learning; Currently, I
> am blending these interests in a personal project, where I am implementing
> model predictive control to autonomously drive a classic racing game,
> F-Zero!
>
> On the math side, I have discrete math and graph theory experience, gained
> through classes and research opportunities. I’ve also taken semester-long
> courses in Real Analysis, Data Mining, and Statistics for Data Science.
>
> I learned about SymPy last fall from my peer Tilo, who previously
> contributed through GSoC. Their work piqued my interest in open source, and
> I’ve begun working with him this semester in hopes of joining SymPy for the
> summer.
>
> Thus far, I’ve identified the following projects as the best suited to my
> skill set.
>
> 1. New Assumptions System:
>
> I would love to work on improving the new assumptions system, and I
> believe refactoring and speeding them up would make a great summer project.
> I’ve been working on this pull request (#27698
> <https://github.com/sympy/sympy/pull/27698> ), and plan on working on
> improving inequality handling with non-rational coefficients next. There is
> a lot of prior and continued work for the new assumptions system, and I
> would really love to be a part of it!
>
>
> 2. Symbolic Control Systems:
>
> Working on symbolic control systems and refactoring the old plots sounds
> very fun, and I am interested in seeing how SymPy interoperates with NumPy
> and Matplotlib. I align with the mission to make this system more
> accessible, but I am less sure about where to start here - any pointers
> would be greatly appreciated!
>
>
> I’d love to hear everyone’s thoughts on which of these projects would be
> the best fit for me, and any guidance on where to dive in—thank you!
>
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