I'm a physics engineeering student, and I spend a lot of my time writing numerical simulations and analyzing data.
Programming in C++ is enjoyable, but most of numerical computing libs in are just unpleasant to use. So I started building my own solution in my free time.
GitHub: https://github.com/mslotwinski-dev/NumC
Some of the things I built into it:
You can write mathematical expressions naturally, like sin(x) * exp(-x), and differentiate or integrate them in a single line thanks to lazy expression trees.
It has a built-in plotting engine, so you can display graphs in a native Win32 window or export them as clean SVGs ready to drop into a LaTeX report.
Of course, the project won't surpass the quality of professional libraries. Its goal is to be convenient and accessible for users whose passions lie more in math, rather than programming.
If you're using C++ for simulations, numerical methods, physics, or data analysis, I'd really appreciate any feedback.
What was written by AI?
Most of the project, its entire idea, design, aesthetics and UX was programmed manually by me. I often used the textbook "Numerical methods in engineering with python" by Kiusaalas. Which doesn't mean that I didn't manage to do everything myself.
AI was used to write all the documentation (I wish I were fluent enough in English that it would take a finite amount of time). It was also used to write parts of simple algorithms that I knew but would be extremely tedious to implement by hand, or to improve the performance of algorithms that could be written better.
I'm aware of the ethical aspects of using AI, so I wanted to be honest and describe which things I did on my own and which I did with the help of LLM. At the same time, bearing in mind that this is a project that can help many people in their scientific work and studies, I hope that the benefits outweigh all the evil that LLMs cause.
