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#scipy

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Dear LazyWeb: is there a C/C++, #RustLang or #Zig equivalent of #SciPy’s `stats` module for statistical analysis? Namely:
• a collection of common PDFs (probability density functions);
• MLE (maximum likelihood estimation) for these common distributions;
• KDE (kernel density estimation).

SciPy’s API is a pleasure to work with. Anything that comes close but usable from C/C++/Rust/Zig would make my life so much easier. Boosts appreciated for visibility.

🚀 Save the Date: #EuroSciPy2025 is Coming!

Mark your calendars! 📅

📍 Where: Kraków, Poland
📆 When: 18–22 of August
🌍 Why: European conference for scientific computing in #Python!

Join us for cutting-edge talks, hands-on tutorials, and unparalleled networking with the brightest minds in the #SciPy ecosystem.

Whether you’re expert or just starting your Python journey, EuroSciPy 2025 is the place to be! Stay tuned for more details. 💡🐍

Continued thread

But wait, there's more! 🚨 We are gearing up to release *napari 0.6.0*! 🚨 Come be the first to hear about everything that's coming! There's cool new features, major bug fixes, and we are migrating to @pydantic v2 and #Python 3.10+.

And remember, you can add your own items to the agenda!

Not the right time for you? Remember that we have meetings for people around the world. 🌏🌍🌎 Check out our calendar at:

napari.org/stable/community/me

See you soon! 📅

(2/2) (fin)

napari.orgMeeting schedule — napari

Comparing a naive "nearest neighbor" #TravellingSalesmanProblem solver with a #2optSwap one, adding a #DelaunayTriangulation mesh, it shows how often the better solution falls into the triangulation!

The #py5 sketch is interactive, you can generate other random nodes and move them around dragging with the mouse.

Code at: github.com/villares/sketch-a-d
More sketch-a-day: abav.lugaralgum.com/sketch-a-d
If you like this, support my work: paypal.com/donate/?hosted_butt
#scipy #Processing #Python #TSP #CreativeCoding

Scipy 1.15.0 is out!
docs.scipy.org/doc/scipy/relea

Some of my favorite features are the new `differentiate` submodule that can compute numerical derivatives of functions with an auto-adaptive stepsize, and the brand new `stats` API that defines probability distributions as Python classes that you can compute with (for example `exp(Normal())` to create a log-normal distribution)! 🤩

And I also did one thing! I allowed the `integrate.trapezoid` function to work with non-numpy arrays 😊

docs.scipy.orgSciPy 1.15.0 Release Notes — SciPy v1.15.0 Manual

Optimal rational approximation using SciPy

In this article we solve a non-linear curve fitting problem using the SciPy library. SciPy is especially well-suiting to solving this type of problem, as it includes a variety of functions for fitting and optimizing non-linear functions.

Along the way, we illustrate how to use SciPy's curve_fit and minimize functions for this type of task. In addition, we look at some good practices to apply when solving this type of problem.
#python #scipy #orms
solvermax.com/blog/optimal-rat