#Python fun with #matplotlib

#!/usr/bin/env python3
import matplotlib.pyplot as p,numpy as n
x,y=n.meshgrid(n.linspace(-4,4,512),n.linspace(-4,4,512))
z=(1-x/2+x**4+y**3)*n.exp(-x**2-y**2)*(1-x/3-y**4)*(3-y+x**2)
z+=.5*n.sin(.8*x+.6*y)+.4*n.cos(.5*x-.7*y)+.3*n.sin(.6*x-.4*y)
p.contour(x,y,z,levels=n.linspace(z.min(),z.max(),25),cmap='terrain')
p.show()

The #MatPlotLib maintainer vs vague #OpenClaw bot(?) makes my blood pressure rise.

Why this sort of behaviour specifically?
Because it was about 4 years ago that I started warning technical experts at my job about how the irresponsible release of AI software would soon waste their time.

And now it does and apparently it's seen as the new normal. No.

This is how our brains burn out, we stop caring and will start to feel lonely. People need to stop attacking each other with software that the other party has not consented to.

You can say no to the way people use or implement software that wastes your time and makes you unhappy. If they don't change their behaviour then you'll know that they are happy to remain ignorant. And you can place your boundaries accordingly.

And if you're overwhelmed by AI? Form expert groups, talk to human beings, hell, start meeting up!

https://www.tomshardware.com/tech-industry/artificial-intelligence/rogue-openclaw-ai-agent-wrote-and-published-hit-piece-on-a-python-developer-who-rejected-its-code-disgruntled-bot-accuses-matplotlib-maintainer-of-discrimination-and-hypocrisy-later-backtracks-with-an-apology

Graphs 2.0 migliora grafici scientifici, import dati, curve fitting e supporto mobile con tante novità per Linux e GNOME. #opensource #Linux #GNOME #Graphs #DataScience #Flatpak #Matplotlib #FOSS

https://www.linuxeasy.org/graphs-2-0-funzioni-avanzate-grafici-scientifici-analisi-dati/?utm_source=mastodon&utm_medium=jetpack_social

OK matplotlib, I love you, but now you're just messing with me.

When I try to put contours on the polar plot of these data it works if, and only if, the plot is part of a multiplot with at least 2 rows of axes. If I try to plot it by itself, or in a multiplot with only one row, then the contour function draws a spurious line right through it. Nothing else is different, it's exactly the same plotting code running on the same data, the only thing that I changed is the number of axes in the call to subplots().

Welp, guess I'm plotting an extra axes and then editing it out of the resulting image.

#matplotlib #python

I am thinking to do a “heatmap” of the muscles of the human body using #matplotlib. The idea is to have strength workouts point at different muscles and show that dynamically using matplotlib (see image). Maybe nuts not sure yet…

I was thinking to convert the #png to #svg and then with svgpath2mpl parse it to a matplotlib path (not sure yet if I can do more than one path) :

https://petercbsmith.github.io/marker-tutorial.html

Now, is there a better/easier way?

#python #svg #data #dataviz

It has been nearly two weeks since the World Chess Championship challengers were determined at the Candidates tournament in Cyprus. But what path did 🇮🇳 Vaishali Rameshbabu and 🇺🇿 Javokhir Sindarov take on their path to qualifying?

🇳🇱 Anish Giri's second place score in the open (+3) would have been enough to win the event in the women's section.

#Chess #FIDE #FIDECandidates #CandidatesTournament #Cyprus #graph #graphs #matplotlib

Matplotlib для самых маленьких: от пустого окна до красивого графика

Каждый, кто начинал визуализировать данные на Python, сталкивался с этим: берешь кусок кода со StackOverflow, пытаешься подвинуть легенду или добавить вторую ось, и внезапно весь график ломается. А главное — почему одни пишут plt.plot(), а другие ax.plot()? Какой синтаксис правильный? В этом туториале мы не просто нарисуем пару линий. Мы заглянем под капот Matplotlib и разберем «анатомию» графиков на простых примерах. Вы поймете разницу между процедурным и объектно-ориентированным подходом, научитесь кастомизировать основные типы визуализаций и навсегда избавитесь от ошибки «белого квадрата» при сохранении файлов.

https://habr.com/ru/articles/1028868/

#matplotlib #python #python3 #python_для_начинающих #python_3 #визуализация #графики

Simone Conradi, Theoretical physics PhD
Università degli Studi di Genova

Roots of a parametric polynomial.

Made with #Python #NumPy and #Matplotlib