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My chaotic attractor. Made with #python #numpy #matplotlib and #marimo (and also #wigglystuff)

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Simone Conradi

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37,723 görüntüleme • 12 gün önce •via X (Twitter)

SanatEğitimBilim & Teknoloji#python#numpy#matplotlib#marimo#wigglystuff
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A simulation of the dielectric breakdown model described in Fractal Dimension of Dielectric Breakdown L. Niemeyer, L. Pietronero, and H. J. Wiesmann Phys. Rev. Lett. 52, 1033 – Published 19 March 1984 Made with #python, #numpy and #matplotlib.
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A simulation of the dielectric breakdown model described in Fractal Dimension of Dielectric Breakdown L. Niemeyer, L. Pietronero, and H. J. Wiesmann Phys. Rev. Lett. 52, 1033 – Published 19 March 1984 Made with #python, #numpy and #matplotlib.

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"I used to feel guilty in Cambridge that I spent all day playing games, while I was supposed to be doing mathematics. Then I realized that playing games is math." John H. Conway Made with #python #numpy #matplotlib

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The Aizawa Attractor. A simple equation, but beautiful chaotic pattern. [

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3D embedding of my polynomial roots #mathart. Made with #python #apple #MLX and #pyGFX. Original 2d version below 👇

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Math meets music, capturing chaos in 3D. The Aizawa chaotic attractor, coded with Grok 4.20. Sound on. 🔊

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Kinetic energy dissipation rate in two-dimensional turbulence. Logarithmic contours. Plots with Matplotlib Data available here: #Python script to generate plots: import numpy as np import matplotlib as mpl import matplotlib.colors as colors import matplotlib.pyplot as plt from netCDF4 import Dataset f1=Dataset(' mode='r') dissipation = f1.variables['dissipation'][:,:,:] x = f1.variables['x'][:] y = f1.variables['y'][:] n = dissipation.shape for k in range(0, n[0]): fig, ax = plt.subplots(1,1, figsize=(8,8)) cs1 = ax.contourf(x, y, dissipation[k,:,:], np.logspace(-5,1,101), cmap='Blues_r', extend='both', norm=colors.LogNorm()) ax.set_aspect('equal') ax.xaxis.set_ticks(range(0,7)) ax.yaxis.set_ticks(range(0,7)) ax.set_xlabel(r'$x$') ax.set_ylabel(r'$y$') fname = 'frame.' + str(k) + '.png' plt.savefig(fname, dpi=200, pad_inches = 0.1) print(fname) plt.close()

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Evidence that chaos can be beautiful. Built with Three.js and GLSL shaders, this integrates dx/dt=sin(y)−b x, dy/dt=sin(z)−b y, dz/dt=sin(x)−b z. At b≈0.19 the Thomas attractor settles into a stable yet chaotic 3D geometry. 🔊
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Evidence that chaos can be beautiful. Built with Three.js and GLSL shaders, this integrates dx/dt=sin(y)−b x, dy/dt=sin(z)−b y, dz/dt=sin(x)−b z. At b≈0.19 the Thomas attractor settles into a stable yet chaotic 3D geometry. 🔊

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