Another one! Made with #python #numpy #matplotlib and #marimo... (and also #wigglystuff)show more

Made with #python #numpy #matplotlib and #marimo (and also #wigglystuff)

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.show more

"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 #matplotlibshow more

There's a sequence to it. First you fall for... marimo , and the reactive DAG that makes a notebook feel alive. Then for wigglystuff, Vincent D. Warmerdam anywidgets, dropping into a cell and starting a quiet conversation with everything downstream. Loving #marimo notebook!show more

A classic Monte Carlo simulation, it takes me right... back to my student days. 16 cars of equal length park at random along a street 20 cars long. #builtWithMarimo #python #numpy #matplotlib Thanks Claude Code for drawing nice cars in matplotlib 😀show more

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

I MADE ANOTHER ONE BUT WITH BEAR

Also made one for Schnee and its probably the... best one I've made so far 🦆🦆🦆🦆🦢show more

left: original video right: 100% AI video made with... another one stupid easy prompt and higgsfield genjutsu ps: I made the woman's voice ridiculous on purposeshow more

I made another one with just dongle gongle

Another one. Another one. And another one. #FanaticsFest

Made another one. Tell me what you think and... if you want more of this !show more

Chelsea lost one ragebaiter and replaced him with another.

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()show more

In 2014, my husband I went to the Museum... of the Moving Image and made one of the flip books souvenirs. 12 years later, he took our daughter and made another one. 🥲show more