I had never implemented a marching squares algorithm, so I decided to give it a go. Consider this a late submission to #genuary13 'Something you’ve always wanted to learn'. 😅

haven't had much time for #genuary #genuary2023 so I'm packing 'em in — this is #genuary6 "Steal Like An Artist" (after Helen Lundeberg), #genuary17 "A grid inside a grid inside a grid" and #genuary13 "Something you've always wanted to learn" (Chaikin's algorithm)

Not on schedule, but who cares...
#genuary13 Something you’ve always wanted to learn
#genuary #generativeart #digitalart #creativecoding

Trippy Tiles

This matches half a dozen different #genuary prompts (loop, tessellation, intersections, sines), but I'll go with
#Genuary13: Something you’ve always wanted to learn

#genuary2023 #Processing #glsl

Landscaping

#genuary13 #GenArt #vertexcity #openrndr

RT @alexis_o_O@twitter.com

Something you’ve [always] wanted to learn, something I'll need tomorrow tapes on random path... #genuary day 13.
#genuary13 #genuary2023

🐦🔗: https://twitter.com/alexis_o_O/status/1613880877158748162

#genuary13 I always wanted to learn shaders. So here is my first one on shadertoy

https://www.shadertoy.com/view/DtBGWG

#genuary #genuary2023 #shadertoy

Day 13 – Something you've always wanted to learn.

Noise that loops both temporally and spatially, a continuation of something I tackled last year.

#genuary #genuary2023 #genuary13 #blender #b3d #geometrynodes #generativeart #phenakistiscope #zoetrope #stroboscope #animation

Only partially learnt it but got a point cloud from a mesh and animated transitions with #r3f . Did want too animate between two shapes but got a little confused about how to pass the second position as an attribute?

#genuary #genuary2023 #genuary13

https://tomjhinton.github.io/genuary23/#/always

Oh my, tomorrow's prompt is "sine waves". Should have looked at that before I wrote this sketch for #genuary13. Heh.

I also had to jump back and pick up #genuary13, which I missed yesterday. The prompt is "Something you’ve always wanted to learn", which is inevitably a vast topic. I implemented Sinuous Meander patterns (based on Whewell equations) as described by David Chappell. See https://archive.bridgesmathart.org/2012/bridges2012-183.pdf and https://www.tandfonline.com/doi/abs/10.1080/17513472.2015.1092859. #genuary https://editor.p5js.org/isohedral/sketches/a_fcgs1uz

= SIHAWTL! =
"Something you’ve always wanted to learn"
genuary2023 prompt 13
.
.
#genuary2023 #genuary #genuary13 #tessellation #p5js #webgl #3d #generative #CreativeToots

#genuary13 & #genuary14 - I've always wanted to learn L-systems, so I took an approach to create some Aesemic characters. Heres the result! #genuary #genart #genuary2023

Generative music part II, this time with something I've always wanted to learn: raw webaudio API. Let's start with a simple ambient generative patch...

🔊 https://houdard.net/genuary-2023-13/

#genuary13 #genuary

For #genuary13: to just sit down and read/watch people play/explain their adventures in making generative art.
Currently into curves thanks to Keith Peters: http://www.bit-101.com/blog/
:)

"Something you’ve always wanted to learn."

I've always loved the look of flow fields. I found a great explanation by Hadeel Alharthi and produced this. Just scratching the surface but excited to explore this technique more.

#genuary #genuary2023 #genuary13 #processing #creativecode #creativecodeart

Genuary 2023 day 13: Something you’ve always wanted to learn

#genuary #genuary13 #p5js

I thought about working on shaders, or reaction-diffusion algorithms, but I was pretty tired today and didn't feel up for that, so instead I forked day 8's sketch and delved deeper into signed distance functions, which I had been looking forward to learning about this month. I'm really pleased that I managed to make exactly what I had envisioned. SDFs are great!

https://openprocessing.org/sketch/1794508

"""
sketch_2022_01_13 #Processing

Learning how to make a np_array based Py5Image for #SDF exploration #Python #py5 #genuary #genuary13
"""
import py5
import numpy as np

def setup():
global HW, HH, img
py5.size(600, 600)
HW = py5.width / 2
HH = py5.height / 2
img = py5.create_image(600, 600, py5.ALPHA)

def L(x, y): return np.linalg.norm((x, y)) # return (x * x + y * y) ** 0.5

@np.vectorize
def vsdf(x, y, xo):
ring = abs(L(x - 50, y - 50) - 100 + xo) - 50
return min(y + 2 * xo, ring, x + 2 * xo)

def draw():
py5.translate(HW, HH)
xg, yg = np.mgrid[-300:300, -300:300]
dg = vsdf(xg, yg, py5.mouse_x - HW)
py5.create_image_from_numpy(dg, 'L', dst=img)
py5.image(img, -HW, -HH)

py5.run_sketch()

The prompt for #genuary today was "Something you've always wanted to learn". So I decided to play around with Verlet Physics thanks to this fantastic resource: https://datagenetics.com/blog/july22018/index.html
#pico8 #genuary13

Worked on shaders and I definitely understand them better now. I was able to reuse my SDF code in the shader.

"Genuary 13: Something you’ve always wanted to learn"

#genuary #genuary2023 #genuary13 #learning