Man Spends 7 Years Drawing Incredibly Intricate Maze Almost 30 years ago a Japanese custodian sat in front of a large A1 size sheet of white paper, whipped out a pen and started drawing the beginnings of diabolically complex maze, each twist and turn springing spontaneously from his brain onto the paper without aid of a computer. The hobby would consume him as he drew in his spare time until its completion nearly 7 years later when the final labyrinth was rolled up and almost forgotten. Twitter user @Kya7y was recently going through some of her father’s old things (he’s still a custodian at a public university) when she happened upon the maze and snapped a few photos to share on Twitter. She was quickly inundated by requests from friends and eventually strangers who had endless questions, the most obvious being: are you making prints!? Update: Prints now available over in the Spoon & Tamago shop, just $40.
Built-in types One-Dimensional Line Polynomial Gaussian peak Lorentzian peak Exponential with X offset constant Double Exponential with X offset constant Exponential Double Exponential Sin Hill Equation Sigmoid Power Lognormal Two-Dimensional Gaussian Polynomial All built-in nonlinear fit functions feature automatic initial guess generation. Override automatic initial guesses with your own. Hold any fit coefficient.
Daniel Pielucha See more of Daniel's paintings here. Thanks to Paul Rumsey for mentioning this artist to me. Drawing from noise, and then making animated loopy GIFs from there. – necessary-disorder tutorials This tutorial will focus on explaining how to draw things from noise functions in Processing, and then will present an automatic way to produce GIFs that loop well from a noise-based drawing. It will explain how to obtain the following GIFs with the same animation technique : Most of my latest gifs have all used this same trick I will present here, so I thought it was worth sharing it. About noise functions First of all let’s explain a little bit noise functions. Processing has a function noise() that produces values between 0 and 1, centered on 0.5 given some inputs. Let’s show with a quite short code what noise() gives us : Result : The parameter scale is used because without it the values changed too fast. Beware that the noise function is symmetrical (noise(x) = noise(-x)). Everytime the sketch is launched, the curve looks different. That was 1-dimensional noise. 2-dimensional noise takes 2 float values and returns a value between 0 and 1. To make it loop we’ll need 4-dimensional noise.
The Poetics of Space Sometimes the house of the future is better built, lighter and larger than all the houses of the past, so that the image of the dream house is opposed to that of the childhood home…. Maybe it is a good thing for us to keep a few dreams of a house that we shall live in later, always later, so much later, in fact, that we shall not have time to achieve it. For a house that was final, one that stood in symmetrical relation to the house we were born in, would lead to thoughts—serious, sad thoughts—and not to dreams. It is better to live in a state of impermanence than in one of finality. Chapter 2: House and Universe: section VIII Camille Paglia has listed it as an influence on her 1990 work of literary criticism Sexual Personae.[1] Review[edit] Joan Ockman. References[edit]
Art From Code » Random Lissajous Webs Start out as Lissajous Curves, but velocity is allowed to vary randomly. This entry was posted in lines, particles. Bookmark the permalink. Follow any comments here with the RSS feed for this post. or leave a trackback. Ten Must-See Art Documentaries | Art School Guide NodeBox | Home Home Welcome to NodeBoxNodeBox is a Mac OS X application that lets you create 2D visuals (static, animated or interactive) using Python programming code and export them as a PDF or a QuickTime movie. NodeBox is free and well-documented. Read more » News NodeBox Workshops: view the results of current and past NodeBox workshops. Current projects NB3 NodeBox 3: NodeBox 3 is cross-platform and has a node-based GUI. NOGL NodeBox for OpenGL: cross-platform version developed for rendering fast animation of images. Gallery favorites
Drawing vector field | GenerateMe The goal During last few days I’ve made several attempts to create and visualize 2D vector fields. In the following article you can read about this concept with several examples and code in Processing. There are many beautiful art/code based on vector field visualization around the net. Mostly based on noise function. What is the vector field? Vector field (in our case) is just a to function exatly the same as variation described in my previous post about Folds. Why vector? as vector for each point from 2d plane. Vector fields can be visualised in the following way How to get the vector field The main goal, in this article, is to research various ways to create vector fields. We can operate on functions which returns pair of values like variations. The second option is to get single float number like from noise(), dist() between points or dot product of vectors, etc. Drawing method The method is quite simple. Step 4 is key here. The general flow for constructing vector field follows this scheme: or
necessary-disorder tutorials « XenoFlora 001 (Process 2x2) » par Frederik Vanhoutte Art mural Poster Impression sur toile Impression photo Impression rigide Impression artistique Impression encadrée Impression métallique Maison Bloc acrylique Chargement de plus d'œuvres par Frederik Vanhoutte... desktop tablet-landscape content-width tablet-portrait workstream-4-across phone-landscape phone-portrait Complexification LIVING WORKS binary.ring bit.10001 bone.piles box.fitting box.fitting.img new bubble.chamber buddhabrot city.traveler cubic.attractor deep.lorenz guts new happy.place new henon.phase henon.phase.deep new inter.aggregate new inter.momentary new invader.fractal limb.sand.stroke limb.strat limb.stroke mcp moonlight.soyuz nine.block node.garden new offspring orbitals new paths.i peter.de.jong sand.dollar sand.stroke sand.traveler new self-dividing.line stitches substrate new tree.garden.ii trema.disk trema.spike INFORMATION about the programmer about the medium ORDERING works available production qualities ordering policies CONTACT j.tarbell @ complexification.net
Random Walk from Processing to Tableau » Tableau Picasso For another submission to Viz as Art contest at Tableau, I wanted to create something involving randomness and random walk specifically. But I found that the classic random walk algorithm creates results that are, well…too random, as opposed to the organic, botanical shapes I was looking for. Luckily, someone has already thought of developing a “Random Walk with Transition Probabilities that Depend on Direction of Motion”. It sounds nerdy, but that is just the recipe that Mother Nature uses to build branches on a blueberry bush, dandelion’s see head or the maple tree outside my window. In particular, a particle always moves forward and changes direction or stays the course dependent on a given probability. As with Lorenz Attractor visualization, I wrote a program in Processing to generate the points and export them to a text file. Just by changing one or two parameters, one can create an infinite number of patterns, some more organic looking than others.
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