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More writing for the main posts
This commit is contained in:
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@ -3,7 +3,8 @@ import { randomBiUnit } from "../src/randomBiUnit";
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import { randomChoice } from "../src/randomChoice";
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import { plot } from "./plot"
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import {Transform} from "../src/transform";
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const iterations = 50_000;
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const quality = 0.5;
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const step = 1000;
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// hidden-end
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export type Props = {
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@ -20,8 +21,7 @@ export function* chaosGameWeighted(
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randomBiUnit()
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];
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// TODO: Explain quality
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const iterations = width * height * 0.5;
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const iterations = width * height * quality;
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for (let c = 0; c < iterations; c++) {
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// highlight-start
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const [_, xform] = randomChoice(transforms);
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@ -24,7 +24,7 @@ import banner from '../banner.png'
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I don't remember exactly when I first learned about fractal flames, but I do remember becoming entranced by the images they created.
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I also remember their unique appeal to my young engineering mind; this was an art form I could participate in.
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The original [Fractal Flame](https://flam3.com/flame_draves.pdf) describing their structure was too much
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The original [Fractal Flame Algorithm paper](https://flam3.com/flame_draves.pdf) describing their structure was too much
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for me to handle at the time (I was ~12 years old), so I was content to play around and enjoy the pictures.
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But the desire to understand it stuck around. Now, with a graduate degree under my belt, maybe I can make some progress.
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@ -35,7 +35,13 @@ can understand without too much prior knowledge.
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## Iterated function systems
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As mentioned above, fractal flames are a type of "[iterated function system](https://en.wikipedia.org/wiki/Iterated_function_system),"
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:::note
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This post covers section 2 of the Fractal Flame Algorithm paper
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:::
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As mentioned, fractal flames are a type of "[iterated function system](https://en.wikipedia.org/wiki/Iterated_function_system),"
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or IFS. Their mathematical foundations come from a paper written by [John E. Hutchinson](https://maths-people.anu.edu.au/~john/Assets/Research%20Papers/fractals_self-similarity.pdf),
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but reading that paper isn't critical for our purposes. Instead, we'll focus on building a practical understanding
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of how they work. The formula for an IFS is short, but will take some time to unpack:
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@ -65,7 +71,11 @@ export const simpleData = [
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</VictoryChart>
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However, this is a pretty boring image. With fractal flames, rather than listing individual points,
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we use functions to describe which points are part of the solution. This means there are an infinite
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we use functions to describe which points are part of the solution.
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TODO: Explain characteristics of the solution - fixed set
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This means there are an infinite
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number of points, but if we find _enough_ points to plot, we'll end up with a nice picture.
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And if we choose different functions to start with, our solution set changes, and we'll end up
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with a new picture.
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@ -73,10 +83,6 @@ with a new picture.
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However, it's not clear which points belong in the solution just by staring at the functions.
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We'll need a computer to figure it out.
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TODO: Other topics worth covering in this section? Maybe in a `details` block?:
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- Fixed sets: https://en.wiktionary.org/wiki/fixed_set
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- Compact sets
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### Transformation functions
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Second, $F_i(S)$. At their most basic, each $F_i$ is a function that takes in a 2-dimensional point and transforms
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@ -37,8 +37,6 @@ export default function FlameBlend() {
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const [xform3Variations, setXform3Variations] = useState(xform3VariationsDefault)
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const resetXform3Variations = () => setXform3Variations(xform3VariationsDefault);
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// Cheating a bit here; for purposes of code re-use, use the post- and final-transform-enabled chaos game,
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// and swap in identity components for each
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const identityXform: Transform = (x, y) => [x, y];
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useEffect(() => {
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@ -17,7 +17,7 @@ export default function FlamePost() {
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const resetXform2CoefsPost = () => setXform2CoefsPost(params.xform2CoefsPost);
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const [xform3CoefsPost, setXform3CoefsPost] = useState<Coefs>(params.xform3CoefsPost);
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const resetXform3CoefsPost = () => setXform1CoefsPost(params.xform3CoefsPost);
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const resetXform3CoefsPost = () => setXform3CoefsPost(params.xform3CoefsPost);
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const identityXform: Transform = (x, y) => [x, y];
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@ -25,7 +25,9 @@ export function* chaosGameFinal({width, height, transforms, final}: Props) {
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// highlight-end
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if (i > 20)
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// highlight-start
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plot(finalX, finalY, image);
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// highlight-end
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if (i % step === 0)
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yield image;
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@ -7,60 +7,55 @@ tags: []
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---
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Now that we have a basic chaos game in place, it's time to spice things up. Transforms and variations create the
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interesting patterns that fractal flames are known for.
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shapes and patterns that fractal flames are known for.
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<!-- truncate -->
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This blog post uses a set of reference parameters ([available here](../params.flame)) to demonstrate a practical
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implementation of the fractal flame algorithm. If you're interested in tweaking the parameters, or generating
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your own art, [Apophysis](https://sourceforge.net/projects/apophysis/) is a good introductory tool.
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:::note
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TODO: Include the reference image here
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This post uses a set of [reference parameters](../params.flame) to demonstrate a working
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implementation of the fractal flame algorithm. If you're interested in tweaking the parameters,
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or generating your own art, [Apophysis](https://sourceforge.net/projects/apophysis/)
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can load that file and gives full control over the image.
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:::
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## Transforms and variations
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:::note
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This post covers section 3 of the Fractal Flame Algorithm paper
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:::
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import CodeBlock from '@theme/CodeBlock'
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We previously introduced "transforms" as the "functions" of an "iterated function system." Their general format is:
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We previously introduced transforms as the "functions" of an "iterated function system," and showed how
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playing the chaos game leads to an image of Sierpinski's Gasket. Even though we used simple functions,
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the image it generates is exciting. But it's still not nearly as exciting as the images the Fractal Flame
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algorithm is known for.
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This leads us to the first big innovation of the Fractal Flame algorithm: using non-linear functions
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for the transforms. These functions are known as "variations":
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$$
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F_i(x,y) = (a_i \cdot x + b_i \cdot y + c_i, \hspace{0.2cm} d_i \cdot x + e_i \cdot y + f_i)
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F_i(x, y) = V_j(a_i \cdot x + b_i \cdot y + c_i, d_i \cdot x + e_i \cdot y + f_i)
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$$
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import coefsSrc from '!!raw-loader!../src/coefs'
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import variationSource from '!!raw-loader!../src/variation'
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<CodeBlock language={'typescript'}>{coefsSrc}</CodeBlock>
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<CodeBlock language="typescript">{variationSource}</CodeBlock>
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We also introduced the Sierpinski Gasket functions ($F_0$, $F_1$, and $F_2$), demonstrating how they are related to
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the general format. For example:
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Variations, labeled $V_j$ above, are functions just like transforms (we use $j$ to indicate a specific variation).
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They take an input point $(x,y)$, and give an output point. However, the sky is the limit for what variation functions do in between
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input to output. The Fractal Flame paper lists 49 different variation functions,
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and the official `flam3` implementation supports [98 different functions](https://github.com/scottdraves/flam3/blob/7fb50c82e90e051f00efcc3123d0e06de26594b2/variations.c).
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$$
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\begin{align*}
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F_0(x,y) &= \left({x \over 2}, {y \over 2}\right) \\
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&= (a_0 \cdot x + b_0 \cdot y + c_0, d_0 \cdot x + e_0 \cdot y + f_0) \\
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& a_0 = 0.5 \hspace{0.2cm} b_0 = 0 \hspace{0.2cm} c_0 = 0 \\
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& d_0 = 0 \hspace{0.2cm} e_0 = 0.5 \hspace{0.2cm} f_0 = 0
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\end{align*}
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$$
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TODO: Explain the applyCoefs function
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However, these transforms are pretty boring. We can build more exciting images by using additional functions
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within the transform. These "sub-functions" are called "variations":
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$$
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F_i(x, y) = V_j(a_i \cdot x + b_i \cdot y + c_i, \hspace{0.2cm} d_i \cdot x + e_i \cdot y + f_i)
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$$
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The fractal flame paper lists 49 variation functions ($V_j$ above), but the sky's the limit here.
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For example, the official `flam3` implementation supports
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[98 variations](https://github.com/scottdraves/flam3/blob/7fb50c82e90e051f00efcc3123d0e06de26594b2/variations.c).
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Our reference image will focus on just four variations:
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To draw our reference image, we'll focus on four variations:
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### Linear (variation 0)
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This variation returns the $x$ and $y$ coordinates as-is:
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This variation is dead simple: just return the $x$ and $y$ coordinates as-is.
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$$
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V_0(x,y) = (x,y)
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@ -70,11 +65,17 @@ import linearSrc from '!!raw-loader!../src/linear'
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<CodeBlock language={'typescript'}>{linearSrc}</CodeBlock>
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:::tip
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In a way, we've already been using this variation! The functions that define Sierpinski's Gasket
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apply the affine coefficients to the input point, and use that as the output point.
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:::
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### Julia (variation 13)
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This variation still uses just the $x$ and $y$ coordinates, but does crazy things with them:
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<small>TODO: Is this related to the Julia set?</small>
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This variation is a good example of the non-linear functions the Fractal Flame Algorithm introduces.
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It still receives an input point $(x, y)$, but does some crazy things with it:
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$$
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\begin{align*}
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@ -97,8 +98,8 @@ import juliaSrc from '!!raw-loader!../src/julia'
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### Popcorn (variation 17)
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This is known as a "dependent variation" because it depends on knowing the transform coefficients
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(specifically, $c$ and $f$):
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Some variations rely on knowing the transform's affine coefficients; these are known as "dependent variations."
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For the popcorn variation, we use the $c$ and $f$ coefficients:
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$$
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V_{17}(x,y) = (x + c \cdot \text{sin}(\text{tan }3y), y + f \cdot \text{sin}(\text{tan }3x))
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@ -110,7 +111,8 @@ import popcornSrc from '!!raw-loader!../src/popcorn'
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### PDJ (variation 24)
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This is known as a "parametric" variation because it has additional parameters given to it:
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Some variations have extra parameters that the designer can choose; these are known as "parametric variations."
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For the PDJ variation, there are four extra parameters we can choose:
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$$
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p_1 = \text{pdj.a} \hspace{0.2cm} p_2 = \text{pdj.b} \hspace{0.2cm} p_3 = \text{pdj.c} \hspace{0.2cm} p_4 = \text{pdj.d} \\
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@ -123,9 +125,9 @@ import pdjSrc from '!!raw-loader!../src/pdj'
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## Blending
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Now, one variation is fun, but we can also combine variations in a single transform by "blending."
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Now, one variation is fun, but we can also combine variations in a process called "blending."
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Each variation receives the same $x$ and $y$ inputs, and we add together each variation's $x$ and $y$ outputs.
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We'll also give each variation a weight ($v_{ij}$) to control how much it contributes to the transform:
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We'll also give each variation a weight (called $v_{ij}$) that changes how much it contributes to the transform:
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$$
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F_i(x,y) = \sum_{j} v_{ij} V_j(a_i \cdot x + b_i \cdot y + c_i, \hspace{0.2cm} d_i \cdot x + e_i \cdot y + f_i)
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@ -137,10 +139,15 @@ import blendSource from "!!raw-loader!../src/blend";
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<CodeBlock language={'typescript'}>{blendSource}</CodeBlock>
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And with that in place, we have enough to render a first full fractal flame.
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The sliders below change the variation weights for each transform (the $v_{ij}$ parameters);
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try changing them around to see which parts of the image are controlled by
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each transform.
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With that in place, we have enough to render a first full fractal flame. We'll use the same
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chaos game as before, but use our new transforms and variations to produce a dramatically different image:
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:::tip
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This image is interactive! The sliders change the variation weights ($v_{ij}$ parameters)
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so you can design your own image.
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Try using the sliders to find which parts of the image each transform controls.
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:::
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import {SquareCanvas} from "../src/Canvas";
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import FlameBlend from "./FlameBlend";
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@ -149,20 +156,40 @@ import FlameBlend from "./FlameBlend";
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## Post transforms
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After variation blending, we apply a second set of transform coordinates.
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Post transforms introduce a second affine transform, this time _after_ variation blending.
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We'll use introduce some new variables, but the post transform function should look familiar by now:
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The fractal flame below starts with the same initial transforms/variations as the previous fractal flame,
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$$
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\begin{align*}
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P_i(x, y) &= (\alpha_i x + \beta_i y + \gamma_i, \delta_i x + \epsilon_i y + \zeta_i) \\
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F_i(x, y) &= P_i\left(\sum_{j} v_{ij} V_j(x, y)\right)
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\end{align*}
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$$
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import postSource from '!!raw-loader!./post'
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<CodeBlock language="typescript">{postSource}</CodeBlock>
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The image below starts with the same initial transforms/variations as the previous fractal flame,
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but allows modifying the post-transform coefficients.
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$$
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P_i(x, y) = (\alpha_i x + \beta_i y + \gamma_i, \delta_i x + \epsilon_i y + \zeta_i)
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$$
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<details>
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<summary>If you want a challenge...</summary>
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Challenge 1: What post-transform coefficients will give us the previous image?
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Challenge 2: What post-transform coefficients will give us a _mirrored_ image?
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</details>
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import FlamePost from "./FlamePost";
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<SquareCanvas><FlamePost/></SquareCanvas>
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## Final transform
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## Final transforms
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import chaosGameFinalSource from "!!raw-loader!./chaosGameFinal"
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<CodeBlock language="typescript">{chaosGameFinalSource}</CodeBlock>
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import FlameFinal from "./FlameFinal";
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@ -4,4 +4,4 @@ import {Transform} from "../src/transform";
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import {applyCoefs} from "../src/coefs";
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// hidden-end
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export const transformPost = (transform: Transform, coefs: Coefs): Transform =>
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(x, y): [number, number] => applyCoefs(...transform(x, y), coefs)
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(x, y) => applyCoefs(...transform(x, y), coefs)
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@ -44,20 +44,6 @@ const PaletteBar: React.FC<PaletteBarProps> = ({height, palette, children}) => {
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)
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}
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const colorSwatchPainter = (palette: number[], color: number) =>
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(width: number, height: number) => {
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const [r, g, b] = colorFromPalette(palette, color);
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const image = new ImageData(width, height);
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for (let i = 0; i < image.data.length; i += 4) {
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image.data[i] = r * 0xff;
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image.data[i + 1] = g * 0xff;
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image.data[i + 2] = b * 0xff;
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image.data[i + 3] = 0xff;
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}
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return image;
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}
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type ColorEditorProps = {
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title: string;
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palette: number[];
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@ -1,9 +1,13 @@
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import {ChaosGameFinalProps} from "../2-transforms/chaosGameFinal";
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// hidden-start
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import {Props as ChaosGameFinalProps} from "../2-transforms/chaosGameFinal";
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import {randomBiUnit} from "../src/randomBiUnit";
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import {randomChoice} from "../src/randomChoice";
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import {camera, histIndex} from "../src/camera";
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import {colorFromPalette, paintColor} from "./paintColor";
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const quality = 15;
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const step = 100_000;
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// hidden-end
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export type TransformColor = {
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color: number;
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colorSpeed: number;
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@ -13,23 +17,21 @@ function mixColor(color1: number, color2: number, colorSpeed: number) {
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return color1 * (1 - colorSpeed) + color2 * colorSpeed;
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}
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export type ChaosGameColorProps = ChaosGameFinalProps & {
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type Props = ChaosGameFinalProps & {
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palette: number[];
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colors: TransformColor[];
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finalColor: TransformColor;
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}
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export function* chaosGameColor({width, height, transforms, final, palette, colors, finalColor, quality, step}: ChaosGameColorProps) {
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let iterations = (quality ?? 1) * width * height;
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step = step ?? 10_000;
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export function* chaosGameColor({width, height, transforms, final, palette, colors, finalColor}: Props) {
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let currentColor = Math.random();
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const red = Array(width * height).fill(0);
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const green = Array(width * height).fill(0);
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const blue = Array(width * height).fill(0);
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const alpha = Array(width * height).fill(0);
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const red = Array<number>(width * height).fill(0);
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const green = Array<number>(width * height).fill(0);
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const blue = Array<number>(width * height).fill(0);
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const alpha = Array<number>(width * height).fill(0);
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let [x, y] = [randomBiUnit(), randomBiUnit()];
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const iterations = width * height * quality;
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for (let i = 0; i < iterations; i++) {
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const [transformIndex, transform] = randomChoice(transforms);
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[x, y] = transform(x, y);
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@ -1,17 +1,19 @@
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// hidden-start
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import {randomBiUnit} from "../src/randomBiUnit";
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import {randomChoice} from "../src/randomChoice";
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import {ChaosGameFinalProps} from "../2-transforms/chaosGameFinal";
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import {Props as ChaosGameFinalProps} from "../2-transforms/chaosGameFinal";
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import {camera, histIndex} from "../src/camera";
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// hidden-end
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export type ChaosGameHistogramProps = ChaosGameFinalProps & {
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paint: (width: number, histogram: Uint32Array) => ImageData;
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}
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export function* chaosGameHistogram({width, height, transforms, final, quality, step, paint}: ChaosGameHistogramProps) {
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let iterations = (quality ?? 1) * width * height;
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step = step ?? 10_000;
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const histogram = new Uint32Array(width * height);
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const quality = 10;
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const step = 100_000;
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// hidden-end
|
||||
export type Props = ChaosGameFinalProps & {
|
||||
paint: (width: number, height: number, histogram: number[]) => ImageData;
|
||||
}
|
||||
export function* chaosGameHistogram({width, height, transforms, final, paint}: Props) {
|
||||
let iterations = quality * width * height;
|
||||
|
||||
const histogram = Array<number>(width * height).fill(0);
|
||||
|
||||
let [x, y] = [randomBiUnit(), randomBiUnit()];
|
||||
|
||||
@ -22,13 +24,18 @@ export function* chaosGameHistogram({width, height, transforms, final, quality,
|
||||
|
||||
if (i > 20) {
|
||||
const [pixelX, pixelY] = camera(finalX, finalY, width);
|
||||
const pixelIndex = histIndex(pixelX, pixelY, width, 1);
|
||||
histogram[pixelIndex] += 1;
|
||||
const hIndex = histIndex(pixelX, pixelY, width, 1);
|
||||
|
||||
if (hIndex < 0 || hIndex >= histogram.length) {
|
||||
continue;
|
||||
}
|
||||
|
||||
histogram[hIndex] += 1;
|
||||
}
|
||||
|
||||
if (i % step === 0)
|
||||
yield paint(width, histogram);
|
||||
yield paint(width, height, histogram);
|
||||
}
|
||||
|
||||
yield paint(width, histogram);
|
||||
yield paint(width, height, histogram);
|
||||
}
|
||||
@ -18,6 +18,10 @@ Can we do something more intelligent with that information?
|
||||
|
||||
## Image histograms
|
||||
|
||||
:::note
|
||||
This post covers sections 4 and 5 of the Fractal Flame Algorithm paper
|
||||
:::
|
||||
|
||||
To start with, it's worth demonstrating how much work is actually "wasted."
|
||||
We'll render the reference image again, but this time, set each pixel's transparency
|
||||
based on how many times we encounter it in the chaos game:
|
||||
|
||||
@ -1,17 +1,17 @@
|
||||
export function paintLinear(width: number, histogram: Uint32Array): ImageData {
|
||||
const image = new ImageData(width, histogram.length / width);
|
||||
export function paintLinear(width: number, height: number, histogram: number[]): ImageData {
|
||||
const image = new ImageData(width, height);
|
||||
|
||||
let countMax = 0;
|
||||
let valueMax = 0;
|
||||
for (let value of histogram) {
|
||||
countMax = Math.max(countMax, value);
|
||||
valueMax = Math.max(valueMax, value);
|
||||
}
|
||||
|
||||
for (let i = 0; i < histogram.length; i++) {
|
||||
const pixelIndex = i * 4;
|
||||
image.data[pixelIndex] = 0; // red
|
||||
image.data[pixelIndex + 1] = 0; // green
|
||||
image.data[pixelIndex + 2] = 0; // blue
|
||||
image.data[pixelIndex + 3] = Number(histogram[i]) / countMax * 0xff;
|
||||
image.data[pixelIndex] = 0;
|
||||
image.data[pixelIndex + 1] = 0;
|
||||
image.data[pixelIndex + 2] = 0;
|
||||
image.data[pixelIndex + 3] = histogram[i] / valueMax * 0xff;
|
||||
}
|
||||
|
||||
return image;
|
||||
|
||||
@ -1,5 +1,5 @@
|
||||
export function paintLogarithmic(width: number, histogram: Uint32Array): ImageData {
|
||||
const image = new ImageData(width, histogram.length / width);
|
||||
export function paintLogarithmic(width: number, height: number, histogram: number[]): ImageData {
|
||||
const image = new ImageData(width, height);
|
||||
|
||||
const histogramLog = new Array<number>();
|
||||
histogram.forEach(value => histogramLog.push(Math.log(value)));
|
||||
|
||||
@ -5,14 +5,15 @@ export type VariationBlend = [number, Variation][];
|
||||
export function blend(
|
||||
x: number,
|
||||
y: number,
|
||||
variations: VariationBlend): [number, number] {
|
||||
let [finalX, finalY] = [0, 0];
|
||||
variations: VariationBlend
|
||||
): [number, number] {
|
||||
let [outX, outY] = [0, 0];
|
||||
|
||||
for (const [weight, variation] of variations) {
|
||||
const [varX, varY] = variation(x, y);
|
||||
finalX += weight * varX;
|
||||
finalY += weight * varY;
|
||||
outX += weight * varX;
|
||||
outY += weight * varY;
|
||||
}
|
||||
|
||||
return [finalX, finalY];
|
||||
return [outX, outY];
|
||||
}
|
||||
@ -2,14 +2,11 @@ import { camera, histIndex } from "./camera"
|
||||
|
||||
export function plotBinary(x: number, y: number, image: ImageData) {
|
||||
const [pixelX, pixelY] = camera(x, y, image.width);
|
||||
if (
|
||||
pixelX < 0 || pixelX >= image.width || pixelY < 0 || pixelY > image.height
|
||||
) {
|
||||
const pixelIndex = histIndex(pixelX, pixelY, image.width, 4);
|
||||
if (pixelIndex < 0 || pixelIndex > image.data.length) {
|
||||
return;
|
||||
}
|
||||
|
||||
const pixelIndex = histIndex(pixelX, pixelY, image.width, 4);
|
||||
|
||||
image.data[pixelIndex] = 0;
|
||||
image.data[pixelIndex + 1] = 0;
|
||||
image.data[pixelIndex + 2] = 0;
|
||||
|
||||
@ -8,7 +8,7 @@
|
||||
--ifm-pre-padding: .6rem;
|
||||
|
||||
/* More readable code highlight background */
|
||||
--docusaurus-highlighted-code-line-bg: var(--ifm-color-emphasis-300);
|
||||
--docusaurus-highlighted-code-line-bg: var(--ifm-color-emphasis-200);
|
||||
|
||||
/*--ifm-code-font-size: 85%;*/
|
||||
}
|
||||
|
||||
Loading…
Reference in New Issue
Block a user