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Fix eslint issues
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@facelessuser
facelessuser committed Dec 20, 2023
1 parent 86312ac commit 2e95b69
Showing 1 changed file with 117 additions and 117 deletions.
234 changes: 117 additions & 117 deletions src/spaces/hct.js
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Original file line number Diff line number Diff line change
Expand Up @@ -5,111 +5,111 @@ import {fromCam16, toCam16, environment} from "./cam16.js";
import {WHITES} from "../adapt.js";

const white = WHITES.D65;
const ε = 216/24389; // 6^3/29^3 == (24/116)^3
const κ = 24389/27; // 29^3/3^3
const ε = 216 / 24389; // 6^3/29^3 == (24/116)^3
const κ = 24389 / 27; // 29^3/3^3

function toLstar (y) {
// Convert XYZ Y to L*
// Convert XYZ Y to L*

const fy = (y > ε) ? Math.cbrt(y) : (κ * y + 16) / 116;
return (116.0 * fy) - 16.0;
const fy = (y > ε) ? Math.cbrt(y) : (κ * y + 16) / 116;
return (116.0 * fy) - 16.0;
}

function fromLstar (lstar) {
// Convert L* back to XYZ Y
// Convert L* back to XYZ Y

return (lstar > 8) ? Math.pow((lstar + 16) / 116, 3) : lstar / κ;
return (lstar > 8) ? Math.pow((lstar + 16) / 116, 3) : lstar / κ;
}

function fromHct (coords, env) {
// Use Newton's method to try and converge as quick as possible or
// converge as close as we can. While the requested precision is achieved
// most of the time, it may not always be achievable. Especially past the
// visible spectrum, the algorithm will likely struggle to get the same
// precision. If, for whatever reason, we cannot achieve the accuracy we
// seek in the allotted iterations, just return the closest we were able to
// get.

let [h, c, t] = coords;
let xyz = [];
let j = 0;

// Shortcut out for black
if (t === 0) {
return [0.0, 0.0, 0.0];
}

// Calculate the Y we need to target
let y = fromLstar(t);

// A better initial guess yields better results. Polynomials come from
// curve fitting the T vs J response.
if (t > 0) {
j = 0.00379058511492914 * t ** 2 + 0.608983189401032 * t + 0.9155088574762233;
}
else {
j = 9.514440756550361e-06 * t ** 2 + 0.08693057439788597 * t - -21.928975842194614;
}

// Threshold of how close is close enough, and max number of attempts.
// More precision and more attempts means more time spent iterating. Higher
// required precision gives more accuracy but also increases the chance of
// not hitting the goal. 2e-12 allows us to convert round trip with
// reasonable accuracy of six decimal places or more.
const threshold = 2e-12;
const max_attempts = 15;

let attempt = 0;
let last = Infinity;
let best = j;

// Try to find a J such that the returned y matches the returned y of the L*
while (attempt <= max_attempts) {
xyz = fromCam16({J: j, C: c, h: h}, env);

// If we are within range, return XYZ
// If we are closer than last time, save the values
const delta = Math.abs(xyz[1] - y)
if (delta < last) {
if (delta <= threshold) {
return xyz;
}
best = j;
last = delta;
}

// f(j_root) = (j ** (1 / 2)) * 0.1
// f(j) = ((f(j_root) * 100) ** 2) / j - 1 = 0
// f(j_root) = Y = y / 100
// f(j) = (y ** 2) / j - 1
// f'(j) = (2 * y) / j
j = j - (xyz[1] - y) * j / (2 * xyz[1]);

attempt += 1;
}

// We could not acquire the precision we desired,
// return our closest attempt.
return fromCam16({J: j, C: c, h: h}, env);
// Use Newton's method to try and converge as quick as possible or
// converge as close as we can. While the requested precision is achieved
// most of the time, it may not always be achievable. Especially past the
// visible spectrum, the algorithm will likely struggle to get the same
// precision. If, for whatever reason, we cannot achieve the accuracy we
// seek in the allotted iterations, just return the closest we were able to
// get.

let [h, c, t] = coords;
let xyz = [];
let j = 0;

// Shortcut out for black
if (t === 0) {
return [0.0, 0.0, 0.0];
}

// Calculate the Y we need to target
let y = fromLstar(t);

// A better initial guess yields better results. Polynomials come from
// curve fitting the T vs J response.
if (t > 0) {
j = 0.00379058511492914 * t ** 2 + 0.608983189401032 * t + 0.9155088574762233;
}
else {
j = 9.514440756550361e-06 * t ** 2 + 0.08693057439788597 * t - -21.928975842194614;
}

// Threshold of how close is close enough, and max number of attempts.
// More precision and more attempts means more time spent iterating. Higher
// required precision gives more accuracy but also increases the chance of
// not hitting the goal. 2e-12 allows us to convert round trip with
// reasonable accuracy of six decimal places or more.
const threshold = 2e-12;
const max_attempts = 15;

let attempt = 0;
let last = Infinity;
let best = j;

// Try to find a J such that the returned y matches the returned y of the L*
while (attempt <= max_attempts) {
xyz = fromCam16({J: j, C: c, h: h}, env);

// If we are within range, return XYZ
// If we are closer than last time, save the values
const delta = Math.abs(xyz[1] - y);
if (delta < last) {
if (delta <= threshold) {
return xyz;
}
best = j;
last = delta;
}

// f(j_root) = (j ** (1 / 2)) * 0.1
// f(j) = ((f(j_root) * 100) ** 2) / j - 1 = 0
// f(j_root) = Y = y / 100
// f(j) = (y ** 2) / j - 1
// f'(j) = (2 * y) / j
j = j - (xyz[1] - y) * j / (2 * xyz[1]);

attempt += 1;
}

// We could not acquire the precision we desired,
// return our closest attempt.
return fromCam16({J: j, C: c, h: h}, env);
}

function toHct (xyz, env) {
// Calculate HCT by taking the L* of CIE LCh D65 and CAM16 chroma and hue.

const t = toLstar(xyz[1]);
if (t === 0.0) {
return [0.0, 0.0, 0.0];
}
const cam16 = toCam16(xyz, viewingConditions);
return [constrain(cam16.h), cam16.C, t];
// Calculate HCT by taking the L* of CIE LCh D65 and CAM16 chroma and hue.

const t = toLstar(xyz[1]);
if (t === 0.0) {
return [0.0, 0.0, 0.0];
}
const cam16 = toCam16(xyz, viewingConditions);
return [constrain(cam16.h), cam16.C, t];
}

// Pre-calculate everything we can with the viewing conditions
export const viewingConditions = environment(
white, 200 / Math.PI * fromLstar(50.0),
fromLstar(50.0) * 100,
'average',
false
white, 200 / Math.PI * fromLstar(50.0),
fromLstar(50.0) * 100,
"average",
false
);

// https://material.io/blog/science-of-color-design
Expand All @@ -122,33 +122,33 @@ export const viewingConditions = environment(
// This implementation comes from https://github.com/facelessuser/coloraide
// which is licensed under MIT.
export default new ColorSpace({
id: "hct",
name: "HCT",
coords: {
h: {
refRange: [0, 360],
type: "angle",
name: "Hue",
},
c: {
refRange: [0, 145],
name: "Colorfulness",
},
t: {
refRange: [0, 100],
name: "Tone",
}
},

base: xyz_d65,

fromBase (xyz) {
return toHct(xyz, viewingConditions);
},
toBase (hct) {
return fromHct(hct, viewingConditions);
},
formats: {
color: {}
},
id: "hct",
name: "HCT",
coords: {
h: {
refRange: [0, 360],
type: "angle",
name: "Hue",
},
c: {
refRange: [0, 145],
name: "Colorfulness",
},
t: {
refRange: [0, 100],
name: "Tone",
}
},

base: xyz_d65,

fromBase (xyz) {
return toHct(xyz, viewingConditions);
},
toBase (hct) {
return fromHct(hct, viewingConditions);
},
formats: {
color: {}
},
});

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