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https://github.com/rsms/inter.git
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99 lines
2.7 KiB
JavaScript
99 lines
2.7 KiB
JavaScript
//
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// Program that searches for optimal a,b,c values for dynamic metrics.
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//
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// Provide ideal tracking values for font sizes in idealTracking and start
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// this program. It will run forever and print to stdout when it finds
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// better a,b,c values that brings you closer to the ideal values.
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//
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// These are the initial a,b,c values. (Update if you find better values.)
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let a = -0.02, b = 0.0755, c = -0.1021 // 0.00092
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//
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// These are the ideal tracking values.
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let idealTracking = {
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// 6: 0.05,
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// 7: 0.04,
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// 8: 0.03,
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9: 0.01,
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// 10: 0.015,
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11: 0.005,
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12: 0.0025,
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13: 0,
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// 14: 0,
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// 15: -0.002,
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16: -0.005,
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// 17: -0.008,
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18: -0.01,
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// 20: -0.014,
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// 24: -0.016,
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// 30: -0.019,
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40: -0.022,
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}
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let idealTrackingList = Object.keys(idealTracking).map(fontSize =>
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[fontSize, idealTracking[fontSize]]
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)
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function sample(a, b, c) {
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let idealDist = 0.0
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for (let [fontSize, idealTracking] of idealTrackingList) {
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let tracking = a + b * Math.pow(Math.E, c * fontSize)
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let dist = Math.abs(tracking - idealTracking)
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idealDist += dist
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// console.log(`${fontSize} d=${tracking - idealTracking} d'=${dist}`)
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}
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// console.log(`idealDist=${idealDist}`)
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return idealDist / idealTrackingList.length
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}
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const prec = 4 // precision
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let bestConstants = { a, b, c }
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let isneg = {
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a: a < 0,
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b: b < 0,
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c: c < 0,
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}
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let bestDistance = sample(a, b, c)
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console.log(
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'------------------------------------------------------------------\n' +
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`| Started at ${(new Date()).toLocaleString()} with initial values:\n` +
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`| a = ${bestConstants.a}, b = ${bestConstants.b},` +
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` c = ${bestConstants.c} // D ${bestDistance.toFixed(5)}\n` +
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`| Ctrl-C to end.\n` +
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'------------------------------------------------------------------'
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)
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function logNewBest() {
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console.log(
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`new best: a = ${a.toFixed(prec)}, b = ${b.toFixed(prec)}, c = ${c.toFixed(prec)} // D ${bestDistance.toFixed(5)}`
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)
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}
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while (true) {
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// a = parseFloat((bestConstants.a * ((Math.random() * 2.0) - 1.0)).toFixed(prec))
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// b = parseFloat((bestConstants.b * ((Math.random() * 2.0) - 1.0)).toFixed(prec))
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// c = parseFloat((bestConstants.c * ((Math.random() * 2.0) - 1.0)).toFixed(prec))
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let a2 = bestConstants.a * ((Math.random() * 2.0) - 1.0)
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let b2 = bestConstants.b * ((Math.random() * 2.0) - 1.0)
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let c2 = bestConstants.c * ((Math.random() * 2.0) - 1.0)
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if (isneg.a) { if (a2 > 0) { a2 = a } } else if (a2 < 0) { a2 = a }
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if (isneg.b) { if (b2 > 0) { b2 = b } } else if (b2 < 0) { b2 = b }
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if (isneg.c) { if (c2 > 0) { c2 = c } } else if (c2 < 0) { c2 = c }
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a = a2
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b = b2
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c = c2
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let dist = sample(a, b, c)
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if (dist < bestDistance) {
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bestDistance = dist
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logNewBest()
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}
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}
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