88 lines
3.1 KiB
TypeScript
88 lines
3.1 KiB
TypeScript
import {
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type Levels,
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DEFAULT_STANDARDS_DATASET,
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} from "@blade-and-brawn/calculator";
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import { Activity, clamp, Gender, range } from "@blade-and-brawn/domain";
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import { levenbergMarquardt as LM } from "ml-levenberg-marquardt";
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for (const activity of Object.values(Activity)) {
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const DATASET_MAX_LEVEL = 5;
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const NEW_LEVEL_COUNT = 2;
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const RATIO_CLAMP = 1.4;
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function expDecayModel([A, B, C]: number[]) {
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return (i: number) => A! * Math.exp(-B! * i) + C!;
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}
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for (const gender of Object.values(Gender)) {
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const standardsByGender = DEFAULT_STANDARDS_DATASET[
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activity
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].standards.filter((s) => s["metrics"].gender === gender);
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const ages = [...new Set(standardsByGender.map((s) => s.metrics.age))];
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for (const age of ages) {
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const standards = standardsByGender.filter(
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(s) => s.metrics.age === age,
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);
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const data = {
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x: [] as number[],
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y: [] as number[],
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};
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const isIncreasing =
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standards[0]!.levels["2"]! > standards[0]!.levels["1"]!;
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for (const i of range(DATASET_MAX_LEVEL).slice(0, -1)) {
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const level = i + 1;
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const progressionRatios: number[] = [];
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for (const standard of standards) {
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const curr = standard.levels[level]!;
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const next = standard.levels[level]!;
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progressionRatios.push(
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isIncreasing ? next / curr : curr / next,
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);
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}
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const sum = progressionRatios.reduce((p, c) => p + c, 0);
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const progressionRatioAvg = sum / progressionRatios.length;
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data.x.push(i);
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data.y.push(progressionRatioAvg);
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}
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const fittedParams = LM(data, expDecayModel, {
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initialValues: [0.4, 0.5, 1.1],
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minValues: [0.0, 0.0, 1.02],
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maxValues: [1.0, 2.0, 1.25],
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maxIterations: 200,
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});
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const getDecayRatio = (i: number) =>
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clamp(
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expDecayModel(fittedParams.parameterValues)(i),
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1,
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RATIO_CLAMP,
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);
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// UPDATE THE DATA
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for (const standard of standards) {
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const newLevels: Levels = {};
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let prev = standard.levels["1"]!;
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for (const i of range(NEW_LEVEL_COUNT)) {
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const level = i + 1;
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const ratio = getDecayRatio(level - NEW_LEVEL_COUNT);
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prev = isIncreasing ? prev / ratio : prev * ratio;
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newLevels[level] = Math.round(prev);
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}
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const oldLevels = standard.levels as Levels;
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for (const i of range(DATASET_MAX_LEVEL)) {
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const level = i + 1;
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newLevels[level + NEW_LEVEL_COUNT] = oldLevels[level]!;
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}
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standard.levels = newLevels;
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}
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}
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}
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}
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