initial

www/tests/demo.mjs

@@ -0,0 +1,50 @@
+import assert from 'assert';
+import { Objective } from '../src/Objective.js';
+import { PSO } from '../src/PSO.js';
+import { monod, pirt } from '../src/conhecidos.js';
+
+function monodPirt(_, y, params) {
+  const K_S = params[0];
+  const mu_max = params[1];
+  const m_S = params[2];
+  const Y_XS = params[3];
+  const X = y[0];
+  const S = y[1];
+  const dmu = monod(S, mu_max, K_S);
+  const dX = X * dmu;
+  const qS = pirt(dmu, Y_XS, m_S);
+  const dS = -qS * X;
+  return [dX, dS];
+}
+
+const demoData = [
+  ['tempo', 'substrato', 'celulas'],
+  [0, 3.0, 0.05],
+  [1, 2.9835, 0.0595],
+  [2, 2.964, 0.0708],
+  [3, 2.9406, 0.0843],
+  [4, 2.9129, 0.1003],
+  [5, 2.8799, 0.1194],
+  [6, 2.8407, 0.1421],
+  [7, 2.794, 0.1691],
+  [8, 2.7385, 0.2011],
+  [9, 2.6725, 0.2393],
+  [10, 2.5942, 0.2846],
+  [11, 2.501, 0.3384],
+  [12, 2.3905, 0.4023],
+  [13, 2.2594, 0.478],
+  [14, 2.104, 0.5678],
+  [15, 1.9202, 0.674],
+];
+
+const obj = new Objective(demoData, monodPirt, 100, 2);
+const optim = new PSO(obj, 30, [
+  [0.005, 2],
+  [0.05, 0.9],
+  [0.0015, 0.05],
+  [0.3, 0.7],
+]);
+optim.run(1.49618, 1.49618, 0.7298, 30);
+
+assert(Number.isFinite(optim.err_best_g));
+console.log('Final error', optim.err_best_g);

www/tests/synthetic-search.mjs

@@ -0,0 +1,107 @@
+import assert from 'assert';
+import { Objective } from '../src/Objective.js';
+import { PSO } from '../src/PSO.js';
+import { monod, pirt } from '../src/conhecidos.js';
+import { RK4, RK4getvalue } from '../src/runge-kutta.js';
+
+function monodPirt(_, y, params) {
+  const K_S = params[0];
+  const mu_max = params[1];
+  const m_S = params[2];
+  const Y_XS = params[3];
+  const X = y[0];
+  const S = y[1];
+  const dmu = monod(S, mu_max, K_S);
+  const dX = X * dmu;
+  const qS = pirt(dmu, Y_XS, m_S);
+  const dS = -qS * X;
+  return [dX, dS];
+}
+
+function generateDataset(params, options) {
+  const {
+    initialCells,
+    initialSubstrate,
+    timeFinal,
+    sampleCount,
+    resolution,
+  } = options;
+
+  const y0 = [initialCells, initialSubstrate];
+  const timeArray = Array.from({ length: resolution + 1 }, (_, i) => (i * timeFinal) / resolution);
+  const solution = RK4(monodPirt, timeArray, y0, params);
+
+  const rows = [['tempo', 'substrato', 'celulas']];
+  for (let i = 0; i <= sampleCount; i++) {
+    const timePoint = (i * timeFinal) / sampleCount;
+    const [cells, substrate] = RK4getvalue(solution, timeArray, timePoint, monodPirt, params);
+    rows.push([timePoint, substrate, cells]);
+  }
+
+  return rows;
+}
+
+function createDeterministicRandom(seed) {
+  let state = seed >>> 0;
+  return function random() {
+    state = (state * 1664525 + 1013904223) >>> 0;
+    return state / 0x100000000;
+  };
+}
+
+const trueParams = [160, 0.45, 1.5, 0.5];
+const dataset = generateDataset(trueParams, {
+  initialCells: 1.2,
+  initialSubstrate: 120,
+  timeFinal: 12,
+  sampleCount: 12,
+  resolution: 240,
+});
+
+const bounds = [
+  [140, 200],
+  [0.3, 0.6],
+  [1.0, 2.5],
+  [0.3, 0.7],
+];
+
+const objective = new Objective(dataset, monodPirt, 240, 2);
+const originalRandom = Math.random;
+Math.random = createDeterministicRandom(12345);
+
+let optim;
+try {
+  optim = new PSO(objective, 50, bounds);
+  optim.run(1.49618, 1.49618, 0.7298, 150);
+} finally {
+  Math.random = originalRandom;
+}
+
+const defaultGuess = bounds.map(([min, max]) => (min + max) / 2);
+const defaultError = objective.objective(defaultGuess);
+
+assert(
+  optim.err_best_g < defaultError,
+  'Swarm should reduce the error compared to the midpoint default parameters',
+);
+
+const bestError = optim.err_best_g;
+assert(
+  bestError < 1e-3,
+  `Best error ${bestError} should approach the synthetic optimum with the default hyperparameters`,
+);
+
+const boundaryMargin = optim.pos_best_g.map((value, index) => {
+  const [min, max] = bounds[index];
+  const distanceToEdge = Math.min(value - min, max - value);
+  return distanceToEdge;
+});
+
+boundaryMargin.forEach((margin, index) => {
+  assert(
+    margin > 1e-3,
+    `Parameter ${index} is clamped to the boundary, default configuration should explore the interior`,
+  );
+});
+
+console.log('Synthetic dataset best parameters', optim.pos_best_g);