feat: implement free-field CPU beamforming
This commit is contained in:
Codex
@@ -0,0 +1,34 @@
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import { computeDasMap } from "/packages/acoustics-core/das.js";
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import { distance3 } from "/packages/acoustics-core/math.js";
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import { synthesizeMicrophoneSignals } from "/packages/acoustics-core/propagation.js";
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async function loadJson(path) {
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const response = await fetch(path);
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assert(response.ok, `${path} load failed`);
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return response.json();
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}
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test("192채널 · 50×50 CPU baseline이 ground truth를 찾는다", async () => {
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const [arrayDefinition, scene, experiment] = await Promise.all([
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loadJson("/assets/array-geometries/rectangular-16x12.array.json"),
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loadJson("/assets/sample-scenes/single-tone.scene.json"),
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loadJson("/assets/sample-scenes/single-tone.experiment.json"),
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]);
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const startedAt = performance.now();
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const synthesis = synthesizeMicrophoneSignals({ scene, arrayDefinition });
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const result = await computeDasMap({
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channels: synthesis.channels,
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sampleRate: synthesis.sampleRate,
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arrayDefinition,
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scene,
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experiment,
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});
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const elapsedMs = performance.now() - startedAt;
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const localizationError = distance3(result.bands[0].peak.position, scene.sources[0].position);
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assertEqual(result.microphoneCount, 192, "microphone count");
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assertEqual(result.pointCount, 2500, "scan point count");
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assert(localizationError < 0.03, `localization error=${localizationError} m`);
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assert(Number.isFinite(result.bands[0].peak.rawPower) && result.bands[0].peak.rawPower > 0, "finite peak power");
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document.documentElement.dataset.cpuBaselineMs = elapsedMs.toFixed(1);
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});
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@@ -10,6 +10,8 @@ globalThis.assertEqual = (actual, expected, message = "values differ") => {
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try {
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await import("/tests/unit/contracts.test.js");
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await import("/tests/unit/acoustics.test.js");
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await import("/tests/integration/cpu-baseline.test.js");
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} catch (error) {
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registeredTests.push({
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name: "테스트 모듈을 불러온다",
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@@ -0,0 +1,304 @@
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import { computeBinMap, computeDasMap, createDistanceMatrix } from "/packages/acoustics-core/das.js";
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import { fftInPlace, fftReal } from "/packages/acoustics-core/fft.js";
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import {
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addFrequencyDomainDelay,
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createDelayWorkspace,
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prepareDelaySpectrum,
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} from "/packages/acoustics-core/fractional-delay.js";
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import { dbToLinear, distance3 } from "/packages/acoustics-core/math.js";
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import { whiteNoiseAt } from "/packages/acoustics-core/noise.js";
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import { sphericalAttenuation, synthesizeMicrophoneSignals } from "/packages/acoustics-core/propagation.js";
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import { getFrameCount } from "/packages/acoustics-core/stft.js";
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function assertNear(actual, expected, tolerance, label) {
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assert(Math.abs(actual - expected) <= tolerance, `${label}: expected ${expected} ± ${tolerance}, received ${actual}`);
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}
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function rms(values, start = 0, end = values.length) {
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let sum = 0;
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for (let index = start; index < end; index += 1) sum += values[index] ** 2;
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return Math.sqrt(sum / (end - start));
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}
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function createArray(columns, rows, width, height) {
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const microphones = [];
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for (let row = 0; row < rows; row += 1) {
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for (let column = 0; column < columns; column += 1) {
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microphones.push({
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id: `mic-${row}-${column}`,
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position: [
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-width / 2 + (column * width) / (columns - 1),
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-height / 2 + (row * height) / (rows - 1),
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0,
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],
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});
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}
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}
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return { id: "test-array", aperture: { width, height }, microphones };
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}
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test("거리, dB와 구면 감쇠 기본식을 계산한다", () => {
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assertNear(distance3([0, 0, 0], [1, 2, 2]), 3, 1e-12, "distance");
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assertNear(dbToLinear(-6.020599913), 0.5, 1e-9, "dB amplitude");
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assertNear(sphericalAttenuation(2), 0.5, 1e-12, "1/r attenuation");
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});
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test("index 기반 noise가 seed에 대해 결정적이다", () => {
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const first = Array.from({ length: 16 }, (_, index) => whiteNoiseAt(42, index));
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const second = Array.from({ length: 16 }, (_, index) => whiteNoiseAt(42, index));
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assert(first.every((value, index) => value === second[index]));
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assert(first.some((value, index) => value !== whiteNoiseAt(43, index)));
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});
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test("radix-2 FFT가 정확한 tone bin을 찾는다", () => {
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const size = 128;
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const bin = 16;
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const samples = Float64Array.from({ length: size }, (_, index) => Math.sin((2 * Math.PI * bin * index) / size));
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const spectrum = fftReal(samples);
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const magnitude = Math.hypot(spectrum.real[bin], spectrum.imaginary[bin]);
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assertNear(magnitude, size / 2, 1e-8, "tone magnitude");
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assertNear(spectrum.real[bin], 0, 1e-8, "forward real sign");
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assertNear(spectrum.imaginary[bin], -size / 2, 1e-8, "forward imaginary sign");
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assert(Math.hypot(spectrum.real[bin - 1], spectrum.imaginary[bin - 1]) < 1e-8, "adjacent leakage");
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fftInPlace(spectrum.real, spectrum.imaginary, true);
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samples.forEach((value, index) => assertNear(spectrum.real[index], value, 1e-9, `inverse sample ${index}`));
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});
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test("FFT phase shift가 integer와 fractional delay를 적용한다", () => {
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const impulse = new Float32Array(16);
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impulse[2] = 1;
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const impulseSpectrum = prepareDelaySpectrum(impulse, 3);
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const impulseOutput = new Float32Array(16);
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addFrequencyDomainDelay({
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output: impulseOutput,
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spectrum: impulseSpectrum,
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delaySamples: 3,
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workspace: createDelayWorkspace(impulseSpectrum.fftSize),
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});
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assertNear(impulseOutput[5], 1, 1e-6, "integer delayed impulse");
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const size = 512;
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const frequencyCyclesPerSample = 1 / 8;
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const tone = Float32Array.from({ length: size }, (_, index) => Math.sin(2 * Math.PI * frequencyCyclesPerSample * index));
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const toneSpectrum = prepareDelaySpectrum(tone, 2.5);
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const delayedTone = new Float32Array(size);
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addFrequencyDomainDelay({
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output: delayedTone,
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spectrum: toneSpectrum,
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delaySamples: 2.5,
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workspace: createDelayWorkspace(toneSpectrum.fftSize),
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});
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let squaredError = 0;
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let count = 0;
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for (let index = 48; index < size - 48; index += 1) {
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const expected = Math.sin(2 * Math.PI * frequencyCyclesPerSample * (index - 2.5));
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squaredError += (delayedTone[index] - expected) ** 2;
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count += 1;
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}
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assert(Math.sqrt(squaredError / count) < 1e-3, "fractional delay RMS error");
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});
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test("STFT frame count가 마지막 partial tail을 포함한다", () => {
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assertEqual(getFrameCount(512, 512, 256), 1);
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assertEqual(getFrameCount(513, 512, 256), 2);
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assertEqual(getFrameCount(12000, 512, 256), 46);
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});
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test("구면 전파가 거리별 지연과 1/r 진폭비를 적용한다", () => {
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const scene = {
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sampleRate: 8000,
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duration: 0.02,
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speedOfSound: 400,
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seed: 1,
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mix: { normalization: "none", targetPeak: 0.95 },
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sources: [{
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id: "tone", name: "tone", position: [0, 0, 0.1], gainDb: -40, startTime: 0, duration: 0.02,
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signal: { type: "tone", frequency: 500, phaseDeg: 0 },
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}],
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ambient: [],
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};
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const arrayDefinition = {
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microphones: [
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{ id: "near", position: [0, 0, 0.05] },
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{ id: "far", position: [0, 0, 0] },
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],
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};
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const result = synthesizeMicrophoneSignals({ scene, arrayDefinition });
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const emittedSampleOne = Math.sin((2 * Math.PI * 500) / 8000) * dbToLinear(-40);
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assertNear(result.channels[0][1], 0, 1e-7, "one-sample propagation delay");
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assertNear(result.channels[0][2], emittedSampleOne * 20, 1e-5, "near analytic delayed sample");
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assertNear(result.channels[1][3], emittedSampleOne * 10, 1e-5, "far analytic delayed sample");
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assertNear(rms(result.channels[0], 16, 150) / rms(result.channels[1], 16, 150), 2, 0.02, "distance amplitude ratio");
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});
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test("peak mix 정규화와 channel buffer 한도를 적용한다", () => {
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const scene = {
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sampleRate: 8000,
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duration: 0.02,
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speedOfSound: 343,
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seed: 1,
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mix: { normalization: "peak", targetPeak: 0.5 },
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sources: [{
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id: "tone", name: "tone", position: [0, 0, 1], gainDb: 6, startTime: 0, duration: 0.02,
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signal: { type: "tone", frequency: 500, phaseDeg: 0 },
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}],
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ambient: [],
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};
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const arrayDefinition = { microphones: [{ id: "mic", position: [0, 0, 0] }] };
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const result = synthesizeMicrophoneSignals({ scene, arrayDefinition });
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assertNear(result.peak, 0.5, 1e-6, "normalized peak");
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assert(result.appliedScale < 1);
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let error;
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try {
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synthesizeMicrophoneSignals({ scene, arrayDefinition, maximumBufferBytes: 1 });
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} catch (caught) {
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error = caught;
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}
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assert(error instanceof Error && error.message.includes("한도"), "buffer limit error");
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});
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test("ambient에도 microphone gain과 phase calibration 편차를 적용한다", () => {
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const scene = {
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sampleRate: 8000,
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duration: 0.02,
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speedOfSound: 343,
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seed: 1,
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mix: { normalization: "none", targetPeak: 0.95 },
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sources: [],
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ambient: [{ id: "ambient", gainDb: -20, signal: { type: "tone", frequency: 500, phaseDeg: 0 } }],
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};
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const arrayDefinition = {
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microphones: [{ id: "calibrated", position: [0, 0, 0], sensitivityDb: 6, phaseOffsetDeg: 90 }],
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};
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const result = synthesizeMicrophoneSignals({ scene, arrayDefinition });
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const expected = dbToLinear(-20) * dbToLinear(6);
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assertNear(result.channels[0][80], expected, 4e-3, "ambient calibrated sample");
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});
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test("CPU DAS peak가 calibration 후 단일 tone의 실제 grid 위치를 찾는다", async () => {
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const arrayDefinition = createArray(4, 4, 0.3, 0.3);
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arrayDefinition.microphones.forEach((microphone, index) => {
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microphone.sensitivityDb = (index % 3) * 2 - 2;
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microphone.phaseOffsetDeg = (index % 5) * 8 - 16;
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});
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const scene = {
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id: "das-scene",
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sampleRate: 8000,
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duration: 0.128,
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speedOfSound: 343,
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seed: 7,
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mix: { normalization: "none", targetPeak: 0.95 },
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sources: [{
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id: "source", name: "source", position: [0.1, 0.1, 1.5], gainDb: -12, startTime: 0, duration: 0.128,
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signal: { type: "tone", frequency: 1000, phaseDeg: 0 },
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}],
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ambient: [],
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};
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const experiment = {
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stft: { fftSize: 256, hopSize: 128, window: "hann" },
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scan: { z: 1.5, xMin: -0.4, xMax: 0.4, yMin: -0.4, yMax: 0.4, columns: 17, rows: 17 },
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frequencyBands: [{ id: "1k", minHz: 990, maxHz: 1010, color: "#65f2bf" }],
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beamforming: { normalization: "peak" },
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};
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const synthesis = synthesizeMicrophoneSignals({ scene, arrayDefinition });
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const progressEvents = [];
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const result = await computeDasMap({
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channels: synthesis.channels,
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sampleRate: synthesis.sampleRate,
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arrayDefinition,
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scene,
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experiment,
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onProgress: (progress) => progressEvents.push(progress),
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});
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const peakPosition = result.bands[0].peak.position;
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assert(distance3(peakPosition, scene.sources[0].position) <= 0.071, `peak=${peakPosition.join(",")}`);
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assert(result.bands[0].rawMap !== result.bands[0].displayMap, "raw/display buffers are separate");
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assertNear(Math.max(...result.bands[0].rawMap), result.bands[0].peak.rawPower, 1e-4, "raw map peak");
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assertNear(Math.max(...result.bands[0].displayMap), 1, 1e-6, "normalized display peak");
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assert(progressEvents.some(({ stage }) => stage === "beamforming"), "beamforming progress");
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});
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test("독립 복소 spectrum fixture에서 DAS steering 부호가 맞다", async () => {
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const arrayDefinition = {
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microphones: [
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{ id: "left", position: [-0.15, 0, 0] },
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{ id: "middle", position: [-0.02, 0, 0] },
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{ id: "right", position: [0.12, 0, 0] },
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],
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};
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const scan = { z: 1, xMin: -0.2, xMax: 0.2, yMin: 0, yMax: 0, columns: 2, rows: 1 };
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const target = [0.2, 0, 1];
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const sampleRate = 8000;
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const fftSize = 256;
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const bin = 32;
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const frequency = (bin * sampleRate) / fftSize;
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const speedOfSound = 343;
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const spectrum = { real: new Float32Array(3), imaginary: new Float32Array(3) };
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arrayDefinition.microphones.forEach((microphone, index) => {
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const phase = (2 * Math.PI * frequency * distance3(target, microphone.position)) / speedOfSound;
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spectrum.real[index] = Math.cos(-phase);
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spectrum.imaginary[index] = Math.sin(-phase);
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});
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const map = await computeBinMap({
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bin,
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spectrum,
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frameCount: 1,
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arrayDefinition,
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pointCount: 2,
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distances: createDistanceMatrix(arrayDefinition, scan),
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sampleRate,
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fftSize,
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speedOfSound,
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pointBatchSize: 64,
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});
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assertNear(map[1], 1, 1e-6, "target coherent power");
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assert(map[1] > map[0] * 1.1, `wrong-sign alternative power=${map[0]}`);
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});
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test("CPU DAS가 event-loop 취소와 working-set 한도를 지킨다", async () => {
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const arrayDefinition = createArray(2, 2, 0.2, 0.2);
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const scene = { speedOfSound: 343 };
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const experiment = {
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stft: { fftSize: 128, hopSize: 64, window: "hann" },
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scan: { z: 1, xMin: -0.2, xMax: 0.2, yMin: -0.2, yMax: 0.2, columns: 17, rows: 17 },
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frequencyBands: [{ id: "tone", minHz: 490, maxHz: 510, color: "#65f2bf" }],
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beamforming: { normalization: "peak" },
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};
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const channels = arrayDefinition.microphones.map(() => new Float32Array(512));
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let memoryError;
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try {
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await computeDasMap({ channels, sampleRate: 8000, arrayDefinition, scene, experiment, maximumWorkingBytes: 1 });
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} catch (error) {
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memoryError = error;
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}
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assert(memoryError instanceof Error && memoryError.message.includes("working set"), "working-set guard");
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const controller = new AbortController();
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let stftStarted = false;
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let abortScheduled = false;
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const pending = computeDasMap({
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channels,
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sampleRate: 8000,
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arrayDefinition,
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scene,
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experiment,
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signal: controller.signal,
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pointBatchSize: 1,
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stftTransformBatchSize: 1,
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onProgress: (progress) => {
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if (progress.stage === "stft" && progress.completedTransforms > 0 && !abortScheduled) {
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stftStarted = true;
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abortScheduled = true;
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setTimeout(() => controller.abort(), 0);
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}
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},
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});
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let abortError;
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try {
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await pending;
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} catch (error) {
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abortError = error;
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}
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assert(stftStarted, "STFT started before abort");
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assert(abortError?.name === "AbortError", "async abort");
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});
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