fix: stabilize localization comparison semantics

This commit is contained in:
2026-08-28 20:57:13 +09:00
parent 9b9244be85
commit e8dac792d9
10 changed files with 340 additions and 31 deletions
+10 -1
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@@ -601,15 +601,24 @@ export function estimateDasWorkload(options) {
};
}
export function finalizeDasBands(rawMaps, workload, experiment, rawScale = "power") {
export function finalizeDasBands(
rawMaps,
workload,
experiment,
rawScale = "power",
options = {},
) {
if (rawScale !== "power" && rawScale !== "score") {
throw new RangeError('rawScale must be "power" or "score".');
}
const averageBandBins = options.averageBandBins !== false;
return experiment.frequencyBands.map((band, bandIndex) => {
const rawMap = rawMaps[bandIndex];
if (averageBandBins) {
for (let pointIndex = 0; pointIndex < workload.pointCount; pointIndex += 1) {
rawMap[pointIndex] /= workload.bandBins[bandIndex].length;
}
}
const rawPeak = findPeak(rawMap);
const displayMap = Float32Array.from(rawMap);
let displayScale = rawScale;
+123 -14
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@@ -14,7 +14,10 @@ import {
export const GCC_PHAT_ANALYSIS_PLAN_KIND = "micarrsim.gcc-phat-analysis-plan/1";
export const DEFAULT_GCC_PHAT_FLOOR_RATIO = 1e-6;
export const DEFAULT_GCC_PHAT_POINT_BATCH_SIZE = 4096;
export const DEFAULT_GCC_PHAT_CROSS_SPECTRUM_BATCH_SIZE = 16384;
export const DEFAULT_MAXIMUM_GCC_PHAT_PLAN_BYTES = 512 * 1024 * 1024;
export const DEFAULT_MAXIMUM_GCC_PHAT_WORKING_BYTES = 512 * 1024 * 1024;
function createAbortError(signal) {
if (signal?.reason instanceof Error && signal.reason.name === "AbortError") {
@@ -241,6 +244,60 @@ function requirePhatFloorRatio(value) {
return ratio;
}
function requireMaximumWorkingBytes(value) {
const maximumWorkingBytes = value ?? DEFAULT_MAXIMUM_GCC_PHAT_WORKING_BYTES;
if (!Number.isSafeInteger(maximumWorkingBytes) || maximumWorkingBytes <= 0) {
throw new RangeError("maximumWorkingBytes must be a positive safe integer.");
}
return maximumWorkingBytes;
}
/**
* Reject an oversized no-plan analysis before createDistanceMatrix allocates
* its P x M table. This mirrors estimateWithGeometry's retained/spectrum/
* calibration/output accounting without requiring geometry to exist first.
*/
function preflightUnplannedWorkingSet(options, configuration) {
const microphoneCount = configuration.arrayDefinition.microphones.length;
const sampleCount = validateChannels(options.channels, microphoneCount);
const { bandBins, selectedBins } = createBandGeometry(configuration);
const frameCount = getFrameCount(
sampleCount,
configuration.fftSize,
configuration.hopSize,
);
const bandCount = bandBins.length;
const distanceBytes =
configuration.pointCount * microphoneCount * Float32Array.BYTES_PER_ELEMENT;
const stftWorkspaceBytes =
configuration.fftSize * Float64Array.BYTES_PER_ELEMENT * 3;
const correlationWorkspaceBytes =
configuration.fftSize * Float64Array.BYTES_PER_ELEMENT * 2;
const spectrumBytes =
selectedBins.length * frameCount * microphoneCount *
Float32Array.BYTES_PER_ELEMENT * 2;
const calibrationPhaseBytes =
selectedBins.length * microphoneCount * Float64Array.BYTES_PER_ELEMENT;
const outputBytes =
bandCount * configuration.pointCount * Float32Array.BYTES_PER_ELEMENT * 2;
const estimatedWorkingBytes =
distanceBytes + stftWorkspaceBytes + correlationWorkspaceBytes +
spectrumBytes + calibrationPhaseBytes + outputBytes;
if (!Number.isSafeInteger(estimatedWorkingBytes)) {
throw new RangeError("GCC-PHAT estimated working set exceeds the safe integer range.");
}
const maximumWorkingBytes = requireMaximumWorkingBytes(options.maximumWorkingBytes);
if (estimatedWorkingBytes > maximumWorkingBytes) {
throw new RangeError(
"GCC-PHAT estimated working set " +
(estimatedWorkingBytes / 1024 ** 2).toFixed(1) +
" MiB exceeds maximumWorkingBytes " +
(maximumWorkingBytes / 1024 ** 2).toFixed(1) + " MiB before geometry allocation.",
);
}
return { estimatedWorkingBytes, maximumWorkingBytes };
}
function estimateWithGeometry(options, configuration, geometry) {
const sampleCount = validateChannels(options.channels, geometry.microphoneCount);
const frameCount = getFrameCount(
@@ -332,6 +389,7 @@ export function estimateGccPhatWorkload(options) {
assertCompatibleAnalysisPlan(options.analysisPlan, options);
geometry = options.analysisPlan;
} else {
preflightUnplannedWorkingSet(options, configuration);
geometry = createGeometry(configuration);
}
return estimateWithGeometry(options, configuration, geometry);
@@ -467,7 +525,7 @@ function circularLinearSample(values, lagSamples) {
return values[firstIndex] * (1 - fraction) + values[secondIndex] * fraction;
}
function fillBandPairCorrelation({
async function fillBandPairCorrelation({
correlationReal,
correlationImaginary,
bins,
@@ -476,11 +534,14 @@ function fillBandPairCorrelation({
referenceIndex,
phasesByBin,
phatFloorRatio,
signal,
crossSpectrumBatchSize,
}) {
correlationReal.fill(0);
correlationImaginary.fill(0);
const microphoneCount = stft.microphoneCount;
let maximumMagnitude = 0;
let operationsUntilYield = crossSpectrumBatchSize;
for (const bin of bins) {
const spectrum = stft.spectra.get(bin);
@@ -498,6 +559,12 @@ function fillBandPairCorrelation({
maximumMagnitude,
Math.hypot(crossReal, crossImaginary),
);
operationsUntilYield -= 1;
if (operationsUntilYield === 0) {
await cooperativeYield();
throwIfAborted(signal);
operationsUntilYield = crossSpectrumBatchSize;
}
}
}
@@ -535,6 +602,12 @@ function fillBandPairCorrelation({
normalizedReal * correctionReal - normalizedImaginary * correctionImaginary;
accumulatedImaginary +=
normalizedReal * correctionImaginary + normalizedImaginary * correctionReal;
operationsUntilYield -= 1;
if (operationsUntilYield === 0) {
await cooperativeYield();
throwIfAborted(signal);
operationsUntilYield = crossSpectrumBatchSize;
}
}
const averagedReal = accumulatedReal / stft.frameCount;
@@ -552,13 +625,38 @@ function fillBandPairCorrelation({
fftInPlace(correlationReal, correlationImaginary, true);
}
function shiftAndSquareScores(rawMaps) {
for (const rawMap of rawMaps) {
let minimum = Infinity;
for (const value of rawMap) minimum = Math.min(minimum, value);
async function normalizePositiveScores(
rawMaps,
bandBins,
fftSize,
pairCount,
pointBatchSize,
signal,
) {
for (let bandIndex = 0; bandIndex < rawMaps.length; bandIndex += 1) {
const rawMap = rawMaps[bandIndex];
const coefficientCount = bandBins[bandIndex].reduce(
(count, bin) => count + (bin === 0 || bin === fftSize / 2 ? 1 : 2),
0,
);
const normalization = fftSize / (pairCount * coefficientCount);
for (let pointIndex = 0; pointIndex < rawMap.length; pointIndex += 1) {
const shifted = rawMap[pointIndex] - minimum;
rawMap[pointIndex] = shifted * shifted;
// PHAT coefficients have magnitude <= 1. After Hermitian completion and
// inverse-FFT scaling, coefficientCount / fftSize is therefore a strict
// per-pair bound. Pair averaging makes the positive score stable across
// microphone count, band width, and scan extent without implying a
// probability. Negative correlation is evidence against the hypothesis.
rawMap[pointIndex] = Math.min(
1,
Math.max(0, rawMap[pointIndex] * normalization),
);
if (
(pointIndex + 1) % pointBatchSize === 0 &&
pointIndex + 1 < rawMap.length
) {
await cooperativeYield();
throwIfAborted(signal);
}
}
}
}
@@ -568,16 +666,16 @@ async function computeGccPhatMapInternal(options, configuration, geometry, plan)
channels,
signal,
onProgress,
maximumWorkingBytes = 512 * 1024 * 1024,
maximumWorkingBytes = DEFAULT_MAXIMUM_GCC_PHAT_WORKING_BYTES,
maximumFftButterflies = 1_000_000_000,
pointBatchSize = 256,
pointBatchSize = DEFAULT_GCC_PHAT_POINT_BATCH_SIZE,
crossSpectrumBatchSize = DEFAULT_GCC_PHAT_CROSS_SPECTRUM_BATCH_SIZE,
stftTransformBatchSize = 128,
} = options;
requirePositiveInteger(pointBatchSize, "pointBatchSize");
requirePositiveInteger(crossSpectrumBatchSize, "crossSpectrumBatchSize");
requirePositiveInteger(stftTransformBatchSize, "stftTransformBatchSize");
if (!Number.isSafeInteger(maximumWorkingBytes) || maximumWorkingBytes <= 0) {
throw new RangeError("maximumWorkingBytes must be a positive safe integer.");
}
requireMaximumWorkingBytes(maximumWorkingBytes);
const phatFloorRatio = requirePhatFloorRatio(
options.phatFloorRatio ??
options.phatRelativeFloor ??
@@ -666,7 +764,7 @@ async function computeGccPhatMapInternal(options, configuration, geometry, plan)
const rawMap = rawMaps[bandIndex];
for (const microphoneIndex of geometry.pairMicrophoneIndexes) {
throwIfAborted(signal);
fillBandPairCorrelation({
await fillBandPairCorrelation({
correlationReal,
correlationImaginary,
bins,
@@ -675,6 +773,8 @@ async function computeGccPhatMapInternal(options, configuration, geometry, plan)
referenceIndex: geometry.reference.index,
phasesByBin,
phatFloorRatio,
signal,
crossSpectrumBatchSize,
});
if (plan) {
plan.statistics.inverseFftTransforms += 1;
@@ -715,12 +815,20 @@ async function computeGccPhatMapInternal(options, configuration, geometry, plan)
}
throwIfAborted(signal);
shiftAndSquareScores(rawMaps);
await normalizePositiveScores(
rawMaps,
geometry.bandBins,
configuration.fftSize,
geometry.pairCount,
pointBatchSize,
signal,
);
const bands = finalizeDasBands(
rawMaps,
workload,
configuration.experiment,
"score",
{ averageBandBins: false },
);
return {
backend: "cpu",
@@ -753,6 +861,7 @@ export async function computeGccPhatMap(options) {
const configuration = validateConfiguration(options);
const plan = options.analysisPlan;
if (!plan) {
preflightUnplannedWorkingSet(options, configuration);
const geometry = createGeometry(configuration);
return computeGccPhatMapInternal(options, configuration, geometry, undefined);
}
+9 -9
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@@ -25,9 +25,9 @@ function requestedAlgorithm(options) {
*/
export function estimateLocalizationWorkload(options) {
const algorithm = requestedAlgorithm(options);
return isDasAlgorithm(algorithm.id)
? estimateDasWorkload(options)
: estimateGccPhatWorkload(options);
if (isDasAlgorithm(algorithm.id)) return estimateDasWorkload(options);
if (algorithm.id === "gcc-phat") return estimateGccPhatWorkload(options);
throw new RangeError("No workload estimator is registered for " + algorithm.id + ".");
}
/**
@@ -35,9 +35,9 @@ export function estimateLocalizationWorkload(options) {
*/
export function createLocalizationAnalysisPlan(options) {
const algorithm = requestedAlgorithm(options);
return isDasAlgorithm(algorithm.id)
? createDasAnalysisPlan(options)
: createGccPhatAnalysisPlan(options);
if (isDasAlgorithm(algorithm.id)) return createDasAnalysisPlan(options);
if (algorithm.id === "gcc-phat") return createGccPhatAnalysisPlan(options);
throw new RangeError("No analysis-plan factory is registered for " + algorithm.id + ".");
}
/**
@@ -47,7 +47,7 @@ export function createLocalizationAnalysisPlan(options) {
*/
export async function computeLocalizationMap(options) {
const algorithm = requestedAlgorithm(options);
return isDasAlgorithm(algorithm.id)
? computeDasMap(options)
: computeGccPhatMap(options);
if (isDasAlgorithm(algorithm.id)) return computeDasMap(options);
if (algorithm.id === "gcc-phat") return computeGccPhatMap(options);
throw new RangeError("No CPU localization implementation is registered for " + algorithm.id + ".");
}
+10 -1
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@@ -3,6 +3,10 @@ import {
computeLocalizationMap,
createLocalizationAnalysisPlan,
} from "./localization.js";
import {
DEFAULT_GCC_PHAT_CROSS_SPECTRUM_BATCH_SIZE,
DEFAULT_GCC_PHAT_POINT_BATCH_SIZE,
} from "./gcc-phat.js";
import {
isDasAlgorithm,
requireLocalizationAlgorithmDefinition,
@@ -355,8 +359,13 @@ export function createLocalizationPlan(config) {
? { dasPlan: analysisPlan }
: { gccPhatPlan: analysisPlan }),
computeOptions: Object.freeze({
pointBatchSize: DEFAULT_REALTIME_POINT_BATCH_SIZE,
pointBatchSize: isDasAlgorithm(algorithm.id)
? DEFAULT_REALTIME_POINT_BATCH_SIZE
: DEFAULT_GCC_PHAT_POINT_BATCH_SIZE,
stftTransformBatchSize: DEFAULT_REALTIME_STFT_TRANSFORM_BATCH_SIZE,
...(!isDasAlgorithm(algorithm.id)
? { crossSpectrumBatchSize: DEFAULT_GCC_PHAT_CROSS_SPECTRUM_BATCH_SIZE }
: {}),
...(phatRelativeFloor !== undefined ? { phatRelativeFloor } : {}),
...(phatFloorRatio !== undefined ? { phatFloorRatio } : {}),
...(config.computeOptions ?? {}),
+34
View File
@@ -555,6 +555,19 @@ function validateResultRelationships(value, context = {}) {
}
const sourceIds = new Set(context.scene?.sources?.map((source) => source.id) ?? []);
const expectedBandIds = new Set(context.experiment?.frequencyBands?.map((band) => band.id) ?? []);
const resultAlgorithm = value.algorithm ?? context.experiment?.beamforming?.algorithm;
const expectedRawScale =
resultAlgorithm === "das"
? "power"
: resultAlgorithm === "das-phat" || resultAlgorithm === "gcc-phat"
? "score"
: undefined;
const expectedBeamSpreadMethod =
expectedRawScale === "power"
? "connected-half-power-power-weighted-covariance"
: expectedRawScale === "score"
? "connected-half-maximum-score-weighted-covariance"
: undefined;
const bandIds = [];
if (Array.isArray(value.bands)) {
value.bands.forEach((band, bandIndex) => {
@@ -576,12 +589,33 @@ function validateResultRelationships(value, context = {}) {
});
if (isRecord(band.rawMap) && !["power", "score"].includes(band.rawMap.scale)) {
addIssue(issues, `${path}.rawMap.scale`, "rawMap은 power 또는 score scale이어야 합니다.");
} else if (
isRecord(band.rawMap) &&
expectedRawScale &&
band.rawMap.scale !== expectedRawScale
) {
addIssue(
issues,
`${path}.rawMap.scale`,
`${resultAlgorithm} 결과의 rawMap scale은 ${expectedRawScale}여야 합니다.`,
);
}
if (Array.isArray(band.peaks)) {
band.peaks.forEach((peak, peakIndex) => {
if (peak?.sourceId && sourceIds.size > 0 && !sourceIds.has(peak.sourceId)) {
addIssue(issues, `${path}.peaks[${peakIndex}].sourceId`, "장면에 없는 source id입니다.");
}
if (
expectedBeamSpreadMethod &&
isRecord(peak?.beamSpread) &&
peak.beamSpread.method !== expectedBeamSpreadMethod
) {
addIssue(
issues,
`${path}.peaks[${peakIndex}].beamSpread.method`,
`${expectedRawScale} map과 맞는 beamSpread method여야 합니다.`,
);
}
});
}
});
+3
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@@ -90,6 +90,9 @@ export async function computeLocalizationWithBackend(options, dependencies = {})
if (isDasAlgorithm(algorithm.id)) {
return computeDasBackend(options, dependencies);
}
if (algorithm.id !== "gcc-phat") {
throw new RangeError("No backend dispatcher is registered for " + algorithm.id + ".");
}
const requestedBackend = options?.experiment?.beamforming?.backend ?? "auto";
if (requestedBackend === "webgpu") {
+32
View File
@@ -118,6 +118,38 @@ test("WebGPU DAS가 CPU 수치 기준과 일치하거나 auto CPU fallback한다
document.documentElement.dataset.webgpuRmsError = error.rms.toExponential(3);
});
test("WebGPU DAS-PHAT가 CPU score map과 일치하거나 auto CPU fallback한다", async () => {
const adapter = await globalThis.navigator?.gpu?.requestAdapter();
const fixture = createFixture(adapter ? "webgpu" : "auto");
fixture.experiment.beamforming.algorithm = "das-phat";
fixture.experiment.frequencyBands = [
{ id: "phase-1k", minHz: 900, maxHz: 1_100, color: "#65f2bf" },
];
if (!adapter) {
const result = await computeDasWithBackend(fixture);
assertEqual(result.backend, "cpu", "DAS-PHAT auto fallback backend");
assertEqual(result.algorithm, "das-phat", "DAS-PHAT fallback algorithm");
assertEqual(result.bands[0].rawScale, "score", "DAS-PHAT fallback scale");
return;
}
const cpuResult = await computeDasMap(fixture);
const gpuResult = await computeDasWebGpu(fixture);
const cpuBand = cpuResult.bands[0];
const gpuBand = gpuResult.bands[0];
const error = normalizedMapError(cpuBand.rawMap, gpuBand.rawMap);
assertEqual(gpuResult.algorithm, "das-phat", "actual WebGPU DAS-PHAT algorithm");
assertEqual(gpuBand.rawScale, "score", "actual WebGPU DAS-PHAT scale");
assert(!("rawPower" in gpuBand.peak), "DAS-PHAT GPU peak is not mislabeled as power");
assert(error.rms <= 0.005, `DAS-PHAT CPU/GPU normalized RMS error=${error.rms}`);
assert(
error.maximumAbsoluteError <= 0.02,
`DAS-PHAT CPU/GPU normalized max error=${error.maximumAbsoluteError}`,
);
});
test("192채널 · 50×50 WebGPU map이 CPU baseline 허용 오차를 만족한다", async () => {
const adapter = await globalThis.navigator?.gpu?.requestAdapter();
if (!adapter) {
+45 -2
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@@ -410,7 +410,28 @@ test("복수 음원 대응 result map 계약과 shape 관계를 검증한다", a
id: "tone-1k",
color: "#65f2bf",
rawMap: { rows: 50, columns: 50, scale: "power", values: Array(2500).fill(0) },
peaks: [{ sourceId: "source-1", position: [0.08, 0.04, 2], value: 1, localizationErrorM: 0 }],
peaks: [{
sourceId: "source-1",
position: [0.08, 0.04, 2],
value: 1,
localizationErrorM: 0,
beamSpread: {
calibrated: false,
method: "connected-half-power-power-weighted-covariance",
halfPowerRatio: 0.5,
thresholdValue: 0.5,
pixelCount: 1,
centroid: [0.08, 0.04, 2],
covarianceM2: { xx: 0, xy: 0, yy: 0 },
ellipse: {
axisScale: "rms",
angleReference: "counterclockwise-from-positive-x",
majorRmsRadiusM: 0,
minorRmsRadiusM: 0,
angleDeg: 0,
},
},
}],
metrics: { energyInsideTruthRatio: 1, precision: 1, recall: 1 },
}],
};
@@ -419,17 +440,39 @@ test("복수 음원 대응 result map 계약과 shape 관계를 검증한다", a
experiment.beamforming.algorithm = "das-phat";
result.algorithm = "das-phat";
result.bands[0].rawMap.scale = "score";
result.bands[0].peaks[0].beamSpread.method =
"connected-half-maximum-score-weighted-covariance";
assertEqual(
(await validateResult(result, { experiment, scene })).length,
0,
"phase-weighted score result issues",
);
result.algorithm = "das";
result.bands[0].rawMap.scale = "power";
let issues = await validateResult(result, { experiment, scene });
assert(
issues.some(({ path }) => path.endsWith("rawMap.scale")),
"algorithm and raw map scale must agree",
);
result.bands[0].rawMap.scale = "score";
result.bands[0].peaks[0].beamSpread.method =
"connected-half-power-power-weighted-covariance";
issues = await validateResult(result, { experiment, scene });
assert(
issues.some(({ path }) => path.endsWith("beamSpread.method")),
"score map and beam spread method must agree",
);
result.bands[0].peaks[0].beamSpread.method =
"connected-half-maximum-score-weighted-covariance";
result.algorithm = "das";
issues = await validateResult(result, { experiment, scene });
assert(issues.some(({ path }) => path === "$.algorithm"), "result algorithm must match its experiment");
experiment.beamforming.algorithm = "das";
result.bands[0].rawMap.scale = "power";
result.bands[0].peaks[0].beamSpread.method =
"connected-half-power-power-weighted-covariance";
result.bands[0].rawMap.values.pop();
result.bands[0].rawMap.scale = "normalized";
result.bands[0].peaks[0].sourceId = "missing-source";
+56 -2
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@@ -174,6 +174,18 @@ test("GCC-PHAT workload reports reference-pair scan reduction and rejects aliase
"maximum geometric lag is exposed and unaliased",
);
let preflightError;
try {
estimateGccPhatWorkload({ ...fixture, maximumWorkingBytes: 1 });
} catch (error) {
preflightError = error;
}
assert(
preflightError instanceof RangeError &&
preflightError.message.includes("before geometry allocation"),
"unplanned workload is rejected before allocating its distance matrix",
);
let memoryError;
try {
createGccPhatAnalysisPlan({ ...fixture, maximumPlanBytes: 1 });
@@ -241,8 +253,8 @@ test("GCC-PHAT corrected lag sign finds a deterministic broadband source and emi
assertNear(result.maximumLagSamples, result.workload.maximumLagSamples, 0, "lag metadata");
assertEqual(band.rawScale, "score", "raw map scale");
assert(
band.rawMap.every((value) => Number.isFinite(value) && value >= 0),
"shifted and squared score map is finite and nonnegative",
band.rawMap.every((value) => Number.isFinite(value) && value >= 0 && value <= 1),
"pair- and bandwidth-normalized score map is finite and bounded",
);
assert(
distance3(peakPosition, fixture.target) <= 0.15,
@@ -263,6 +275,48 @@ test("GCC-PHAT corrected lag sign finds a deterministic broadband source and emi
"X_m * conj(X_ref) correlation uses the physical arrival-lag sign",
);
assertNear(Math.max(...band.displayMap), 1, 1e-6, "normalized score display");
const expandedFixture = createBroadbandFixture();
expandedFixture.experiment.scan = {
...expandedFixture.experiment.scan,
xMin: -0.8,
xMax: 0.8,
yMin: -0.8,
yMax: 0.8,
columns: 17,
rows: 17,
};
const expanded = await computeGccPhatMap({
...expandedFixture,
phatFloorRatio: 1e-5,
pointBatchSize: 1024,
stftTransformBatchSize: 1024,
});
const expandedTargetIndex = scanIndexFor(
expandedFixture.experiment.scan,
expandedFixture.target[0],
expandedFixture.target[1],
);
assertNear(
expanded.bands[0].rawMap[expandedTargetIndex],
band.rawMap[targetIndex],
1e-6,
"raw score at a fixed hypothesis is independent of scan extent",
);
});
test("GCC-PHAT compute rejects an oversized unplanned working set before geometry", async () => {
const fixture = createBroadbandFixture();
let error;
try {
await computeGccPhatMap({ ...fixture, maximumWorkingBytes: 1 });
} catch (candidate) {
error = candidate;
}
assert(
error instanceof RangeError && error.message.includes("before geometry allocation"),
"compute preflight error",
);
});
test("GCC-PHAT analysis plan reuses geometry and FFT workspaces and releases its busy lock", async () => {
+16
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@@ -3,6 +3,10 @@ import {
createLocalizationAnalysisPlan,
estimateLocalizationWorkload,
} from "/packages/acoustics-core/localization.js";
import {
DEFAULT_GCC_PHAT_CROSS_SPECTRUM_BATCH_SIZE,
DEFAULT_GCC_PHAT_POINT_BATCH_SIZE,
} from "/packages/acoustics-core/gcc-phat.js";
import {
DEFAULT_LOCALIZATION_ALGORITHM,
LOCALIZATION_ALGORITHM_IDS,
@@ -167,10 +171,22 @@ test("portable and streaming API accept an algorithm choice without Scene synthe
computeOptions: { pointBatchSize: 1024, stftTransformBatchSize: 1024 },
};
const plan = createLocalizationPlan(config);
const defaultBatchPlan = createLocalizationPlan({ ...config, computeOptions: undefined });
const localized = await localizeMultichannel({ plan, channels: fixture.channels });
assertEqual(plan.algorithm, "gcc-phat", "portable plan algorithm");
assertEqual(plan.computeOptions.phatFloorRatio, 1e-5, "portable PHAT floor forwarding");
assertEqual(plan.analysisPlan, plan.gccPhatPlan, "portable GCC plan alias");
assertEqual(plan.computeOptions.pointBatchSize, 1024, "explicit portable point batch override");
assertEqual(
defaultBatchPlan.computeOptions.pointBatchSize,
DEFAULT_GCC_PHAT_POINT_BATCH_SIZE,
"GCC lookup-oriented default batch",
);
assertEqual(
defaultBatchPlan.computeOptions.crossSpectrumBatchSize,
DEFAULT_GCC_PHAT_CROSS_SPECTRUM_BATCH_SIZE,
"GCC cross-spectrum cancellation batch",
);
assertEqual(localized.algorithm, "gcc-phat", "portable result algorithm");
assertEqual(localized.phatFloorRatio, 1e-5, "portable PHAT floor reaches GCC core");
assertEqual(localized.bands[0].rawScale, "score", "portable score map");