fix: stabilize localization comparison semantics
This commit is contained in:
@@ -601,15 +601,24 @@ export function estimateDasWorkload(options) {
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};
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}
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export function finalizeDasBands(rawMaps, workload, experiment, rawScale = "power") {
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export function finalizeDasBands(
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rawMaps,
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workload,
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experiment,
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rawScale = "power",
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options = {},
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) {
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if (rawScale !== "power" && rawScale !== "score") {
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throw new RangeError('rawScale must be "power" or "score".');
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}
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const averageBandBins = options.averageBandBins !== false;
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return experiment.frequencyBands.map((band, bandIndex) => {
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const rawMap = rawMaps[bandIndex];
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if (averageBandBins) {
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for (let pointIndex = 0; pointIndex < workload.pointCount; pointIndex += 1) {
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rawMap[pointIndex] /= workload.bandBins[bandIndex].length;
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}
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}
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const rawPeak = findPeak(rawMap);
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const displayMap = Float32Array.from(rawMap);
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let displayScale = rawScale;
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@@ -14,7 +14,10 @@ import {
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export const GCC_PHAT_ANALYSIS_PLAN_KIND = "micarrsim.gcc-phat-analysis-plan/1";
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export const DEFAULT_GCC_PHAT_FLOOR_RATIO = 1e-6;
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export const DEFAULT_GCC_PHAT_POINT_BATCH_SIZE = 4096;
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export const DEFAULT_GCC_PHAT_CROSS_SPECTRUM_BATCH_SIZE = 16384;
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export const DEFAULT_MAXIMUM_GCC_PHAT_PLAN_BYTES = 512 * 1024 * 1024;
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export const DEFAULT_MAXIMUM_GCC_PHAT_WORKING_BYTES = 512 * 1024 * 1024;
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function createAbortError(signal) {
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if (signal?.reason instanceof Error && signal.reason.name === "AbortError") {
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@@ -241,6 +244,60 @@ function requirePhatFloorRatio(value) {
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return ratio;
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}
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function requireMaximumWorkingBytes(value) {
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const maximumWorkingBytes = value ?? DEFAULT_MAXIMUM_GCC_PHAT_WORKING_BYTES;
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if (!Number.isSafeInteger(maximumWorkingBytes) || maximumWorkingBytes <= 0) {
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throw new RangeError("maximumWorkingBytes must be a positive safe integer.");
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}
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return maximumWorkingBytes;
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}
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/**
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* Reject an oversized no-plan analysis before createDistanceMatrix allocates
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* its P x M table. This mirrors estimateWithGeometry's retained/spectrum/
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* calibration/output accounting without requiring geometry to exist first.
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*/
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function preflightUnplannedWorkingSet(options, configuration) {
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const microphoneCount = configuration.arrayDefinition.microphones.length;
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const sampleCount = validateChannels(options.channels, microphoneCount);
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const { bandBins, selectedBins } = createBandGeometry(configuration);
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const frameCount = getFrameCount(
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sampleCount,
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configuration.fftSize,
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configuration.hopSize,
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);
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const bandCount = bandBins.length;
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const distanceBytes =
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configuration.pointCount * microphoneCount * Float32Array.BYTES_PER_ELEMENT;
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const stftWorkspaceBytes =
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configuration.fftSize * Float64Array.BYTES_PER_ELEMENT * 3;
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const correlationWorkspaceBytes =
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configuration.fftSize * Float64Array.BYTES_PER_ELEMENT * 2;
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const spectrumBytes =
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selectedBins.length * frameCount * microphoneCount *
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Float32Array.BYTES_PER_ELEMENT * 2;
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const calibrationPhaseBytes =
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selectedBins.length * microphoneCount * Float64Array.BYTES_PER_ELEMENT;
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const outputBytes =
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bandCount * configuration.pointCount * Float32Array.BYTES_PER_ELEMENT * 2;
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const estimatedWorkingBytes =
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distanceBytes + stftWorkspaceBytes + correlationWorkspaceBytes +
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spectrumBytes + calibrationPhaseBytes + outputBytes;
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if (!Number.isSafeInteger(estimatedWorkingBytes)) {
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throw new RangeError("GCC-PHAT estimated working set exceeds the safe integer range.");
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}
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const maximumWorkingBytes = requireMaximumWorkingBytes(options.maximumWorkingBytes);
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if (estimatedWorkingBytes > maximumWorkingBytes) {
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throw new RangeError(
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"GCC-PHAT estimated working set " +
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(estimatedWorkingBytes / 1024 ** 2).toFixed(1) +
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" MiB exceeds maximumWorkingBytes " +
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(maximumWorkingBytes / 1024 ** 2).toFixed(1) + " MiB before geometry allocation.",
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);
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}
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return { estimatedWorkingBytes, maximumWorkingBytes };
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}
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function estimateWithGeometry(options, configuration, geometry) {
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const sampleCount = validateChannels(options.channels, geometry.microphoneCount);
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const frameCount = getFrameCount(
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@@ -332,6 +389,7 @@ export function estimateGccPhatWorkload(options) {
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assertCompatibleAnalysisPlan(options.analysisPlan, options);
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geometry = options.analysisPlan;
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} else {
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preflightUnplannedWorkingSet(options, configuration);
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geometry = createGeometry(configuration);
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}
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return estimateWithGeometry(options, configuration, geometry);
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@@ -467,7 +525,7 @@ function circularLinearSample(values, lagSamples) {
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return values[firstIndex] * (1 - fraction) + values[secondIndex] * fraction;
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}
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function fillBandPairCorrelation({
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async function fillBandPairCorrelation({
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correlationReal,
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correlationImaginary,
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bins,
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@@ -476,11 +534,14 @@ function fillBandPairCorrelation({
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referenceIndex,
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phasesByBin,
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phatFloorRatio,
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signal,
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crossSpectrumBatchSize,
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}) {
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correlationReal.fill(0);
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correlationImaginary.fill(0);
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const microphoneCount = stft.microphoneCount;
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let maximumMagnitude = 0;
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let operationsUntilYield = crossSpectrumBatchSize;
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for (const bin of bins) {
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const spectrum = stft.spectra.get(bin);
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@@ -498,6 +559,12 @@ function fillBandPairCorrelation({
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maximumMagnitude,
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Math.hypot(crossReal, crossImaginary),
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);
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operationsUntilYield -= 1;
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if (operationsUntilYield === 0) {
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await cooperativeYield();
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throwIfAborted(signal);
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operationsUntilYield = crossSpectrumBatchSize;
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}
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}
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}
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@@ -535,6 +602,12 @@ function fillBandPairCorrelation({
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normalizedReal * correctionReal - normalizedImaginary * correctionImaginary;
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accumulatedImaginary +=
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normalizedReal * correctionImaginary + normalizedImaginary * correctionReal;
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operationsUntilYield -= 1;
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if (operationsUntilYield === 0) {
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await cooperativeYield();
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throwIfAborted(signal);
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operationsUntilYield = crossSpectrumBatchSize;
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}
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}
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const averagedReal = accumulatedReal / stft.frameCount;
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@@ -552,13 +625,38 @@ function fillBandPairCorrelation({
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fftInPlace(correlationReal, correlationImaginary, true);
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}
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function shiftAndSquareScores(rawMaps) {
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for (const rawMap of rawMaps) {
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let minimum = Infinity;
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for (const value of rawMap) minimum = Math.min(minimum, value);
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async function normalizePositiveScores(
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rawMaps,
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bandBins,
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fftSize,
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pairCount,
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pointBatchSize,
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signal,
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) {
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for (let bandIndex = 0; bandIndex < rawMaps.length; bandIndex += 1) {
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const rawMap = rawMaps[bandIndex];
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const coefficientCount = bandBins[bandIndex].reduce(
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(count, bin) => count + (bin === 0 || bin === fftSize / 2 ? 1 : 2),
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0,
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);
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const normalization = fftSize / (pairCount * coefficientCount);
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for (let pointIndex = 0; pointIndex < rawMap.length; pointIndex += 1) {
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const shifted = rawMap[pointIndex] - minimum;
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rawMap[pointIndex] = shifted * shifted;
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// PHAT coefficients have magnitude <= 1. After Hermitian completion and
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// inverse-FFT scaling, coefficientCount / fftSize is therefore a strict
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// per-pair bound. Pair averaging makes the positive score stable across
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// microphone count, band width, and scan extent without implying a
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// probability. Negative correlation is evidence against the hypothesis.
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rawMap[pointIndex] = Math.min(
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1,
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Math.max(0, rawMap[pointIndex] * normalization),
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);
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if (
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(pointIndex + 1) % pointBatchSize === 0 &&
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pointIndex + 1 < rawMap.length
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) {
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await cooperativeYield();
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throwIfAborted(signal);
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}
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}
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}
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}
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@@ -568,16 +666,16 @@ async function computeGccPhatMapInternal(options, configuration, geometry, plan)
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channels,
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signal,
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onProgress,
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maximumWorkingBytes = 512 * 1024 * 1024,
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maximumWorkingBytes = DEFAULT_MAXIMUM_GCC_PHAT_WORKING_BYTES,
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maximumFftButterflies = 1_000_000_000,
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pointBatchSize = 256,
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pointBatchSize = DEFAULT_GCC_PHAT_POINT_BATCH_SIZE,
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crossSpectrumBatchSize = DEFAULT_GCC_PHAT_CROSS_SPECTRUM_BATCH_SIZE,
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stftTransformBatchSize = 128,
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} = options;
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requirePositiveInteger(pointBatchSize, "pointBatchSize");
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requirePositiveInteger(crossSpectrumBatchSize, "crossSpectrumBatchSize");
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requirePositiveInteger(stftTransformBatchSize, "stftTransformBatchSize");
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if (!Number.isSafeInteger(maximumWorkingBytes) || maximumWorkingBytes <= 0) {
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throw new RangeError("maximumWorkingBytes must be a positive safe integer.");
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}
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requireMaximumWorkingBytes(maximumWorkingBytes);
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const phatFloorRatio = requirePhatFloorRatio(
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options.phatFloorRatio ??
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options.phatRelativeFloor ??
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@@ -666,7 +764,7 @@ async function computeGccPhatMapInternal(options, configuration, geometry, plan)
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const rawMap = rawMaps[bandIndex];
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for (const microphoneIndex of geometry.pairMicrophoneIndexes) {
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throwIfAborted(signal);
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fillBandPairCorrelation({
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await fillBandPairCorrelation({
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correlationReal,
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correlationImaginary,
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bins,
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@@ -675,6 +773,8 @@ async function computeGccPhatMapInternal(options, configuration, geometry, plan)
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referenceIndex: geometry.reference.index,
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phasesByBin,
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phatFloorRatio,
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signal,
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crossSpectrumBatchSize,
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});
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if (plan) {
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plan.statistics.inverseFftTransforms += 1;
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@@ -715,12 +815,20 @@ async function computeGccPhatMapInternal(options, configuration, geometry, plan)
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}
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throwIfAborted(signal);
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shiftAndSquareScores(rawMaps);
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await normalizePositiveScores(
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rawMaps,
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geometry.bandBins,
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configuration.fftSize,
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geometry.pairCount,
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pointBatchSize,
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signal,
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);
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const bands = finalizeDasBands(
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rawMaps,
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workload,
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configuration.experiment,
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"score",
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{ averageBandBins: false },
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);
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return {
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backend: "cpu",
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@@ -753,6 +861,7 @@ export async function computeGccPhatMap(options) {
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const configuration = validateConfiguration(options);
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const plan = options.analysisPlan;
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if (!plan) {
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preflightUnplannedWorkingSet(options, configuration);
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const geometry = createGeometry(configuration);
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return computeGccPhatMapInternal(options, configuration, geometry, undefined);
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}
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@@ -25,9 +25,9 @@ function requestedAlgorithm(options) {
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*/
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export function estimateLocalizationWorkload(options) {
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const algorithm = requestedAlgorithm(options);
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return isDasAlgorithm(algorithm.id)
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? estimateDasWorkload(options)
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: estimateGccPhatWorkload(options);
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if (isDasAlgorithm(algorithm.id)) return estimateDasWorkload(options);
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if (algorithm.id === "gcc-phat") return estimateGccPhatWorkload(options);
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throw new RangeError("No workload estimator is registered for " + algorithm.id + ".");
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}
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/**
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@@ -35,9 +35,9 @@ export function estimateLocalizationWorkload(options) {
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*/
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export function createLocalizationAnalysisPlan(options) {
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const algorithm = requestedAlgorithm(options);
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return isDasAlgorithm(algorithm.id)
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? createDasAnalysisPlan(options)
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: createGccPhatAnalysisPlan(options);
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if (isDasAlgorithm(algorithm.id)) return createDasAnalysisPlan(options);
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if (algorithm.id === "gcc-phat") return createGccPhatAnalysisPlan(options);
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throw new RangeError("No analysis-plan factory is registered for " + algorithm.id + ".");
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}
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/**
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@@ -47,7 +47,7 @@ export function createLocalizationAnalysisPlan(options) {
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*/
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export async function computeLocalizationMap(options) {
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const algorithm = requestedAlgorithm(options);
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return isDasAlgorithm(algorithm.id)
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? computeDasMap(options)
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: computeGccPhatMap(options);
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if (isDasAlgorithm(algorithm.id)) return computeDasMap(options);
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if (algorithm.id === "gcc-phat") return computeGccPhatMap(options);
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throw new RangeError("No CPU localization implementation is registered for " + algorithm.id + ".");
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}
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@@ -3,6 +3,10 @@ import {
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computeLocalizationMap,
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createLocalizationAnalysisPlan,
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} from "./localization.js";
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import {
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DEFAULT_GCC_PHAT_CROSS_SPECTRUM_BATCH_SIZE,
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DEFAULT_GCC_PHAT_POINT_BATCH_SIZE,
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} from "./gcc-phat.js";
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import {
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isDasAlgorithm,
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requireLocalizationAlgorithmDefinition,
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@@ -355,8 +359,13 @@ export function createLocalizationPlan(config) {
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? { dasPlan: analysisPlan }
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: { gccPhatPlan: analysisPlan }),
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computeOptions: Object.freeze({
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pointBatchSize: DEFAULT_REALTIME_POINT_BATCH_SIZE,
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pointBatchSize: isDasAlgorithm(algorithm.id)
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? DEFAULT_REALTIME_POINT_BATCH_SIZE
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: DEFAULT_GCC_PHAT_POINT_BATCH_SIZE,
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stftTransformBatchSize: DEFAULT_REALTIME_STFT_TRANSFORM_BATCH_SIZE,
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...(!isDasAlgorithm(algorithm.id)
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? { crossSpectrumBatchSize: DEFAULT_GCC_PHAT_CROSS_SPECTRUM_BATCH_SIZE }
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: {}),
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...(phatRelativeFloor !== undefined ? { phatRelativeFloor } : {}),
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...(phatFloorRatio !== undefined ? { phatFloorRatio } : {}),
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...(config.computeOptions ?? {}),
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@@ -555,6 +555,19 @@ function validateResultRelationships(value, context = {}) {
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}
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const sourceIds = new Set(context.scene?.sources?.map((source) => source.id) ?? []);
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const expectedBandIds = new Set(context.experiment?.frequencyBands?.map((band) => band.id) ?? []);
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const resultAlgorithm = value.algorithm ?? context.experiment?.beamforming?.algorithm;
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const expectedRawScale =
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resultAlgorithm === "das"
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? "power"
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: resultAlgorithm === "das-phat" || resultAlgorithm === "gcc-phat"
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? "score"
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: undefined;
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const expectedBeamSpreadMethod =
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expectedRawScale === "power"
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? "connected-half-power-power-weighted-covariance"
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: expectedRawScale === "score"
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? "connected-half-maximum-score-weighted-covariance"
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: undefined;
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const bandIds = [];
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if (Array.isArray(value.bands)) {
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value.bands.forEach((band, bandIndex) => {
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@@ -576,12 +589,33 @@ function validateResultRelationships(value, context = {}) {
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});
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if (isRecord(band.rawMap) && !["power", "score"].includes(band.rawMap.scale)) {
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addIssue(issues, `${path}.rawMap.scale`, "rawMap은 power 또는 score scale이어야 합니다.");
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} else if (
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isRecord(band.rawMap) &&
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expectedRawScale &&
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band.rawMap.scale !== expectedRawScale
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) {
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addIssue(
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issues,
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`${path}.rawMap.scale`,
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`${resultAlgorithm} 결과의 rawMap scale은 ${expectedRawScale}여야 합니다.`,
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);
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}
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if (Array.isArray(band.peaks)) {
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band.peaks.forEach((peak, peakIndex) => {
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if (peak?.sourceId && sourceIds.size > 0 && !sourceIds.has(peak.sourceId)) {
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addIssue(issues, `${path}.peaks[${peakIndex}].sourceId`, "장면에 없는 source id입니다.");
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}
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if (
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expectedBeamSpreadMethod &&
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isRecord(peak?.beamSpread) &&
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peak.beamSpread.method !== expectedBeamSpreadMethod
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) {
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addIssue(
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issues,
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`${path}.peaks[${peakIndex}].beamSpread.method`,
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`${expectedRawScale} map과 맞는 beamSpread method여야 합니다.`,
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);
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}
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});
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}
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});
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@@ -90,6 +90,9 @@ export async function computeLocalizationWithBackend(options, dependencies = {})
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if (isDasAlgorithm(algorithm.id)) {
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return computeDasBackend(options, dependencies);
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}
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if (algorithm.id !== "gcc-phat") {
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throw new RangeError("No backend dispatcher is registered for " + algorithm.id + ".");
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}
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const requestedBackend = options?.experiment?.beamforming?.backend ?? "auto";
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if (requestedBackend === "webgpu") {
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@@ -118,6 +118,38 @@ test("WebGPU DAS가 CPU 수치 기준과 일치하거나 auto CPU fallback한다
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document.documentElement.dataset.webgpuRmsError = error.rms.toExponential(3);
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});
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test("WebGPU DAS-PHAT가 CPU score map과 일치하거나 auto CPU fallback한다", async () => {
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const adapter = await globalThis.navigator?.gpu?.requestAdapter();
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const fixture = createFixture(adapter ? "webgpu" : "auto");
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fixture.experiment.beamforming.algorithm = "das-phat";
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fixture.experiment.frequencyBands = [
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{ id: "phase-1k", minHz: 900, maxHz: 1_100, color: "#65f2bf" },
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];
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if (!adapter) {
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const result = await computeDasWithBackend(fixture);
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assertEqual(result.backend, "cpu", "DAS-PHAT auto fallback backend");
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assertEqual(result.algorithm, "das-phat", "DAS-PHAT fallback algorithm");
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assertEqual(result.bands[0].rawScale, "score", "DAS-PHAT fallback scale");
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return;
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}
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const cpuResult = await computeDasMap(fixture);
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const gpuResult = await computeDasWebGpu(fixture);
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const cpuBand = cpuResult.bands[0];
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const gpuBand = gpuResult.bands[0];
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const error = normalizedMapError(cpuBand.rawMap, gpuBand.rawMap);
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assertEqual(gpuResult.algorithm, "das-phat", "actual WebGPU DAS-PHAT algorithm");
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assertEqual(gpuBand.rawScale, "score", "actual WebGPU DAS-PHAT scale");
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assert(!("rawPower" in gpuBand.peak), "DAS-PHAT GPU peak is not mislabeled as power");
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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) {
|
||||
|
||||
@@ -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";
|
||||
|
||||
@@ -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 () => {
|
||||
|
||||
@@ -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");
|
||||
|
||||
Reference in New Issue
Block a user