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micarrsim/packages/acoustics-core/gcc-phat.js
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JavaScript

import {
createBinCalibration,
createDistanceMatrix,
finalizeDasBands,
} from "./das.js";
import { cooperativeYield } from "./cooperative-yield.js";
import { fftInPlace } from "./fft.js";
import {
binsForBand,
createStftWorkspace,
extractStftBins,
getFrameCount,
} from "./stft.js";
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_MAXIMUM_GCC_PHAT_PLAN_BYTES = 512 * 1024 * 1024;
function createAbortError(signal) {
if (signal?.reason instanceof Error && signal.reason.name === "AbortError") {
return signal.reason;
}
const error = new Error("GCC-PHAT localization was canceled.");
error.name = "AbortError";
return error;
}
function throwIfAborted(signal) {
if (signal?.aborted) throw createAbortError(signal);
}
function requirePositiveFinite(value, label) {
if (!Number.isFinite(value) || value <= 0) {
throw new RangeError(label + " must be a positive finite number.");
}
return value;
}
function requirePositiveInteger(value, label) {
if (!Number.isInteger(value) || value < 1) {
throw new RangeError(label + " must be a positive integer.");
}
return value;
}
function validateArrayDefinition(arrayDefinition) {
if (!Array.isArray(arrayDefinition?.microphones) || arrayDefinition.microphones.length < 2) {
throw new RangeError("GCC-PHAT requires at least two microphones.");
}
arrayDefinition.microphones.forEach((microphone, index) => {
if (
!Array.isArray(microphone?.position) ||
microphone.position.length !== 3 ||
!microphone.position.every(Number.isFinite)
) {
throw new TypeError(
"arrayDefinition.microphones[" + index + "].position must be a finite [x, y, z] array.",
);
}
});
return arrayDefinition;
}
function validateConfiguration(options) {
const sampleRate = requirePositiveFinite(options.sampleRate, "sampleRate");
const arrayDefinition = validateArrayDefinition(options.arrayDefinition);
const speedOfSound = requirePositiveFinite(options.scene?.speedOfSound, "scene.speedOfSound");
const experiment = options.experiment;
if (!experiment?.stft || !experiment?.scan || !Array.isArray(experiment.frequencyBands)) {
throw new TypeError("experiment must contain stft, scan, and frequencyBands.");
}
const fftSize = requirePositiveInteger(experiment.stft.fftSize, "experiment.stft.fftSize");
if ((fftSize & (fftSize - 1)) !== 0) {
throw new RangeError("experiment.stft.fftSize must be a power of two.");
}
const hopSize = requirePositiveInteger(experiment.stft.hopSize, "experiment.stft.hopSize");
if (hopSize > fftSize) {
throw new RangeError("experiment.stft.hopSize must not exceed fftSize.");
}
const pointCount =
requirePositiveInteger(experiment.scan.columns, "experiment.scan.columns") *
requirePositiveInteger(experiment.scan.rows, "experiment.scan.rows");
if (!Number.isSafeInteger(pointCount)) {
throw new RangeError("scan point count exceeds the safe integer range.");
}
if (experiment.frequencyBands.length === 0) {
throw new RangeError("experiment.frequencyBands must not be empty.");
}
return { sampleRate, arrayDefinition, speedOfSound, experiment, fftSize, hopSize, pointCount };
}
function validateChannels(channels, microphoneCount) {
if (!Array.isArray(channels) || channels.length !== microphoneCount) {
throw new Error(
"channel count " + (channels?.length ?? 0) +
" does not match microphone count " + microphoneCount + ".",
);
}
if (!channels.every((channel) => channel instanceof Float32Array)) {
throw new TypeError("every channel must be a Float32Array.");
}
const sampleCount = channels[0].length;
if (sampleCount === 0) throw new RangeError("channels must contain at least one sample.");
if (channels.some((channel) => channel.length !== sampleCount)) {
throw new Error("all channels must have the same sample count.");
}
return sampleCount;
}
function referenceTieBreak(left, right) {
if (left.id < right.id) return -1;
if (left.id > right.id) return 1;
return left.index - right.index;
}
/**
* Select a stable reference without depending on microphone input order.
*
* A peripheral microphone generally provides a longer TDOA baseline. Exact
* geometric ties are resolved by microphone id and finally by input index.
*/
export function selectGccPhatReference(arrayDefinition) {
validateArrayDefinition(arrayDefinition);
const centroid = [0, 0, 0];
for (const microphone of arrayDefinition.microphones) {
for (let axis = 0; axis < 3; axis += 1) centroid[axis] += microphone.position[axis];
}
for (let axis = 0; axis < 3; axis += 1) {
centroid[axis] /= arrayDefinition.microphones.length;
}
let selected;
arrayDefinition.microphones.forEach((microphone, index) => {
const descriptor = {
index,
id: String(microphone.id ?? ""),
microphone,
distanceSquared:
(microphone.position[0] - centroid[0]) ** 2 +
(microphone.position[1] - centroid[1]) ** 2 +
(microphone.position[2] - centroid[2]) ** 2,
};
if (!selected) {
selected = descriptor;
return;
}
if (
descriptor.distanceSquared > selected.distanceSquared ||
(
descriptor.distanceSquared === selected.distanceSquared &&
referenceTieBreak(descriptor, selected) < 0
)
) {
selected = descriptor;
}
});
return Object.freeze({
index: selected.index,
id: selected.id,
microphone: selected.microphone,
});
}
function createBandGeometry(configuration) {
const bandBins = configuration.experiment.frequencyBands.map((band) =>
binsForBand(band, configuration.sampleRate, configuration.fftSize)
);
const selectedBins = [...new Set(bandBins.flat())].sort((left, right) => left - right);
return { bandBins, selectedBins };
}
function maximumGeometricLagSamples({
distances,
pointCount,
microphoneCount,
referenceIndex,
sampleRate,
speedOfSound,
}) {
let maximumLagSamples = 0;
for (let pointIndex = 0; pointIndex < pointCount; pointIndex += 1) {
const distanceOffset = pointIndex * microphoneCount;
const referenceDistance = distances[distanceOffset + referenceIndex];
for (let microphoneIndex = 0; microphoneIndex < microphoneCount; microphoneIndex += 1) {
if (microphoneIndex === referenceIndex) continue;
const lagSamples =
Math.abs(distances[distanceOffset + microphoneIndex] - referenceDistance) *
sampleRate / speedOfSound;
maximumLagSamples = Math.max(maximumLagSamples, lagSamples);
}
}
return maximumLagSamples;
}
function assertUnaliasedLag(maximumLagSamples, fftSize) {
const maximumUnaliasedLag = fftSize / 2;
if (maximumLagSamples > maximumUnaliasedLag) {
throw new RangeError(
"GCC-PHAT maximum absolute geometric lag " + maximumLagSamples.toFixed(3) +
" samples exceeds fftSize/2 (" + maximumUnaliasedLag +
"); increase fftSize or reduce the array aperture or scan range.",
);
}
}
function createGeometry(configuration, distances) {
const microphoneCount = configuration.arrayDefinition.microphones.length;
const reference = selectGccPhatReference(configuration.arrayDefinition);
const pairMicrophoneIndexes = [];
for (let microphoneIndex = 0; microphoneIndex < microphoneCount; microphoneIndex += 1) {
if (microphoneIndex !== reference.index) pairMicrophoneIndexes.push(microphoneIndex);
}
const resolvedDistances =
distances ?? createDistanceMatrix(configuration.arrayDefinition, configuration.experiment.scan);
const maximumLagSamples = maximumGeometricLagSamples({
distances: resolvedDistances,
pointCount: configuration.pointCount,
microphoneCount,
referenceIndex: reference.index,
sampleRate: configuration.sampleRate,
speedOfSound: configuration.speedOfSound,
});
assertUnaliasedLag(maximumLagSamples, configuration.fftSize);
return {
microphoneCount,
reference,
pairMicrophoneIndexes,
pairCount: pairMicrophoneIndexes.length,
distances: resolvedDistances,
maximumLagSamples,
...createBandGeometry(configuration),
};
}
function requirePhatFloorRatio(value) {
const ratio = value ?? DEFAULT_GCC_PHAT_FLOOR_RATIO;
if (!Number.isFinite(ratio) || ratio < 0 || ratio > 1) {
throw new RangeError("phatFloorRatio must be a finite number from 0 through 1.");
}
return ratio;
}
function estimateWithGeometry(options, configuration, geometry) {
const sampleCount = validateChannels(options.channels, geometry.microphoneCount);
const frameCount = getFrameCount(
sampleCount,
configuration.fftSize,
configuration.hopSize,
);
const pairCount = geometry.pairCount;
const bandCount = geometry.bandBins.length;
const bandBinCount = geometry.bandBins.reduce((sum, bins) => sum + bins.length, 0);
const selectedBinCount = geometry.selectedBins.length;
const stftTransformCount = frameCount * geometry.microphoneCount;
const inverseFftCount = pairCount * bandCount;
const fftButterfliesPerTransform =
(configuration.fftSize / 2) * Math.log2(configuration.fftSize);
const stftButterflyCount = stftTransformCount * fftButterfliesPerTransform;
const inverseFftButterflyCount = inverseFftCount * fftButterfliesPerTransform;
const crossSpectrumSampleCount = pairCount * frameCount * bandBinCount;
// The relative-floor pass finds the maximum magnitude, then the PHAT pass
// recomputes and accumulates each complex cross-spectrum sample.
const crossSpectrumComplexOpCount = crossSpectrumSampleCount * 2;
const scanLookupCount = configuration.pointCount * pairCount * bandCount;
const dasEquivalentComplexMacCount =
configuration.pointCount * geometry.microphoneCount * frameCount * selectedBinCount;
const distanceBytes =
configuration.pointCount * geometry.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 =
selectedBinCount * frameCount * geometry.microphoneCount *
Float32Array.BYTES_PER_ELEMENT * 2;
const calibrationPhaseBytes =
selectedBinCount * geometry.microphoneCount * Float64Array.BYTES_PER_ELEMENT;
const outputBytes =
bandCount * configuration.pointCount * Float32Array.BYTES_PER_ELEMENT * 2;
const retainedPlanBytes =
options.analysisPlan?.retainedBytes ??
distanceBytes + stftWorkspaceBytes + correlationWorkspaceBytes;
const estimatedWorkingBytes =
retainedPlanBytes + spectrumBytes + calibrationPhaseBytes + outputBytes;
return {
bandBins: geometry.bandBins,
selectedBins: geometry.selectedBins,
selectedBinCount,
bandBinCount,
frameCount,
microphoneCount: geometry.microphoneCount,
pointCount: configuration.pointCount,
bandCount,
pairCount,
referenceMicrophoneId: geometry.reference.id,
referenceMicrophoneIndex: geometry.reference.index,
maximumLagSamples: geometry.maximumLagSamples,
stftTransformCount,
inverseFftCount,
stftButterflyCount,
inverseFftButterflyCount,
crossSpectrumSampleCount,
crossSpectrumComplexOpCount,
crossSpectrumCount: crossSpectrumComplexOpCount,
complexMacCount: crossSpectrumComplexOpCount,
scanLookupCount,
operationCount: crossSpectrumComplexOpCount + scanLookupCount,
dasEquivalentComplexMacCount,
distanceBytes,
stftWorkspaceBytes,
correlationWorkspaceBytes,
spectrumBytes,
calibrationPhaseBytes,
outputBytes,
retainedPlanBytes,
estimatedWorkingBytes,
};
}
/**
* Estimate CPU work for one reference-pair GCC-PHAT analysis.
*/
export function estimateGccPhatWorkload(options) {
if (!options || typeof options !== "object") {
throw new TypeError("options must be an object.");
}
const configuration = validateConfiguration(options);
let geometry;
if (options.analysisPlan) {
assertCompatibleAnalysisPlan(options.analysisPlan, options);
geometry = options.analysisPlan;
} else {
geometry = createGeometry(configuration);
}
return estimateWithGeometry(options, configuration, geometry);
}
/**
* Retain geometry and FFT workspaces for repeated analyses with one immutable
* array/scan/band configuration. Plans are stateful and cannot run concurrently.
*/
export function createGccPhatAnalysisPlan(options) {
if (!options || typeof options !== "object") {
throw new TypeError("options must be an object.");
}
const configuration = validateConfiguration(options);
const maximumPlanBytes =
options.maximumPlanBytes ?? DEFAULT_MAXIMUM_GCC_PHAT_PLAN_BYTES;
if (!Number.isSafeInteger(maximumPlanBytes) || maximumPlanBytes <= 0) {
throw new RangeError("maximumPlanBytes must be a positive safe integer.");
}
const microphoneCount = configuration.arrayDefinition.microphones.length;
const pointMicrophonePairs = configuration.pointCount * microphoneCount;
const distanceBytes = pointMicrophonePairs * Float32Array.BYTES_PER_ELEMENT;
const stftWorkspaceBytes =
configuration.fftSize * Float64Array.BYTES_PER_ELEMENT * 3;
const correlationWorkspaceBytes =
configuration.fftSize * Float64Array.BYTES_PER_ELEMENT * 2;
const retainedBytes = distanceBytes + stftWorkspaceBytes + correlationWorkspaceBytes;
if (
!Number.isSafeInteger(pointMicrophonePairs) ||
!Number.isSafeInteger(retainedBytes) ||
retainedBytes > maximumPlanBytes
) {
throw new RangeError(
"GCC-PHAT analysis plan requires " + retainedBytes.toLocaleString() +
" bytes, above maximumPlanBytes " + maximumPlanBytes.toLocaleString() + ".",
);
}
const distances = createDistanceMatrix(
configuration.arrayDefinition,
configuration.experiment.scan,
);
const geometry = createGeometry(configuration, distances);
const plan = {
kind: GCC_PHAT_ANALYSIS_PLAN_KIND,
sampleRate: configuration.sampleRate,
arrayDefinition: configuration.arrayDefinition,
scene: options.scene,
experiment: configuration.experiment,
fftSize: configuration.fftSize,
hopSize: configuration.hopSize,
pointCount: configuration.pointCount,
maximumPlanBytes,
retainedBytes,
distanceBytes,
stftWorkspaceBytes,
correlationWorkspaceBytes,
stftWorkspace: createStftWorkspace(configuration.fftSize),
correlationReal: new Float64Array(configuration.fftSize),
correlationImaginary: new Float64Array(configuration.fftSize),
busy: false,
statistics: {
analysisAttempts: 0,
completedAnalyses: 0,
distanceMatrixBuilds: 1,
distanceEvaluations: pointMicrophonePairs,
avoidedDistanceEvaluations: 0,
stftWorkspaceAllocations: 1,
stftWorkspaceUses: 0,
avoidedStftWorkspaceAllocations: 0,
correlationWorkspaceAllocations: 1,
correlationWorkspaceUses: 0,
avoidedCorrelationWorkspaceAllocations: 0,
stftTransforms: 0,
inverseFftTransforms: 0,
crossSpectrumOperations: 0,
scanLookups: 0,
},
...geometry,
};
return plan;
}
function assertCompatibleAnalysisPlan(plan, options) {
if (plan?.kind !== GCC_PHAT_ANALYSIS_PLAN_KIND) {
throw new TypeError(
"analysisPlan must be created by createGccPhatAnalysisPlan().",
);
}
if (
plan.sampleRate !== options.sampleRate ||
plan.arrayDefinition !== options.arrayDefinition ||
plan.scene !== options.scene ||
plan.experiment !== options.experiment
) {
throw new Error(
"analysisPlan must be used with the exact configuration objects that created it.",
);
}
}
function analysisCacheSummary(plan) {
const statistics = plan.statistics;
return {
analysisAttempts: statistics.analysisAttempts,
completedAnalyses: statistics.completedAnalyses,
distanceMatrixBuilds: statistics.distanceMatrixBuilds,
distanceEvaluations: statistics.distanceEvaluations,
avoidedDistanceEvaluations: statistics.avoidedDistanceEvaluations,
stftWorkspaceAllocations: statistics.stftWorkspaceAllocations,
stftWorkspaceUses: statistics.stftWorkspaceUses,
avoidedStftWorkspaceAllocations: statistics.avoidedStftWorkspaceAllocations,
correlationWorkspaceAllocations: statistics.correlationWorkspaceAllocations,
correlationWorkspaceUses: statistics.correlationWorkspaceUses,
avoidedCorrelationWorkspaceAllocations:
statistics.avoidedCorrelationWorkspaceAllocations,
stftTransforms: statistics.stftTransforms,
inverseFftTransforms: statistics.inverseFftTransforms,
crossSpectrumOperations: statistics.crossSpectrumOperations,
scanLookups: statistics.scanLookups,
retainedBytes: plan.retainedBytes,
maximumPlanBytes: plan.maximumPlanBytes,
};
}
function circularLinearSample(values, lagSamples) {
const length = values.length;
const wrapped = ((lagSamples % length) + length) % length;
const firstIndex = Math.floor(wrapped);
const fraction = wrapped - firstIndex;
const secondIndex = (firstIndex + 1) % length;
return values[firstIndex] * (1 - fraction) + values[secondIndex] * fraction;
}
function fillBandPairCorrelation({
correlationReal,
correlationImaginary,
bins,
stft,
microphoneIndex,
referenceIndex,
phasesByBin,
phatFloorRatio,
}) {
correlationReal.fill(0);
correlationImaginary.fill(0);
const microphoneCount = stft.microphoneCount;
let maximumMagnitude = 0;
for (const bin of bins) {
const spectrum = stft.spectra.get(bin);
for (let frameIndex = 0; frameIndex < stft.frameCount; frameIndex += 1) {
const offset = frameIndex * microphoneCount;
const microphoneReal = spectrum.real[offset + microphoneIndex];
const microphoneImaginary = spectrum.imaginary[offset + microphoneIndex];
const referenceReal = spectrum.real[offset + referenceIndex];
const referenceImaginary = spectrum.imaginary[offset + referenceIndex];
const crossReal =
microphoneReal * referenceReal + microphoneImaginary * referenceImaginary;
const crossImaginary =
microphoneImaginary * referenceReal - microphoneReal * referenceImaginary;
maximumMagnitude = Math.max(
maximumMagnitude,
Math.hypot(crossReal, crossImaginary),
);
}
}
const magnitudeFloor = maximumMagnitude * phatFloorRatio;
if (!(maximumMagnitude > 0)) {
fftInPlace(correlationReal, correlationImaginary, true);
return;
}
for (const bin of bins) {
const spectrum = stft.spectra.get(bin);
const phases = phasesByBin.get(bin);
const correctionPhase = phases[referenceIndex] - phases[microphoneIndex];
const correctionReal = Math.cos(correctionPhase);
const correctionImaginary = Math.sin(correctionPhase);
let accumulatedReal = 0;
let accumulatedImaginary = 0;
for (let frameIndex = 0; frameIndex < stft.frameCount; frameIndex += 1) {
const offset = frameIndex * microphoneCount;
const microphoneReal = spectrum.real[offset + microphoneIndex];
const microphoneImaginary = spectrum.imaginary[offset + microphoneIndex];
const referenceReal = spectrum.real[offset + referenceIndex];
const referenceImaginary = spectrum.imaginary[offset + referenceIndex];
const crossReal =
microphoneReal * referenceReal + microphoneImaginary * referenceImaginary;
const crossImaginary =
microphoneImaginary * referenceReal - microphoneReal * referenceImaginary;
const magnitude = Math.hypot(crossReal, crossImaginary);
const denominator = Math.max(magnitude, magnitudeFloor);
if (!(denominator > 0)) continue;
const normalizedReal = crossReal / denominator;
const normalizedImaginary = crossImaginary / denominator;
accumulatedReal +=
normalizedReal * correctionReal - normalizedImaginary * correctionImaginary;
accumulatedImaginary +=
normalizedReal * correctionImaginary + normalizedImaginary * correctionReal;
}
const averagedReal = accumulatedReal / stft.frameCount;
const averagedImaginary = accumulatedImaginary / stft.frameCount;
correlationReal[bin] = averagedReal;
correlationImaginary[bin] =
bin === 0 || bin === correlationReal.length / 2 ? 0 : averagedImaginary;
if (bin > 0 && bin < correlationReal.length / 2) {
const negativeBin = correlationReal.length - bin;
correlationReal[negativeBin] = averagedReal;
correlationImaginary[negativeBin] = -averagedImaginary;
}
}
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);
for (let pointIndex = 0; pointIndex < rawMap.length; pointIndex += 1) {
const shifted = rawMap[pointIndex] - minimum;
rawMap[pointIndex] = shifted * shifted;
}
}
}
async function computeGccPhatMapInternal(options, configuration, geometry, plan) {
const {
channels,
signal,
onProgress,
maximumWorkingBytes = 512 * 1024 * 1024,
maximumFftButterflies = 1_000_000_000,
pointBatchSize = 256,
stftTransformBatchSize = 128,
} = options;
requirePositiveInteger(pointBatchSize, "pointBatchSize");
requirePositiveInteger(stftTransformBatchSize, "stftTransformBatchSize");
if (!Number.isSafeInteger(maximumWorkingBytes) || maximumWorkingBytes <= 0) {
throw new RangeError("maximumWorkingBytes must be a positive safe integer.");
}
const phatFloorRatio = requirePhatFloorRatio(
options.phatFloorRatio ??
options.phatRelativeFloor ??
configuration.experiment.beamforming?.phatFloorRatio,
);
const workload = estimateWithGeometry(options, configuration, geometry);
if (workload.estimatedWorkingBytes > maximumWorkingBytes) {
throw new RangeError(
"GCC-PHAT estimated working set " +
(workload.estimatedWorkingBytes / 1024 ** 2).toFixed(1) +
" MiB exceeds maximumWorkingBytes " +
(maximumWorkingBytes / 1024 ** 2).toFixed(1) + " MiB.",
);
}
const totalFftButterflies =
workload.stftButterflyCount + workload.inverseFftButterflyCount;
if (totalFftButterflies > maximumFftButterflies) {
throw new RangeError(
"GCC-PHAT estimated FFT butterfly count " +
Math.ceil(totalFftButterflies).toLocaleString() +
" exceeds maximumFftButterflies " +
maximumFftButterflies.toLocaleString() + ".",
);
}
throwIfAborted(signal);
if (plan) {
plan.statistics.stftWorkspaceUses += 1;
plan.statistics.avoidedStftWorkspaceAllocations = Math.max(
0,
plan.statistics.stftWorkspaceUses - 1,
);
plan.statistics.correlationWorkspaceUses += 1;
plan.statistics.avoidedCorrelationWorkspaceAllocations = Math.max(
0,
plan.statistics.correlationWorkspaceUses - 1,
);
}
const stft = await extractStftBins(channels, {
fftSize: configuration.fftSize,
hopSize: configuration.hopSize,
bins: geometry.selectedBins,
workspace: plan?.stftWorkspace,
transformBatchSize: stftTransformBatchSize,
signal,
onProgress: ({ completedTransforms, totalTransforms }) =>
onProgress?.({
stage: "stft",
algorithm: "gcc-phat",
completedTransforms,
totalTransforms,
}),
});
if (plan) {
plan.statistics.stftTransforms += workload.stftTransformCount;
}
await cooperativeYield();
throwIfAborted(signal);
const phasesByBin = new Map();
for (const bin of geometry.selectedBins) {
const calibration = createBinCalibration({
arrayDefinition: configuration.arrayDefinition,
bin,
sampleRate: configuration.sampleRate,
fftSize: configuration.fftSize,
compensateFrequencyResponse:
configuration.experiment.beamforming?.compensateFrequencyResponse !== false,
maxCompensationDb:
configuration.experiment.beamforming?.maxCompensationDb,
includeAmplitude: false,
});
phasesByBin.set(bin, calibration.phases);
}
const correlationReal =
plan?.correlationReal ?? new Float64Array(configuration.fftSize);
const correlationImaginary =
plan?.correlationImaginary ?? new Float64Array(configuration.fftSize);
const rawMaps = geometry.bandBins.map(() => new Float32Array(configuration.pointCount));
const totalPairs = geometry.pairCount * geometry.bandBins.length;
let completedPairs = 0;
for (let bandIndex = 0; bandIndex < geometry.bandBins.length; bandIndex += 1) {
const bins = geometry.bandBins[bandIndex];
const rawMap = rawMaps[bandIndex];
for (const microphoneIndex of geometry.pairMicrophoneIndexes) {
throwIfAborted(signal);
fillBandPairCorrelation({
correlationReal,
correlationImaginary,
bins,
stft,
microphoneIndex,
referenceIndex: geometry.reference.index,
phasesByBin,
phatFloorRatio,
});
if (plan) {
plan.statistics.inverseFftTransforms += 1;
plan.statistics.crossSpectrumOperations +=
bins.length * stft.frameCount * 2;
}
for (let pointIndex = 0; pointIndex < configuration.pointCount; pointIndex += 1) {
const distanceOffset = pointIndex * geometry.microphoneCount;
const predictedLagSamples =
(
geometry.distances[distanceOffset + microphoneIndex] -
geometry.distances[distanceOffset + geometry.reference.index]
) *
configuration.sampleRate / configuration.speedOfSound;
rawMap[pointIndex] += circularLinearSample(
correlationReal,
predictedLagSamples,
);
if (
(pointIndex + 1) % pointBatchSize === 0 &&
pointIndex + 1 < configuration.pointCount
) {
await cooperativeYield();
throwIfAborted(signal);
}
}
if (plan) plan.statistics.scanLookups += configuration.pointCount;
completedPairs += 1;
onProgress?.({
stage: "localization",
algorithm: "gcc-phat",
completedPairs,
totalPairs,
});
if (completedPairs < totalPairs) await cooperativeYield();
}
}
throwIfAborted(signal);
shiftAndSquareScores(rawMaps);
const bands = finalizeDasBands(
rawMaps,
workload,
configuration.experiment,
"score",
);
return {
backend: "cpu",
algorithm: "gcc-phat",
frameCount: workload.frameCount,
microphoneCount: workload.microphoneCount,
pointCount: workload.pointCount,
referenceMicrophoneId: geometry.reference.id,
referenceMicrophoneIndex: geometry.reference.index,
pairCount: geometry.pairCount,
phatFloorRatio,
maximumLagSamples: geometry.maximumLagSamples,
workload,
bands,
...(plan ? { analysisCache: analysisCacheSummary(plan) } : {}),
};
}
/**
* Build band-limited reference-pair GCC-PHAT maps on the CPU.
*
* For each pair and band, corrected PHAT cross spectra are averaged over STFT
* frames, transformed once to circular correlation, and sampled at the
* near-field geometric delay of each scan point.
*/
export async function computeGccPhatMap(options) {
if (!options || typeof options !== "object") {
throw new TypeError("options must be an object.");
}
const configuration = validateConfiguration(options);
const plan = options.analysisPlan;
if (!plan) {
const geometry = createGeometry(configuration);
return computeGccPhatMapInternal(options, configuration, geometry, undefined);
}
assertCompatibleAnalysisPlan(plan, options);
if (plan.busy) {
throw new Error("analysisPlan is already in use by another GCC-PHAT analysis.");
}
plan.busy = true;
plan.statistics.analysisAttempts += 1;
if (plan.statistics.analysisAttempts > 1) {
plan.statistics.avoidedDistanceEvaluations +=
plan.pointCount * plan.microphoneCount;
}
try {
const result = await computeGccPhatMapInternal(
options,
configuration,
plan,
plan,
);
plan.statistics.completedAnalyses += 1;
result.analysisCache = analysisCacheSummary(plan);
return result;
} finally {
plan.busy = false;
}
}