feat: compare localization algorithms in camera

apps/acoustic-camera/model.js

@@ -1,4 +1,8 @@
 import { getFrameCount, binsForBand } from "/packages/acoustics-core/stft.js";
+import {
+  DEFAULT_LOCALIZATION_ALGORITHM,
+  localizationAlgorithmDefinition,
+} from "/packages/acoustics-core/localization-algorithms.js";
 
 const RESULT_METRIC_KEYS = [
   "peakToSidelobeDb",
@@ -25,6 +29,17 @@ export function canonicalStringify(value) {
   return JSON.stringify(sortForCanonicalJson(value));
 }
 
+export function createComparisonSignature(scene, sourceExperiment) {
+  if (!scene || !sourceExperiment) return "";
+  const experiment = structuredClone(sourceExperiment);
+  experiment.arrayId = "$array";
+  if (experiment.beamforming) {
+    experiment.beamforming.algorithm = "$algorithm";
+    experiment.beamforming.backend = "$backend";
+  }
+  return canonicalStringify({ scene, experiment });
+}
+
 export async function hashSimulationInputs({ arrayDefinition, scene, experiment }) {
   const canonical = canonicalStringify({ array: arrayDefinition, experiment, scene });
   const digest = await crypto.subtle.digest("SHA-256", new TextEncoder().encode(canonical));
@@ -42,17 +57,38 @@ export function estimateExperimentWorkload(arrayDefinition, scene, experiment) {
   const bandBins = experiment.frequencyBands.map((band) =>
     binsForBand(band, scene.sampleRate, experiment.stft.fftSize),
   );
+  const bandBinSelectionCount = bandBins.reduce((total, bins) => total + bins.length, 0);
   const selectedBinCount = new Set(bandBins.flat()).size;
   const pointCount = experiment.scan.columns * experiment.scan.rows;
   const microphoneCount = arrayDefinition.microphones.length;
-  const complexMacCount = pointCount * microphoneCount * frameCount * selectedBinCount;
+  const algorithm = experiment.beamforming?.algorithm ?? DEFAULT_LOCALIZATION_ALGORITHM;
+  const algorithmDefinition = localizationAlgorithmDefinition(algorithm);
+  const referencePairCount = Math.max(0, microphoneCount - 1);
+  const stftTransformCount = frameCount * microphoneCount;
+  const dasComplexMacCount = pointCount * microphoneCount * frameCount * selectedBinCount;
+  const gccCrossSpectrumComplexOps =
+    2 * referencePairCount * frameCount * bandBinSelectionCount;
+  const gccScanScoreOps = pointCount * referencePairCount * bandBins.length;
+  const inverseFftTransformCount = referencePairCount * bandBins.length;
+  const scanOperationCount = algorithm === "gcc-phat" ? gccScanScoreOps : dasComplexMacCount;
   return {
+    algorithm,
+    algorithmLabel: algorithmDefinition?.label ?? algorithm,
+    rawScale: algorithmDefinition?.rawScale ?? "power",
     pointCount,
     microphoneCount,
     frameCount,
     selectedBinCount,
+    bandBinSelectionCount,
+    minimumBandBinCount: Math.min(...bandBins.map((bins) => bins.length)),
     bandBins,
-    complexMacCount,
+    stftTransformCount,
+    referencePairCount,
+    scanOperationCount,
+    scanOperationKind: algorithm === "gcc-phat" ? "reference-pair lookup" : "complex MAC",
+    gccCrossSpectrumComplexOps: algorithm === "gcc-phat" ? gccCrossSpectrumComplexOps : 0,
+    inverseFftTransformCount: algorithm === "gcc-phat" ? inverseFftTransformCount : 0,
+    complexMacCount: algorithm === "gcc-phat" ? 0 : dasComplexMacCount,
     scalingVs50: pointCount / 2500,
     distanceMiB: (pointCount * microphoneCount * 4) / 1024 ** 2,
   };
@@ -207,6 +243,14 @@ function environmentForResult({ arrayDefinition, experiment, run }) {
   if (adapter?.architecture) environment.gpuArchitecture = adapter.architecture;
   if (adapter?.device) environment.gpuDevice = adapter.device;
   if (run.gpu?.timingKind) environment.gpuTimingKind = run.gpu.timingKind;
+  const referenceMic =
+    run.referenceMic ??
+    run.referenceMicrophoneId ??
+    run.workload?.referenceMic ??
+    run.workload?.referenceMicrophoneId;
+  if (typeof referenceMic === "string" || Number.isFinite(referenceMic)) {
+    environment.referenceMic = referenceMic;
+  }
   return environment;
 }
 
@@ -220,6 +264,8 @@ export function createResultDocument(options) {
     inputHash,
     createdAt = new Date().toISOString(),
   } = options;
+  const algorithm = run.algorithm ?? experiment.beamforming?.algorithm ?? DEFAULT_LOCALIZATION_ALGORITHM;
+  const rawScale = localizationAlgorithmDefinition(algorithm)?.rawScale ?? "power";
   return {
     schemaVersion: "1.0.0",
     kind: "micarrsim.result",
@@ -227,6 +273,7 @@ export function createResultDocument(options) {
     arrayId: arrayDefinition.id,
     sceneId: scene.id,
     createdAt,
+    algorithm,
     backend: run.backend,
     inputHash,
     signalStats: {
@@ -246,7 +293,8 @@ export function createResultDocument(options) {
     timingMs: {
       total: run.timingMs.total,
       signalGeneration: run.timingMs.signalGeneration,
-      beamforming: run.timingMs.beamforming,
+      localization: run.timingMs.localization ?? run.timingMs.beamforming,
+      beamforming: run.timingMs.beamforming ?? run.timingMs.localization,
     },
     environment: environmentForResult({ arrayDefinition, experiment, run }),
     bands: run.bands.map((band) => {
@@ -257,7 +305,7 @@ export function createResultDocument(options) {
         rawMap: {
           rows: experiment.scan.rows,
           columns: experiment.scan.columns,
-          scale: "power",
+          scale: band.rawScale ?? rawScale,
           values: Array.from(band.rawMap),
         },
         displayMap: {
@@ -286,9 +334,11 @@ export function createHistorySummary({ arrayDefinition, scene, experiment, run,
     arrayName: arrayDefinition.name,
     sceneId: scene.id,
     experimentId: experiment.id,
+    algorithm: run.algorithm ?? experiment.beamforming?.algorithm ?? DEFAULT_LOCALIZATION_ALGORITHM,
     backend: run.backend,
     pointCount: experiment.scan.rows * experiment.scan.columns,
     totalMs: run.timingMs.total,
+    localizationMs: run.timingMs.localization ?? run.timingMs.beamforming,
     localizationErrorM: firstMatchedPeak?.localizationErrorM ?? null,
     peakToSidelobeDb: evaluation?.metrics?.peakToSidelobeDb ?? null,
     inputHash,