feat: add comparable localization algorithms

tests/unit/evaluation.test.js

@@ -1,6 +1,7 @@
 import {
   RESULT_METRIC_KEYS,
   evaluateDasBand,
+  evaluateLocalizationBand,
   exportBandEvaluation,
   findLocalPeaks,
   measureBeamSpread,
@@ -213,6 +214,44 @@ test("beam spread가 회전된 비등방성 half-power lobe의 covariance ellips
   );
 });
 
+test("generic localization 평가는 score map의 척도와 beam spread 방식을 보존한다", () => {
+  const scan = { xMin: -1, xMax: 1, yMin: -1, yMax: 1, z: 2, columns: 3, rows: 3 };
+  const rawMap = {
+    rows: 3,
+    columns: 3,
+    scale: "score",
+    values: Float32Array.of(
+      0, 1, 0,
+      1, 4, 1,
+      0, 1, 0,
+    ),
+  };
+  const evaluation = evaluateLocalizationBand({
+    rawMap,
+    scan,
+    sources: [{ id: "center", position: [0, 0, 2] }],
+    matchToleranceM: 0,
+    truthRadiusM: 0,
+    minimumPeakDistanceM: 0,
+  });
+
+  assertEqual(evaluation.diagnostics.mapScale, "score", "score scale diagnostic");
+  assertEqual(
+    evaluation.detections[0].beamSpread.method,
+    "connected-half-maximum-score-weighted-covariance",
+    "score beam-spread method",
+  );
+  assertEqual(evaluation.sourceMatches[0].localizationErrorM, 0, "score peak localization");
+
+  const legacy = evaluateDasBand({
+    rawMap: rawMap.values,
+    scan,
+    sources: [],
+    minimumPeakDistanceM: 0,
+  });
+  assertEqual(legacy.diagnostics.mapScale, "power", "legacy DAS defaults to power");
+});
+
 test("beam spread가 1-row, 1-column, single-pixel lobe에서 유한하고 결정적이다", () => {
   const powers = Float32Array.of(5, 8, 10, 8, 5);
   const rowSpread = measureBeamSpread(
@@ -337,6 +376,6 @@ test("evaluation이 non-finite, negative, shape 오류를 입력 경계에서
       scan,
       sources: [],
     })) instanceof RangeError,
-    "non-power map rejected",
+    "display-only map scale rejected",
   );
 });