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0ce9643 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 | import type { ActivationData, AnomalyData, CircuitData } from '../types/scan';
import type { CompareData, LayerDiff } from '../types/compare';
import type { ScanMode } from '../types/model';
export interface ScanDataPair {
activationData: ActivationData | null;
circuitData: CircuitData | null;
anomalyData: AnomalyData | null;
}
/**
* Compute layer-wise diffs between two scan datasets.
* Works for both multi-prompt (same model) and cross-model comparisons.
*/
export function computeLayerDiffs(
mode: ScanMode,
labelA: string,
labelB: string,
tokensA: string[],
tokensB: string[],
dataA: ScanDataPair,
dataB: ScanDataPair,
): CompareData | null {
if (mode === 'fMRI' && dataA.activationData && dataB.activationData) {
const a = dataA.activationData;
const b = dataB.activationData;
const diffs: LayerDiff[] = [];
for (let i = 0; i < Math.min(a.layers.length, b.layers.length); i++) {
const aActs = a.layers[i].activations;
const bActs = b.layers[i].activations;
const avgA = aActs.reduce((s, v) => s + v, 0) / Math.max(aActs.length, 1);
const avgB = bActs.reduce((s, v) => s + v, 0) / Math.max(bActs.length, 1);
diffs.push({ layer_id: a.layers[i].layer_id, delta: avgB - avgA });
}
const maxAbs = Math.max(...diffs.map((d) => Math.abs(d.delta)), 0.001);
return { promptA: labelA, promptB: labelB, tokens_a: tokensA, tokens_b: tokensB, layerDiffs: diffs, maxAbsDelta: maxAbs };
}
if (mode === 'DTI' && dataA.circuitData && dataB.circuitData) {
const a = dataA.circuitData;
const b = dataB.circuitData;
const aMap = new Map(a.components.map((c) => [c.layer_id, c.importance]));
const diffs: LayerDiff[] = b.components.map((c) => ({
layer_id: c.layer_id,
delta: c.importance - (aMap.get(c.layer_id) ?? 0),
}));
const maxAbs = Math.max(...diffs.map((d) => Math.abs(d.delta)), 0.001);
return { promptA: labelA, promptB: labelB, tokens_a: tokensA, tokens_b: tokensB, layerDiffs: diffs, maxAbsDelta: maxAbs };
}
if (mode === 'FLAIR' && dataA.anomalyData && dataB.anomalyData) {
const a = dataA.anomalyData;
const b = dataB.anomalyData;
const diffs: LayerDiff[] = [];
for (let i = 0; i < Math.min(a.layers.length, b.layers.length); i++) {
const aScores = a.layers[i].anomaly_scores;
const bScores = b.layers[i].anomaly_scores;
const avgA = aScores.reduce((s, v) => s + v, 0) / Math.max(aScores.length, 1);
const avgB = bScores.reduce((s, v) => s + v, 0) / Math.max(bScores.length, 1);
diffs.push({ layer_id: a.layers[i].layer_id, delta: avgB - avgA });
}
const maxAbs = Math.max(...diffs.map((d) => Math.abs(d.delta)), 0.001);
return { promptA: labelA, promptB: labelB, tokens_a: tokensA, tokens_b: tokensB, layerDiffs: diffs, maxAbsDelta: maxAbs };
}
return null;
}
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