test(photos): batch apply approved mask after Calculate (#62)

Prove frozen calibration mask reuse, per-photo errors, inventory PNG results, calibration-only measures, draft persistence, and no Mask re-prompting for batch siblings.

frontend/src/capture/session.batchApply.test.ts

@@ -0,0 +1,497 @@
+import assert from 'node:assert/strict';
+import { readFileSync } from 'node:fs';
+import { dirname, join } from 'node:path';
+import { fileURLToPath } from 'node:url';
+import { test, beforeEach, afterEach } from 'node:test';
+import { get } from 'svelte/store';
+import type { Draft, Mask, MaskParams, Source, WorkerIn, WorkerOut } from './capture.types';
+import { createCaptureSession, type DraftStore } from './session';
+
+const here = dirname(fileURLToPath(import.meta.url));
+
+function tinyJpeg(label: string): File {
+  const bytes = new Uint8Array([0xff, 0xd8, 0xff, 0xe0, label.charCodeAt(0) & 0xff]);
+  return new File([bytes], `${label}.jpg`, { type: 'image/jpeg' });
+}
+
+function memStore(): DraftStore & { peek: () => Draft | null } {
+  let mem: Draft | null = null;
+  return {
+    loadDraft: async () => mem,
+    saveDraft: async (d) => {
+      mem = d;
+    },
+    clearDraft: async () => {
+      mem = null;
+    },
+    peek: () => mem,
+  };
+}
+
+let store: ReturnType<typeof memStore>;
+
+beforeEach(() => {
+  store = memStore();
+});
+
+/** Controllable FakeWorker for #62 batch-apply paths. */
+type MaskBehavior = {
+  w: number;
+  h: number;
+  /** slabPx; 0 ⇒ empty mask */
+  slabPx: number;
+  slabBounds?: { x: number; y: number; w: number; h: number };
+};
+
+class FakeMaskWorker {
+  onmessage: ((ev: MessageEvent<WorkerOut>) => void) | null = null;
+  static inits: Blob[] = [];
+  static maskCalls: { sheet: string; sensitivity: number; blob: Blob | null }[] = [];
+  static lastInitBlob: Blob | null = null;
+  /** Per-init blob → behavior. Default: full mask at LARGE dims (above PNG floor). */
+  static behaviorFor: (blob: Blob) => MaskBehavior = () => ({
+    w: 1000,
+    h: 900,
+    slabPx: 1000 * 900,
+    slabBounds: { x: 0, y: 0, w: 1000, h: 900 },
+  });
+
+  constructor(_url: URL | string, _opts?: WorkerOptions) {}
+
+  postMessage(msg: WorkerIn) {
+    if (msg.kind === 'init') {
+      FakeMaskWorker.inits.push(msg.blob);
+      FakeMaskWorker.lastInitBlob = msg.blob;
+      const id = msg.id;
+      const b = FakeMaskWorker.behaviorFor(msg.blob);
+      queueMicrotask(() => {
+        this.onmessage?.({ data: { id, kind: 'decoded', w: b.w, h: b.h } } as MessageEvent<WorkerOut>);
+      });
+      return;
+    }
+    if (msg.kind === 'mask') {
+      const id = msg.id;
+      const blob = FakeMaskWorker.lastInitBlob;
+      FakeMaskWorker.maskCalls.push({
+        sheet: msg.sheet,
+        sensitivity: msg.sensitivity,
+        blob,
+      });
+      const b = blob ? FakeMaskWorker.behaviorFor(blob) : { w: 40, h: 20, slabPx: 0 };
+      const bitset = new Uint8Array(Math.max(1, b.w * b.h)).fill(b.slabPx > 0 ? 1 : 0);
+      const bbox = {
+        corners: [
+          [b.w, 0],
+          [b.w, b.h],
+          [0, b.h],
+          [0, 0],
+        ] as [number, number][],
+        longSidePx: b.w,
+        angleDeg: 0,
+      };
+      const slabBounds = b.slabBounds ?? { x: 0, y: 0, w: b.w, h: b.h };
+      queueMicrotask(() => {
+        this.onmessage?.({
+          data: {
+            id,
+            kind: 'ready',
+            slabPx: b.slabPx,
+            bitset,
+            bbox,
+            slabBounds,
+          },
+        } as MessageEvent<WorkerOut>);
+      });
+      return;
+    }
+  }
+
+  terminate() {}
+}
+
+const RealWorker = globalThis.Worker;
+const RealCreateImageBitmap = globalThis.createImageBitmap;
+
+function installFakes() {
+  FakeMaskWorker.inits = [];
+  FakeMaskWorker.maskCalls = [];
+  FakeMaskWorker.lastInitBlob = null;
+  FakeMaskWorker.behaviorFor = () => ({
+    w: 1000,
+    h: 900,
+    slabPx: 1000 * 900,
+    slabBounds: { x: 0, y: 0, w: 1000, h: 900 },
+  });
+  (globalThis as unknown as { Worker: typeof FakeMaskWorker }).Worker = FakeMaskWorker;
+  (globalThis as unknown as { createImageBitmap: typeof createImageBitmap }).createImageBitmap =
+    async (blob: ImageBitmapSource) => {
+      const b = blob instanceof Blob ? FakeMaskWorker.behaviorFor(blob) : { w: 1000, h: 900 };
+      return {
+        width: b.w,
+        height: b.h,
+        close() {},
+      } as ImageBitmap;
+    };
+}
+
+function restoreGlobals() {
+  if (RealWorker === undefined) {
+    delete (globalThis as unknown as { Worker?: unknown }).Worker;
+  } else {
+    globalThis.Worker = RealWorker;
+  }
+  if (RealCreateImageBitmap === undefined) {
+    delete (globalThis as unknown as { createImageBitmap?: unknown }).createImageBitmap;
+  } else {
+    globalThis.createImageBitmap = RealCreateImageBitmap;
+  }
+}
+
+afterEach(() => {
+  restoreGlobals();
+});
+
+async function settleOverlay(
+  s: ReturnType<typeof createCaptureSession>,
+  ms = 800,
+): Promise<Mask> {
+  const start = Date.now();
+  while (Date.now() - start < ms) {
+    const cap = get(s.capture);
+    if (cap.k === 'mask' && cap.overlay && cap.overlay.slabPx > 0) return cap.overlay;
+    await new Promise((r) => setTimeout(r, 5));
+  }
+  throw new Error('mask overlay never settled');
+}
+
+async function driveToMeasure(
+  s: ReturnType<typeof createCaptureSession>,
+  photos: File[],
+  calIndex: number,
+  maskParams: Partial<MaskParams> = { sheet: 'green', sensitivity: 50 },
+) {
+  for (const p of photos) await s.addToBatch(p);
+  s.continueBatch();
+  s.pickCalibration(calIndex);
+  if (maskParams.sheet) s.setSheet(maskParams.sheet);
+  if (typeof maskParams.sensitivity === 'number') s.setSensitivity(maskParams.sensitivity);
+  // setSheet already runs a pass; if only sensitivity, force via setSheet after
+  if (!maskParams.sheet) s.setSheet('auto');
+  await settleOverlay(s);
+  s.approveMask();
+  s.approveAxis();
+  s.setLength(320); // 40 in
+  s.setThickness(16); // 2 in
+}
+
+type BatchApplySlot =
+  | null
+  | { status: 'ok'; inventoryPng: Blob }
+  | { status: 'error'; message: string };
+
+function batchApplyOf(cap: ReturnType<typeof get<ReturnType<typeof createCaptureSession>['capture']>>): BatchApplySlot[] | undefined {
+  if (cap.k !== 'measure') return undefined;
+  return (cap as { batchApply?: BatchApplySlot[] }).batchApply;
+}
+
+// --- #62: apply approved mask + crop to non-calibration batch photos after Calculate ---
+
+test('#62: Calculate applies frozen mask params to every non-calibration batch photo', async () => {
+  installFakes();
+  const encodeCalls: { widthPx: number; heightPx: number; sheet: string; sensitivity: number }[] = [];
+  const s = createCaptureSession({
+    draft: store,
+    encodeInventory: async (input) => {
+      encodeCalls.push({
+        widthPx: input.source.widthPx,
+        heightPx: input.source.heightPx,
+        sheet: (input.mask as Mask).params?.sheet ?? '?',
+        sensitivity: (input.mask as Mask).params?.sensitivity ?? -1,
+      });
+      // Distinctive PNG blob so tests cannot confuse with source JPEG thumbs
+      return {
+        blob: new Blob([`png-${input.source.widthPx}x${input.source.heightPx}`], { type: 'image/png' }),
+        sourceBelowFloor: false,
+      };
+    },
+  } as Parameters<typeof createCaptureSession>[0]);
+
+  const a = tinyJpeg('a');
+  const b = tinyJpeg('b'); // calibration
+  const c = tinyJpeg('c');
+  await driveToMeasure(s, [a, b, c], 1, { sheet: 'black', sensitivity: 72 });
+  await s.calculate();
+
+  const cap = get(s.capture);
+  assert.equal(cap.k, 'measure', 'must stay on Measure — do not reopen Mask');
+  const apply = batchApplyOf(cap);
+  assert.ok(Array.isArray(apply), 'measure.batchApply must exist after Calculate');
+  assert.equal(apply!.length, 3, 'one slot per batch photo');
+  assert.equal(apply![1], null, 'calibration index is null (uses results.inventoryPng)');
+
+  assert.ok(apply![0] && apply![0].status === 'ok', 'batch[0] applied ok');
+  assert.ok(apply![2] && apply![2].status === 'ok', 'batch[2] applied ok');
+  if (apply![0]?.status === 'ok') {
+    assert.equal(apply![0].inventoryPng.type, 'image/png');
+    assert.notEqual(apply![0].inventoryPng, a, 'must not proxy source thumb as inventory PNG');
+  }
+  if (apply![2]?.status === 'ok') {
+    assert.equal(apply![2].inventoryPng.type, 'image/png');
+    assert.notEqual(apply![2].inventoryPng, c);
+  }
+
+  // Frozen params: every sibling mask call used calibration sheet/sensitivity
+  const siblingBlobs = new Set([a, c]);
+  const siblingMasks = FakeMaskWorker.maskCalls.filter((m) => m.blob && siblingBlobs.has(m.blob as File));
+  assert.ok(siblingMasks.length >= 2, 'mask worker must run on non-calibration photos');
+  for (const m of siblingMasks) {
+    assert.equal(m.sheet, 'black', 'reuse approved sheet');
+    assert.equal(m.sensitivity, 72, 'reuse approved sensitivity');
+  }
+
+  s.dispose();
+});
+
+test('#62: empty mask on one sibling → per-photo error; others still proceed', async () => {
+  installFakes();
+  const a = tinyJpeg('a'); // will empty-mask
+  const b = tinyJpeg('b'); // cal
+  const c = tinyJpeg('c'); // ok
+
+  FakeMaskWorker.behaviorFor = (blob) => {
+    if (blob === a) {
+      return { w: 1000, h: 900, slabPx: 0, slabBounds: { x: 0, y: 0, w: 0, h: 0 } };
+    }
+    return { w: 1000, h: 900, slabPx: 1000 * 900, slabBounds: { x: 0, y: 0, w: 1000, h: 900 } };
+  };
+
+  const s = createCaptureSession({
+    draft: store,
+    encodeInventory: async () => ({
+      blob: new Blob(['ok-png'], { type: 'image/png' }),
+      sourceBelowFloor: false,
+    }),
+  } as Parameters<typeof createCaptureSession>[0]);
+
+  await driveToMeasure(s, [a, b, c], 1, { sheet: 'green' });
+  await s.calculate();
+
+  const apply = batchApplyOf(get(s.capture));
+  assert.ok(apply);
+  assert.equal(apply![1], null);
+  assert.ok(apply![0] && apply![0].status === 'error', 'empty mask → error');
+  if (apply![0]?.status === 'error') {
+    assert.match(apply![0].message, /empty|mask/i, 'clear per-photo empty-mask error');
+  }
+  assert.ok(apply![2] && apply![2].status === 'ok', 'other photos still proceed');
+  s.dispose();
+});
+
+test('#62: below PNG size floor on one sibling → per-photo error; others proceed', async () => {
+  installFakes();
+  const a = tinyJpeg('a'); // ok
+  const b = tinyJpeg('b'); // cal
+  const c = tinyJpeg('c'); // below floor
+
+  FakeMaskWorker.behaviorFor = (blob) => {
+    if (blob === c) {
+      return { w: 400, h: 300, slabPx: 400 * 300, slabBounds: { x: 0, y: 0, w: 400, h: 300 } };
+    }
+    return { w: 1000, h: 900, slabPx: 1000 * 900, slabBounds: { x: 0, y: 0, w: 1000, h: 900 } };
+  };
+
+  const s = createCaptureSession({
+    draft: store,
+    encodeInventory: async (input) => {
+      const below = Math.min(input.mask.slabBounds.w, input.mask.slabBounds.h) < 800;
+      return {
+        blob: new Blob([below ? 'tiny' : 'ok'], { type: 'image/png' }),
+        sourceBelowFloor: below,
+      };
+    },
+  } as Parameters<typeof createCaptureSession>[0]);
+
+  await driveToMeasure(s, [a, b, c], 1, { sheet: 'auto' });
+  await s.calculate();
+
+  const apply = batchApplyOf(get(s.capture));
+  assert.ok(apply);
+  assert.ok(apply![0] && apply![0].status === 'ok', 'above-floor sibling ok');
+  assert.ok(apply![2] && apply![2].status === 'error', 'below-floor → error');
+  if (apply![2]?.status === 'error') {
+    assert.match(apply![2].message, /floor|small|800|size/i, 'clear per-photo size-floor error');
+  }
+  s.dispose();
+});
+
+test('#62: scale/widths/sqft/bdft stay on calibration results only (siblings are visual)', async () => {
+  installFakes();
+  const s = createCaptureSession({
+    draft: store,
+    encodeInventory: async () => ({
+      blob: new Blob(['png'], { type: 'image/png' }),
+      sourceBelowFloor: false,
+    }),
+  } as Parameters<typeof createCaptureSession>[0]);
+
+  const a = tinyJpeg('a');
+  const b = tinyJpeg('b');
+  await driveToMeasure(s, [a, b], 1, { sheet: 'green' });
+  await s.calculate();
+
+  const cap = get(s.capture);
+  assert.equal(cap.k, 'measure');
+  if (cap.k === 'measure') {
+    assert.ok(cap.results);
+    assert.equal(typeof cap.results!.scale, 'number');
+    assert.ok(cap.results!.scale > 0);
+    assert.equal(typeof cap.results!.sqft, 'number');
+    assert.equal(typeof cap.results!.bdft, 'number');
+    assert.ok(cap.results!.widths);
+    // batchApply ok slots must NOT carry measure fields
+    const apply = (cap as { batchApply?: BatchApplySlot[] }).batchApply;
+    assert.ok(apply);
+    const slot = apply![0];
+    assert.ok(slot && slot.status === 'ok');
+    if (slot && slot.status === 'ok') {
+      assert.equal(
+        'scale' in slot,
+        false,
+        'non-cal apply must not attach scale',
+      );
+      assert.equal('sqft' in slot, false);
+      assert.equal('bdft' in slot, false);
+      assert.equal('widths' in slot, false);
+    }
+  }
+  s.dispose();
+});
+
+test('#62: draft persists batchApply after Calculate (for #64 UI later)', async () => {
+  installFakes();
+  const s = createCaptureSession({
+    draft: store,
+    encodeInventory: async () => ({
+      blob: new Blob(['draft-png'], { type: 'image/png' }),
+      sourceBelowFloor: false,
+    }),
+  } as Parameters<typeof createCaptureSession>[0]);
+
+  const a = tinyJpeg('a');
+  const b = tinyJpeg('b');
+  const c = tinyJpeg('c');
+  await driveToMeasure(s, [a, b, c], 0, { sheet: 'black' }); // cal = first
+  await s.calculate();
+  await new Promise((r) => setTimeout(r, 30));
+
+  const d = store.peek();
+  assert.ok(d);
+  assert.equal(d!.stage, 'measure');
+  assert.ok(Array.isArray(d!.batchApply), 'draft.batchApply must be persisted');
+  assert.equal(d!.batchApply!.length, 3);
+  assert.equal(d!.batchApply![0], null, 'calibration slot null on draft');
+  assert.ok(d!.batchApply![1] && (d!.batchApply![1] as { status: string }).status === 'ok');
+  assert.ok(d!.batchApply![2] && (d!.batchApply![2] as { status: string }).status === 'ok');
+  s.dispose();
+});
+
+test('#62: single-photo batch Calculate leaves batchApply=[null] (no sibling Mask)', async () => {
+  installFakes();
+  const s = createCaptureSession({
+    draft: store,
+    encodeInventory: async () => ({
+      blob: new Blob(['only'], { type: 'image/png' }),
+      sourceBelowFloor: false,
+    }),
+  } as Parameters<typeof createCaptureSession>[0]);
+
+  const only = tinyJpeg('only');
+  await driveToMeasure(s, [only], 0, { sheet: 'auto' });
+  const initsBefore = FakeMaskWorker.inits.length;
+  await s.calculate();
+
+  const apply = batchApplyOf(get(s.capture));
+  assert.ok(apply);
+  assert.deepEqual(apply, [null]);
+
+  // No extra mask inits for non-existent siblings after Calculate
+  const siblingInits = FakeMaskWorker.inits.slice(initsBefore).filter((blob) => blob !== only);
+  assert.equal(siblingInits.length, 0, 'must not invent Mask work for absent siblings');
+  s.dispose();
+});
+
+test('#62: Calculate does not re-enter Mask / does not open Mask controls for siblings', async () => {
+  installFakes();
+  const s = createCaptureSession({
+    draft: store,
+    encodeInventory: async () => ({
+      blob: new Blob(['x'], { type: 'image/png' }),
+      sourceBelowFloor: false,
+    }),
+  } as Parameters<typeof createCaptureSession>[0]);
+
+  await driveToMeasure(s, [tinyJpeg('a'), tinyJpeg('b')], 0, { sheet: 'green' });
+  await s.calculate();
+  assert.equal(get(s.capture).k, 'measure');
+
+  // Session source must never loop enterMaskOnSource over batch after Calculate
+  const sessionSrc = readFileSync(join(here, 'session.ts'), 'utf8');
+  assert.ok(
+    /batchApply|applyBatch|apply.*non-?calibrat/i.test(sessionSrc),
+    'session must implement batch apply after Calculate (#62)',
+  );
+  // Dishonest proxy: must not set k:'mask' inside calculate for each photo
+  const calcBody = sessionSrc.match(/async calculate\(\)[\s\S]*?(?=\n    [a-zA-Z]+\(|\n  \})/);
+  assert.ok(calcBody, 'calculate() must exist');
+  assert.ok(
+    !/set\(\s*\{\s*k:\s*'mask'/.test(calcBody![0]),
+    'calculate must not reopen Mask state for siblings',
+  );
+
+  const app = readFileSync(join(here, '..', 'App.svelte'), 'utf8');
+  assert.ok(
+    !/\{\s*#each\s+[^}]*batchApply[^}]*\}[\s\S]*MaskPanel/i.test(app) &&
+      !/\{\s*#each\s+[^}]*photos[^}]*\}[\s\S]*MaskPanel/i.test(app),
+    'App must not #each photos into MaskPanel',
+  );
+  s.dispose();
+});
+
+test('#62: resume restores batchApply alongside calibration results', async () => {
+  installFakes();
+  const s1 = createCaptureSession({
+    draft: store,
+    encodeInventory: async () => ({
+      blob: new Blob(['resume-png'], { type: 'image/png' }),
+      sourceBelowFloor: false,
+    }),
+  } as Parameters<typeof createCaptureSession>[0]);
+
+  const a = tinyJpeg('a');
+  const b = tinyJpeg('b');
+  await driveToMeasure(s1, [a, b], 1, { sheet: 'green' });
+  await s1.calculate();
+  await new Promise((r) => setTimeout(r, 30));
+  s1.dispose();
+
+  FakeMaskWorker.inits = [];
+  const s2 = createCaptureSession({ draft: store } as Parameters<typeof createCaptureSession>[0]);
+  await s2.resumeProbe();
+  s2.continueDraft();
+  const start = Date.now();
+  let cap = get(s2.capture);
+  while (cap.k !== 'measure' && Date.now() - start < 1500) {
+    await new Promise((r) => setTimeout(r, 10));
+    cap = get(s2.capture);
+  }
+  assert.equal(cap.k, 'measure');
+  const apply = batchApplyOf(cap);
+  assert.ok(apply, 'restored measure must include batchApply');
+  assert.equal(apply!.length, 2);
+  assert.equal(apply![1], null);
+  assert.ok(apply![0] && apply![0].status === 'ok');
+  if (apply![0]?.status === 'ok') {
+    assert.equal(apply![0].inventoryPng.type, 'image/png');
+  }
+  s2.dispose();
+});