Add rigorous SynthID research and evaluation harness

tests/test_synthid_tile_attack.py

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+from __future__ import annotations
+
+import sys
+from pathlib import Path
+
+import numpy as np
+import pytest
+
+sys.path.insert(0, str(Path(__file__).resolve().parent.parent / "scripts"))
+
+import synthid_tile_attack as attack
+
+
+def test_modulo_folding_recovers_repeated_high_frequency_tile() -> None:
+    tile = np.fromfunction(lambda y, x, channel: ((x + y + channel) % 2) * 2.0 - 1.0, (8, 16, 3))
+    pixels = 100.0 + np.tile(tile, (8, 4, 1))
+
+    estimated = attack.fold_residual_template(
+        pixels,
+        tile_height=8,
+        tile_width=16,
+        denoise_sigma=1.0,
+    )
+
+    correlation = np.corrcoef(tile.ravel(), estimated.ravel())[0, 1]
+    assert correlation > 0.99
+
+
+def test_subtraction_reduces_repeated_tile_energy() -> None:
+    tile = np.fromfunction(lambda y, x, channel: ((x + y + channel) % 2) * 2.0 - 1.0, (8, 16, 3))
+    pixels = np.clip(np.rint(100.0 + 4.0 * np.tile(tile, (8, 4, 1))), 0, 255).astype(np.uint8)
+    template = attack.fold_residual_template(
+        pixels,
+        tile_height=8,
+        tile_width=16,
+        denoise_sigma=1.0,
+    )
+
+    result = attack.subtract_tiled_template(pixels, template, strength=1.0)
+    before = np.std(pixels.astype(np.float64) - np.mean(pixels, axis=(0, 1), keepdims=True))
+    after = np.std(result.astype(np.float64) - np.mean(result, axis=(0, 1), keepdims=True))
+
+    assert after < before
+
+
+def test_folding_rejects_nondivisible_geometry() -> None:
+    pixels = np.zeros((63, 64, 3), dtype=np.uint8)
+
+    with pytest.raises(ValueError, match="divisible"):
+        attack.fold_residual_template(
+            pixels,
+            tile_height=8,
+            tile_width=16,
+            denoise_sigma=1.0,
+        )