Preserve shared RNG state when copying Perlin and Simplex noise (#195)

Preserve shared random streams when copying ordinary noise

Author: antonsoo

CHANGELOG.md

@@ -8,6 +8,7 @@ This project adheres to [Semantic Versioning](https://semver.org/) since version
 
 ### Fixed
 
+- Copying or pickling Perlin and Simplex noise no longer advances a shared random generator while preparing an unused wavelet tile.
 - `tcod.image.Image.rotate90` updates the width and height of rectangular images, keeping NumPy array conversions consistent with the rotated pixels.
 - Adding a root to an already resolved `tcod.path.Pathfinder` resets its predecessor only when its value improves the current distance. This prevents cyclic paths while preserving routes to cheaper roots.
 - Lazy pathfinder queries reconsider previously visited goals after adding a root or lowering a root's distance.

tcod/noise.py

@@ -357,9 +357,18 @@ def __getstate__(self) -> dict[str, Any]:
         if self.dimensions < 4 and self.noise_c.waveletTileData == ffi.NULL:  # noqa: PLR2004
             # Trigger a side effect of wavelet, so that copies will be synced.
             saved_algo = self.algorithm
+            saved_random = self.noise_c.rand
+            wavelet_random = saved_random
+            if saved_algo != tcod.constants.NOISE_WAVELET:
+                # Preparing an unused algorithm must not advance a shared RNG.
+                wavelet_random = ffi.gc(lib.TCOD_random_save(saved_random), lib.TCOD_random_delete)
+            self.noise_c.rand = wavelet_random
             self.algorithm = tcod.constants.NOISE_WAVELET
-            self.get_point()
-            self.algorithm = saved_algo
+            try:
+                self.get_point()
+            finally:
+                self.algorithm = saved_algo
+                self.noise_c.rand = saved_random
 
         waveletTileData = None  # noqa: N806
         if self.noise_c.waveletTileData != ffi.NULL:

tests/test_noise.py

@@ -2,6 +2,7 @@
 
 import copy
 import pickle
+from collections.abc import Callable
 
 import numpy as np
 import pytest
@@ -103,3 +104,20 @@ def test_noise_copy() -> None:
 
 def test_noise_grid() -> None:
     tcod.noise.grid((2, 2), scale=2)  # Check int scale
+
+
+@pytest.mark.parametrize("algorithm", [tcod.noise.Algorithm.PERLIN, tcod.noise.Algorithm.SIMPLEX])
+@pytest.mark.parametrize("rng_algorithm", [tcod.random.MERSENNE_TWISTER, tcod.random.MULTIPLY_WITH_CARRY])
+@pytest.mark.parametrize("snapshot", [copy.copy, copy.deepcopy, lambda n: pickle.loads(pickle.dumps(n))])
+def test_noise_snapshot_preserves_shared_random(
+    algorithm: int, rng_algorithm: int, snapshot: Callable[[tcod.noise.Noise], tcod.noise.Noise]
+) -> None:
+    rng = tcod.random.Random(rng_algorithm, seed=42)
+    noise = tcod.noise.Noise(2, algorithm=algorithm, seed=rng)
+    expected = copy.deepcopy(rng)
+    noise_copy = snapshot(noise)
+    assert [rng.randint(0, 100) for _ in range(8)] == [expected.randint(0, 100) for _ in range(8)]
+    assert noise.algorithm == algorithm
+    # The lazy wavelet tile remains synchronized if this algorithm is selected later.
+    noise.algorithm = noise_copy.algorithm = tcod.noise.Algorithm.WAVELET
+    np.testing.assert_array_equal(noise.sample_ogrid(np.ogrid[:3, :4]), noise_copy.sample_ogrid(np.ogrid[:3, :4]))