GeezerVison

Copying or pickling Perlin/Simplex noise advances a caller-supplied random generator, even though neither algorithm needs new random draws to sample its existing field. Serialization initializes an unused wavelet tile through that same generator. A later dungeon generation step can therefore change just because a checkpoint was saved.

import copy
import pickle
import tcod

rng = tcod.random.Random(seed=42)
noise = tcod.noise.Noise(2, seed=rng)
reference = copy.deepcopy(rng)
pickle.dumps(noise)
print([rng.randint(0, 100) for _ in range(5)])
print([reference.randint(0, 100) for _ in range(5)])
# Before: [57, 45, 80, 84, 37] vs [7, 20, 41, 34, 13]
# After: both [7, 20, 41, 34, 13]

Prepare the unused wavelet tile with a copy of the native generator for Perlin/Simplex snapshots. Retain tile synchronization if a copied instance later switches to wavelet noise, and restore the original algorithm/RNG pointer in finally. Direct wavelet serialization keeps its existing behavior.

Twelve regressions cover both native RNG algorithms and shallow copy, deep copy and pickle; all fail before and pass after, including the subsequent wavelet switch. Across 96 native terrain/BSP continuations, all 32 formerly changed dungeon maps now match an uninterrupted run. The 64 already-working records remain exactly unchanged, including terrain values, random draws and partitions.

Full native no-window suite: 321 passed, 95 rendering skips, with SDL dummy drivers and the pinned libtcod fixtures. Mypy and applicable project hooks pass. Linux/Python 3.12; graphical windows and other platforms were not tested.