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Migrate current callers to level-indexed refinement API

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Frank14f committed 2026-10-28 09:53:20 +08:00
1 parent b4eacf7526
commit 55067652e4
38 files changed
+210 -199
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README.md
+7 -7
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@@ -117,8 +117,8 @@ with CudaContext(0) as ctx, FixedPatchStepper(cfg, context=ctx, refinements=[(8,
level_objects=[(), (body,)]) as run:
rest = np.asarray(compute_feq_d2q9(1.0, 0.0, 0.0), np.float32)[:, None, None]
# (9, ny, nx) postcollision populations per level; non-leaf cells are discarded.
run.initialize(np.broadcast_to(rest, (9, *run.patch.coarse_shape)),
np.broadcast_to(rest, (9, *run.patch.fine_shape)))
run.initialize(np.broadcast_to(rest, (9, *run.hierarchy.pairs[0].coarse_shape)),
np.broadcast_to(rest, (9, *run.hierarchy.pairs[0].fine_shape)))
run.step(128) # coarse steps; fine level takes two per step
coarse_g, fine_g = run.download() # NaN on covered, ghost and solid cells
```
@@ -143,7 +143,7 @@ Scope and limits:
from their union; adjacent, overlapping and concave unions are accepted when
their actual dependencies close. There is no fixed rectangle-gap rule.
The fine level is then one level-wide grid `(2*ny, 2*nx)`:
`run.patch.fine_shape` gives it, `initialize`/`download` use it, and only the
`run.hierarchy.pairs[0].fine_shape` gives it, `initialize`/`download` use it, and only the
grid-aligned tiles intersecting the union plus its four-cell ghost band are stored.
Block sizes must divide the level-wide grid; rectangle edges need not align
with tiles. Order of rectangles does not matter. L1 bodies/Jets (`level_objects[1]`/`level_jets[1]`) work
@@ -159,8 +159,8 @@ Scope and limits:
with CudaContext(0) as ctx, FixedPatchStepper(
cfg, context=ctx, refinements=[((4, 4, 12, 12), (16, 4, 24, 12))],
level_blocks=[(4, 4), (4, 4)]) as run:
run.initialize(np.broadcast_to(rest, (9, *run.patch.coarse_shape)),
np.broadcast_to(rest, (9, *run.patch.fine_shape))) # (9, 32, 64)
run.initialize(np.broadcast_to(rest, (9, *run.hierarchy.pairs[0].coarse_shape)),
np.broadcast_to(rest, (9, *run.hierarchy.pairs[0].fine_shape))) # (9, 32, 64)
run.step(32)
coarse_g, fine_g = run.download() # coarse: NaN on every covered cell;
# fine: NaN on every non-ACTIVE cell
@@ -193,10 +193,10 @@ Scope and limits:
cfg, context=ctx, refinements=[(4, 4, 12, 12), (8, 8, 16, 16)],
level_blocks=[(4, 4)] * 3, level_objects=[(), (), (body,)],
level_jets=[(), (), (jet,)]) as run:
shapes = (run.patch.coarse_shape, run.patch.fine_shape, run.child_patch.fine_shape)
shapes = (run.hierarchy.pairs[0].coarse_shape, run.hierarchy.pairs[0].fine_shape, run.hierarchy.pairs[1].fine_shape)
run.initialize(*(np.broadcast_to(rest, (9, *s)) for s in shapes)) # 16², 24², 24²
run.step(4)
run.set_jet_amplitude(0, -.002, level=2) # default level=1 still addresses L1
run.set_jet_amplitude(0, -.002, level=2) # explicit level selects the driven level
run.step(4)
coarse_g, l1_g, l2_g = run.download() # solids/covered/nonleaves are NaN
```