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Multipatch: validate fine block before modulo, raw-core GPU checks, README usage

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FixedPatchSet2D.fine_layout rejects non-positive, float, bool or wrong-length
block sizes with ValueError before any modulo (was ZeroDivisionError/TypeError).
The face gap-4 GPU test now checks raw owner cores directly by kind/covered
for every patch (ACTIVE finite, OUTER/holes/covered NaN; INNER not asserted),
not only the masked download and reversed-order parity. README documents the
body-free multipatch call, scope and level-wide fine shape.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
This commit is contained in:
Claude
2026-10-16 14:22:00 +00:00
co-authored by Claude Opus 5.5
parent 0397b6ebb7
commit 6301887093
4 changed files with 47 additions and 5 deletions
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tests/validation/multigrid/test_refinement_multipatch.py
+19 -2
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@@ -6,7 +6,8 @@ Run CPU and GPU classes in separate processes. GPU gates (frozen before any run)
- S1 translation copy: two patches on 16x32 equal the 16x16 one-patch run tiled
twice, bit for bit, every step;
- reversed rectangle order gives bit-identical results;
- face gap-4 pair (16x24): ACTIVE leaves finite, covered/hole masks exact.
- face gap-4 pair (16x24): ACTIVE leaves finite, covered/hole masks exact, also on
raw owner cores per patch (INNER partly invalid by contract, not asserted).
Weighted leaf mass is printed as a diagnostic only.
"""
from dataclasses import replace
@@ -16,7 +17,7 @@ import numpy as np
import pycuda.driver as cuda
from CelerisLab.config import LBMConfig
from CelerisLab.lbm.refinement import ACTIVE, FixedPatch2D, FixedPatchSet2D
from CelerisLab.lbm.refinement import ACTIVE, OUTER_GHOST, FixedPatch2D, FixedPatchSet2D
from CelerisLab.lbm.refinement_stepper import FixedPatchStepper
from test_refinement_blocked_fine import BOUNDS, NX, NY, config, state, circle
from test_refinement_blocked_base import exact, raw
@@ -112,6 +113,9 @@ class MultipatchGPU(unittest.TestCase):
fine = level_fine(s, [state(*p.fine_shape, 6 + i) for i, p in enumerate(s.patches)])
kw = dict(fine_block=(4, 4), base_block=(4, 4))
leaf = s.fine_kind == ACTIVE
support = s.fine_layout((4, 4)).owned
outer = support & (s.fine_kind == OUTER_GHOST)
holes = ~support
with CudaContext(0) as context:
runs = [self.run_steps(context, cfg, bounds, coarse, fine, **kw)
for bounds in (FACE, FACE[::-1])]
@@ -123,6 +127,19 @@ class MultipatchGPU(unittest.TestCase):
self.assertTrue(np.isnan(c[:, s.covered]).all())
self.assertTrue(np.isfinite(f[:, leaf]).all())
self.assertTrue(np.isnan(f[:, ~leaf]).all())
# Raw owner cores, independent of the download mask (every patch).
# INNER may be partly NaN after hop 2 by contract: not asserted.
rc, rf = a[2], a[3]
label = f"raw step {step}"
self.assertTrue(np.isfinite(rc[:, ~s.covered]).all(), label + " coarse leaves")
if step: # covered parent cores are poisoned by the parent step
self.assertTrue(np.isnan(rc[:, s.covered]).all(), label + " covered")
self.assertTrue(np.isfinite(rf[:, leaf]).all(), label + " fine ACTIVE")
self.assertTrue(np.isnan(rf[:, outer]).all(), label + " fine OUTER")
self.assertTrue(np.isnan(rf[:, holes]).all(), label + " fine holes")
for i, p in enumerate(s.patches):
active = window(s, i, rf)[:, p.fine_kind == ACTIVE]
self.assertTrue(np.isfinite(active).all(), f"{label} patch {i} ACTIVE")
mass = float(np.nansum(c, dtype=np.float64) + .25 * np.nansum(f, dtype=np.float64))
print(f"face gap4 step {step}: weighted leaf mass {mass:.9g} (diagnostic)", flush=True)