Move host-only blocked table helpers into refinement_tables

Pure move of blocked_fine_tables, blocked_kind, blocked_base_tables,
_BlockedBoundary and _prepare_blocked_boundary out of the pycuda-importing
refinement_stepper into a numpy-only module, so CPU tests can import them
directly. refinement_stepper re-exports the public names; no behaviour change.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

src/CelerisLab/lbm/refinement_tables.py

@@ -0,0 +1,95 @@
+# CelerisLab/lbm/refinement_tables.py
+"""Host-only (numpy) mapping of fixed-patch transfer and boundary tables to block storage.
+
+No CUDA import: CPU tests import these directly. refinement_stepper re-exports the names.
+"""
+from dataclasses import dataclass, replace
+
+import numpy as np
+
+from .blocks import blocked_link_tables
+from ..body.jets import jet_link_shapes, surface_link_velocity
+from .descriptors import D2Q9_EX, D2Q9_EY
+from .refinement import ACTIVE, OUTER_GHOST
+
+
+def blocked_fine_tables(patch, layout, order):
+    """Remap fixed-patch fine tables to owner-core blocked storage (host only).
+
+    Returns (explosion target block cells, coalescence child slots in the same
+    rows/child order as ``patch.coalesce_fine[order]``, per-block-cell kind with
+    unused halo entries OUTER). Coarse donors/targets are unchanged.
+    """
+    owner = layout.owner.ravel().astype(np.intp)
+    cells = patch.fine_shape[0] * patch.fine_shape[1]
+    q, cell = np.divmod(patch.coalesce_fine[order], np.uint64(cells))
+    kind = blocked_kind(layout, patch.fine_kind)
+    return (owner[patch.ghost_fine.astype(np.intp)].astype(np.uint64),
+            layout.slot(owner[cell.astype(np.intp)], q), kind)
+
+
+def blocked_kind(layout, dense_kind):
+    """Per-block-cell kind; unused halo entries and unstored holes stay OUTER."""
+    owner = layout.owner.ravel().astype(np.intp)
+    owned = layout.owned.ravel()  # sparse multipatch levels leave holes unstored
+    kind = np.full(layout.nblocks * int(np.prod(layout.local_shape)), OUTER_GHOST, np.uint8)
+    kind[owner[owned]] = np.asarray(dense_kind).ravel()[owned]
+    return kind
+
+def blocked_base_tables(patch, layout, order, wall_aware=False, *, composed_kind=None):
+    """Parent donor cells and receiver-local arrival slots, in transfer row order.
+
+    Stage arrivals only after child reads and parent halo gather, immediately
+    before parent pull. Source *owner* slots are wrong at block seams.
+    Nested pairs must pass composed_kind to retain inherited INNER/OUTER and
+    sparse holes; donors and receivers must be owned, uncovered ACTIVE cells.
+    """
+    owner = layout.owner.ravel()
+    q, receiver = np.divmod(patch.coalesce_coarse[order], np.uint64(owner.size))
+    if composed_kind is None:
+        dense_kind = np.where(patch.covered, OUTER_GHOST, ACTIVE).astype(np.uint8)
+        if wall_aware:
+            dense_kind[[0, -1]] = OUTER_GHOST
+    else:
+        dense_kind = np.asarray(composed_kind)
+        if dense_kind.shape != patch.coarse_shape:
+            raise ValueError("composed parent kind has the wrong shape")
+    donors = patch.ghost_coarse.astype(np.intp)
+    receivers = receiver.astype(np.intp)
+    legal = layout.owned.ravel() & (dense_kind.ravel() == ACTIVE) & ~patch.covered.ravel()
+    if not legal[donors].all() or not legal[receivers].all():
+        raise ValueError("child donors/receivers need owned uncovered parent ACTIVE cells")
+    offset = (np.asarray(D2Q9_EY)[q.astype(np.intp)] * layout.local_shape[1]
+              + np.asarray(D2Q9_EX)[q.astype(np.intp)])
+    source = owner[receivers].astype(np.int64) - offset
+    return (owner[donors].astype(np.uint64), layout.slot(source, q),
+            blocked_kind(layout, dense_kind))
+
+
+@dataclass
+class _BlockedBoundary:
+    """One level's stationary BFL data and mutable Jet velocity column."""
+    host: object
+    tables: dict
+    jets: tuple
+    actuated: bool
+    jet_cache: object = None
+    flags: object = None
+    device: object = None
+    kernel: object = None
+
+
+def _prepare_blocked_boundary(boundary, layout, cfg, jets):
+    if boundary is None or layout is None:
+        return None
+    fluid_idx, dirs, q, body_id, rx, ry, _, fallback = boundary.curved_host
+    tables, _ = blocked_link_tables(layout, boundary.flags, fluid_idx, dirs, q, fallback)
+    actuated = bool(jets) or any(o.surface_actuation is not None for o in boundary.objects)
+    if actuated:
+        cfg = replace(cfg)
+        cfg.validate()
+        tables["surface_velocity"], _ = surface_link_velocity(
+            boundary.objects, cfg, boundary.flags, fluid_idx, dirs, body_id, rx, ry,
+            jets=jets, hits=boundary.curved_hits)
+    return _BlockedBoundary(boundary, tables, jets, actuated,
+                            jet_link_shapes(jets, boundary.curved_hits) if jets else None)