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CelerisLab/tests/validation/taylor_green/shear_probes.py
T
ClaudeandClaude Opus 5.5 caa573f978 test: adopt native-validated 24-target probe layout
Horizontal y=56 and vertical x=38 through box 1, normal coordinates
[12.5..26.125] (root128 physical). Nearest-ACTIVE mapping with
deterministic tie rule (distance, finer level, smaller j, smaller i),
duplicate-cell rejection, stored centers and displacements. Replaces my
earlier offsets, which mapped two target pairs to the same U128 cell.
U512 spacing 128/512 and root step r -> U512 step 4r unchanged.
Tests: 24 unique cells per case, nested 3 L0 + 5 L1 + 4 L2 per transect,
U128 max displacement 0.625.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-19 03:13:43 +00:00

124 lines
5.3 KiB
Python

"""Signed interface-probe traces for the nested/twin shear presets (mechanism diagnostic).
No pass gates. Native-validated 24-target layout through box 1, in root-128
physical coordinates, crossing L0->L1 and (nested only) L1->L2 away from corners:
horizontal line y = 56 across the vertical faces x = 16 and x = 22;
vertical line x = 38 across the horizontal faces y = 16 and y = 22;
normal coordinates NORMAL_COORDS on both (nested: 3 L0 + 5 L1 + 4 L2 each).
Each target maps to the nearest ACTIVE leaf center (tie rule: distance, then
finer level, then smaller j, then smaller i). Grids differ between cases
(U128, U512, nested, twin), so actual centers, levels and displacements are
stored and analytic fields are evaluated at the actual centers.
Samples are POST-collision G at root synchronization only (root-step units);
no substep content is observed, and grid-scale alternation can alias.
"""
import math
import numpy as np
import shear_wave as sw
from oracle import CX, CY, U
ROOT_N = 128
NORMAL_COORDS = (12.5, 14.5, 15.5, 16.25, 17.25, 19.25, 20.75, 21.75,
22.125, 23.125, 24.125, 26.125)
TRANSECTS = {"horizontal_y56": dict(axis=0, other=56.0), # x varies, y fixed
"vertical_x38": dict(axis=1, other=38.0)} # y varies, x fixed
STEPS = tuple(range(0, 129)) + tuple(range(1920, 2049)) # root steps, both inclusive
TRACE_MAX_BYTES = 600_000
def points():
out = []
for name, t in TRANSECTS.items():
for along in NORMAL_COORDS:
xy = (along, t["other"]) if t["axis"] == 0 else (t["other"], along)
out.append((name, along, xy))
return out
def case_steps(n):
"""Case lattice steps at the fixed root-physical sample times (U512: 4 per root step)."""
return [s * (n // ROOT_N) for s in STEPS]
def select(masks, n=ROOT_N):
"""Nearest ACTIVE leaf center for each target (deterministic tie rule).
Targets and stored centers are in root-physical units (root cell = 1); a case
with root N = n has cell size h = ROOT_N / (n * 2**level) there (U512: 0.25).
"""
if n % ROOT_N:
raise ValueError("case root N must be a multiple of 128")
probes = []
for name, along, (x, y) in points():
best = None
for level, mask in enumerate(masks):
h = ROOT_N / (n * 2 ** level)
i0, j0 = int(math.floor(x / h)), int(math.floor(y / h))
for j in range(j0 - 2, j0 + 3):
for i in range(i0 - 2, i0 + 3):
if 0 <= j < mask.shape[0] and 0 <= i < mask.shape[1] and mask[j, i]:
cx, cy = h * (i + 0.5), h * (j + 0.5)
key = (math.hypot(cx - x, cy - y), -level, j, i)
if best is None or key < best[0]:
best = (key, level, i, j, cx, cy)
if best is None:
raise ValueError(f"no ACTIVE leaf near target {(x, y)}")
_, level, i, j, cx, cy = best
probes.append(dict(transect=name, normal=along, point=[x, y], level=level, i=i, j=j,
center=[cx, cy], displacement=[cx - x, cy - y]))
if len({(p["level"], p["i"], p["j"]) for p in probes}) != len(probes):
raise ValueError("probe targets map to duplicate cells")
return probes
def sample(arrays, probes):
"""Flat [rho, ux, uy] per probe from FP64 physical populations."""
row = []
for p in probes:
f = np.asarray(arrays[p["level"]][:, p["j"], p["i"]], dtype=float)
rho = float(f.sum())
row += [rho, float(CX @ f) / rho, float(CY @ f) / rho]
return row
def new_trace(probes, case_viscosity, case):
"""Times/coordinates are root-physical (N=128); nu_root = U*128/Re for all cases."""
return dict(schema=1, kind="mechanism diagnostic, no pass gates", case=case,
time_unit="root step (N=128)", sample_phase="postcollision G at root synchronization",
root_n=ROOT_N, viscosity_root=U * ROOT_N / sw.RE, case_viscosity=case_viscosity,
mode=list(sw.MODE), phase=sw.PHI,
amplitude=U, fields=["rho", "ux", "uy"], probes=probes, steps=[], values=[])
def residuals(trace):
"""Signed (drho, dux, duy) per step and probe, analytic field at each actual center."""
out = []
for step, row in zip(trace["steps"], trace["values"]):
res = []
for n, p in enumerate(trace["probes"]):
x, y = p["center"]
ux, uy, _ = sw.exact(x, y, step, trace["root_n"], trace["viscosity_root"])
rho, vx, vy = row[3 * n: 3 * n + 3]
res.append((rho - 1.0, vx - float(ux), vy - float(uy)))
out.append(res)
return out
def validate(trace):
"""Exact schedule, finite values, fixed probe count and byte cap."""
import json
if trace.get("steps") != list(STEPS) or len(trace["values"]) != len(STEPS):
raise ValueError("trace steps differ from the fixed schedule")
if len(trace["probes"]) != len(NORMAL_COORDS) * len(TRANSECTS):
raise ValueError("unexpected probe count")
width = 3 * len(trace["probes"])
if any(len(r) != width or not all(math.isfinite(v) for v in r) for r in trace["values"]):
raise ValueError("malformed or nonfinite trace row")
size = len(json.dumps(trace, allow_nan=False).encode())
if size > TRACE_MAX_BYTES:
raise ValueError(f"trace exceeds {TRACE_MAX_BYTES} bytes ({size})")
return size