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ClaudeandClaude Opus 5.5 de5b0cc080 test: shear-wave modal-extinction handling; TG mock verify_source flow arg
- shear_wave.fit_rate: finite late R=0 returns rate_fit_valid=false with
  null fit quantities (no clipping, no invented rate); own screens and
  budgets treat it as a failure (CONTROL_SCREEN_FAIL / refined FAIL),
  other finite metrics retained, JSON-safe.
- test_projected_pairs: dry-run/execution mocks expect the explicit
  'taylor_green' flow argument now passed to verify_source.
- run_case: SHEAR_WAVE_SHA256 repinned; extinction test added.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-19 00:36:19 +00:00
ClaudeandClaude Opus 5.5 f337652683 test: shear-wave row validation, controlled-pass semantics, bounds
- shear_wave: validate_rows before screens (exact scheduled steps/t*, no
  duplicates, all numeric/list fields finite, nonnegative error fields,
  rho_min>0; signed amplitude/phase/interval errors keep their sign);
  INVALID_RUN for invalid refined rows; own_screens_pass vs controlled_pass
  so a CONTROL_SCREEN_FAIL set never reports a controlled pass; empty or
  duplicate refined schemes rejected; pressure-budget redundancy stated.
- run_case: SHEAR_WAVE_SHA256 repinned to the updated module.
- tests: divergence/advection bounds use a(t) and the derived h^2 term;
  invalid-row mutations; signed errors allowed; controlled_pass checks.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-19 00:28:46 +00:00
ClaudeandClaude Opus 5.5 3554cb2fde test: fix shear-wave review findings (runner finiteness, source pin, contract)
- run_case: finite_row accepts list diagnostics; sample() shared by sample
  and READY paths; verify_source pins shear_wave.py path+SHA256 for
  --flow shear_wave (default TG flow unchanged, does not import it).
- assess_shear_wave.py: fixed N128 four-case contract and 4-JSON CLI,
  reusing assess_projected_pairs provenance/build/workload/time checks plus
  shear metadata; missing/duplicate/mixed/extra records -> INVALID_SET.
- tests: mocked refined runner sample (list diagnostics, NaN, TG unchanged),
  contract pass + reproduced false-pass mutations, divergence check uses
  analytic E.k=0 and a derived h^2 truncation + roundoff bound with
  h-halving scaling instead of a fixed 1e-12.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-19 00:26:58 +00:00
ClaudeandClaude Opus 5.5 10069feadb test: apply shear-wave review corrections
Modal magnitude R=hypot(a,b) with amplitude error and separate phase;
free-intercept ln R rate fit with per-interval rates, log-fit residual,
t* units and finite-positive check; spurious-pressure naming with raw rms;
INVALID_CONTROL vs CONTROL_SCREEN_FAIL (refined results kept), mixed-source
check, raw ratios to both controls; docs narrow the cubic-term scope,
startup and placement limitations. oracle.py still byte-identical.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-19 00:18:20 +00:00
ClaudeandClaude Opus 5.5 ffff742b69 test: add oblique (2,1) shear-wave diagnostic with composite modal fit
Test-only. New shear_wave.py (exact field, equilibrium initializer reusing
frozen oracle constants/geometry, area-weighted composite metrics with a
2x2 Gram-matrix modal fit, late-time rate fit, preregistered assess with
max(2*control, floor) budgets). run_case.py gains --flow (default
taylor_green, unchanged receipt). oracle.py byte-identical (pinned by test).
CPU manufactured checks in test_shear_wave.py; docs record caveats.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-19 00:16:21 +00:00
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# Compatibility and API changes
Changes that can make a previously accepted setup or call behave differently.
Each entry names the commit, the affected entry points and the observable result.
## 87c3a31: cut-link ownership is validated for every body
`validate_cut_link_ownership` (`body/preprocess/flag_overlay.py`) now runs for
passive bodies as well as Jet/aperture bodies. Every cut link must have an
active fluid receiver (FLUID set, SOLID clear), and each `(receiver, direction)`
population may have only one writer.
Rejected with `ValueError`, before flags, populations or device buffers change:
1. Overlapping or touching passive solids whose cut links write the same
population ("Boundary requires unique cut-link writers").
2. A body whose cut-link receiver is a non-fluid cell, e.g. a channel wall row
or the inlet/outlet column ("Cut links must have active fluid receivers").
Both were previously accepted silently for passive bodies; the interpolated
boundary then had undefined results. The rules apply to the cut links of all
bodies together, so a passive body overlapping a Jet body is rejected as well.
The check runs in `Simulation.initialize`, runtime body sync (`sync_bodies`),
checkpoint save and checkpoint load (`common/checkpoint.py`). Load validates
before restoring anything, so a checkpoint whose saved geometry violates either
rule no longer restores; rebuild the geometry with separated bodies.
## 87c3a31: `Simulation.read_surface_exchange` accepts Jet-driven bodies
`read_surface_exchange(id)` previously required `SurfaceActuation` on the body.
It now also accepts bodies that own Jet aperture links, including Jets with zero
or negative amplitude (the aperture test is geometric). Bodies with neither
`SurfaceActuation` nor aperture links still raise
`ValueError("Body has no surface actuation")`. The value is unchanged: the latest
step's wall/aperture exchange, not total nozzle force.
-49
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@@ -1,49 +0,0 @@
# DFG 2D-1 (Re 20) against the official reference intervals
`tests/validation/run_dfg_re20.py` runs the steady DFG 2D-1 case on the refined
channel root (D40 root, D80 wide fine patch) and on the uniform D80 grid. Geometry,
inflow, initial state, layout and observation are those of the pinned Re100 runner
(`run_refined_dfg.py`, `re100_helpers.py`, both unchanged); only the lattice
viscosity is set for Re 20 (root tau 0.56, fine 0.62, uniform 0.62, lattice speed 0.01).
Label: "compared against the official reference bands", not a full benchmark
certification: the outlet is pressure-NEQ (`neq_extrap`), not do-nothing, and the
inlet is local Zou-He.
## Quantities
- Cd = 2 Fx / (rho U^2 D), Cl = 2 Fy / (rho U^2 D), interval means over each sample.
- p_diff = p(0.15, 0.2) - p(0.25, 0.2), linear extrapolation to the exact surface
points (`re100_helpers.pressure_probes`). The helper returns dp / (rho U^2) in
scaled units; p_diff = dp * 0.04 for U = 0.2 m/s, rho = 1. Both are reported.
- Official intervals (Schaefer & Turek 1996): Cd [5.57, 5.59], Cl [0.0104, 0.0110],
p_diff [0.1172, 0.1176].
## Bounds and steady rule (frozen before any run)
- End time t* = 60 (30 s physical): 240,000 refined root steps, 480,000 uniform steps.
- One sample every t* = 0.5 (0.25 s) at the end of a synchronized root step; Cd and
Cl are interval means. Trailing window t* 50..60 inclusive (21 samples).
- Steady rule (our engineering choice, not official): in the window, for each of Cd,
Cl, p_diff, max - min <= 10 % and |least-squares slope x window| <= 2 % of its
official interval width (range 2e-3 / 6e-5 / 4e-5; slope 4e-4 / 1.2e-5 / 8e-6).
Absolute limits, so the small Cl is never a divisor. Never relaxed after a run.
- The verdict uses the window mean; the distance to the nearest interval edge is
reported for each quantity (negative outside).
- Force sign: fluid on cylinder, x along the inflow, y up from the bottom wall; Cd > 0
and the official Cl > 0 (`cd_positive` is reported).
- Not steady at t* = 60: status `NOT_STEADY`, no interval verdict. Health limits
(Mach <= 0.2, rho in [0.5, 1.5]) stop the run with `UNHEALTHY`.
- Steady: `WITHIN_INTERVALS` or `OUTSIDE_INTERVALS`, with the per-quantity verdict.
## Run
```
python tests/validation/run_dfg_re20.py --output <new-dir> --plan
CUDA_VISIBLE_DEVICES=<n> python tests/validation/run_dfg_re20.py --case both \
--collision SRT --output <new-dir> --max-wall-seconds <cap>
```
The uniform D80 control separates method error from refinement error. `--plan` writes `plan.json` only. A GPU run writes `plan.json` and `result.json`
(per case: lattice parameters, every sample, window ranges, status, verdict).
Host contract tests: `tests/unit/test_dfg_re20.py`.
-59
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@@ -56,62 +56,3 @@ Root must independently review and admit any execution. An admitted paired pilot
the existing watchdog, device selection, `--gpu-gates-approved`, positive
`--max-wall-seconds` and a new output directory, adding only `--exchange-window` to the
selected collision's pilot command. No GPU or remote action was performed for this patch.
## Public Jet diagnostic option
`--collision MRT --exchange-window --jet-scenario zero|fixed|reverse` selects
unshifted FP32, no LES, constant transfer on both existing public backends. Default
`none` and the historical manifests remain unchanged. `zero` registers both Jets at
zero amplitude and retains every existing DFG verdict, including pressure. `fixed`
uses outward radial parabolic sectors at pi/2 and 3pi/2, half-width pi/12, peaks
(+.001,-.001). Both use the existing D40/D80 geometry and U=.01. Sector origins are
(80.5,81) in root edge coordinates and (160,160.5) in uniform node coordinates;
radial extent is [0,1.005R]. `reverse` keeps those peaks through t*=300, updates both
public setters at that completed boundary, and continues to 305 with opposite signs.
Fixed diagnostic windows are 250–260, 260–270, 270–280, 280–290 and 290–300; reversal
adds 300–305. Histories retain exact interval endpoints and root/uniform lattice
impulses. The refined window uses total exchange; uniform uses public `read_force`
batch averages. Driven windows report mean/min/max/RMS Cd/Cl without applying DFG
reference or periodicity gates. Exit zero means healthy execution, not qualification;
`matched_case_pass` remains false. No independent CV or stress-load claim is made.
This opt-in records current source/helper hashes with the existing manifest format,
checkout revision/dirty state and runner hash. Pilot/full must match that snapshot
and the exact scenario. It does not relabel current source as historical evidence.
Use the existing bounded plan/pilot/full commands with the three option flags above;
full requires the matching completed t*=5 paired pilot. `step_seconds` includes force
readback; observation/overhead and total wall time are separate, not kernel throughput.
Add `--observe-cv` to record independent scalar control-volume samples from the
already downloaded public macros. The pilot exercises this path at t*=.02..5;
full records 501 endpoints at 290..300. Each `cv_history.jsonl` row contains actual
root time, preceding interval start/duration/impulse, and two inventories/outward
fluxes ordered [mass,Px,Py]. Exclude the first row's preceding impulse: that row
supplies the initial inventory. Uniform native impulse converts by .5² to root
units; refined ledger impulse is already in root units. Explicit native-aligned
contours differ by .25 root cells in x and are recorded in the plan. Cropping
retains the two-cell face-gradient stencils. No fields or per-link arrays are saved.
`cv_observation_seconds` is the CV portion of observation/overhead time. Helper hash
and the observation flag must match pilot/full. Time integration, temporal
coarsening and any physical assessment remain separate offline work.
## Bounded resolution and placement controls
Defaults remain `--case both --uniform-diameter 80 --placement wide`. Single-case
runs use `--case uniform` or `--case refined` and never report a matched-case pass.
Their own reference/periodicity or driven-diagnostic results remain available.
A single zero-Jet full run exits successfully only when its periodicity and the
unchanged complete DFG reference verdict pass; driven completion is not qualification.
The D160 option requires `--case uniform --uniform-diameter 160` and an explicit
public Jet scenario. U and Jet speeds stay .01 and ±.001; viscosity is .016,
grid 3521×658, center (320,320.5), radius80. CV uses root spacing/time factor .25,
origin (.375,.75), impulse factor .0625, root viscosity .004, and x-face shift .125.
`--case refined --placement compact` selects root bounds (48,48,128,128), fine
168×168 and origin (46,46), with the same D40/fineD80 body/Jet resolution. Its CV
contours are (52,52,112,112) and (50,50,120,120); complete face-gradient stencils
are clear of both solids and the transfer footprint. Compact is refined-only.
CV metadata gives each grid's spacing/origin/contours explicitly. Case, uniform
diameter and placement must match the newly completed pilot in every receipt.
+136
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@@ -159,3 +159,139 @@ theoretical stress-consistency certification or production-kernel change.
## Repository integration
The four Python harness files remain together under tests/validation/taylor_green, so runtime provenance hashes precisely this harness directory. Formatting changes produce a new harness identity; preparation and integrated receipts must not be mixed. All analytic definitions, numerical floors, assessment gates, sample times, and source-import assertions are unchanged. Production source is unchanged from the cd3 snapshot; these periodic tests do not waive the separate channel GPU gate.
## Oblique shear wave (test-only diagnostic, not GPU-qualified)
`shear_wave.py` reuses the frozen oracle's constants, cell centers and
geometry. `oracle.py` is byte-identical, and `test_shear_wave.py` pins its
eec4677 SHA-256. `run_case.py --flow shear_wave` selects the shear wave;
the default flow and its receipt are the unchanged Taylor–Green path.
### Convention
Integer mode (2,1) on the L=N periodic root domain:
- the wavevector `k = (2*pi/L)*(2,1)` points 26.565° from +x;
- mode (1,2) would point 63.435°, and a wrong-mode test catches a swap.
Polarization is `E = (-1,2)/sqrt(5)`, perpendicular to k:
u = U*E*sin(k.x + phi)*exp(-nu*|k|^2*t), phi = 0, p = const, rho0 = 1
`nu = U*N/100`, the Taylor–Green Re100 viscosity at the same N. This is an
exact incompressible Navier–Stokes solution. The initial condition is FP64
second-order equilibrium at the actual leaf centers, with no
non-equilibrium part.
### Physical caveats
1. *Scope of the cubic-term argument.* The second-order D2Q9 equilibrium
lacks the cubic third moment `rho*u_a*u_b*u_g` of the Maxwellian (Dellar,
https://people.maths.ox.ac.uk/dellar/papers/Galilean.pdf, eq. 3). At
Navier–Stokes order this produces a stress error proportional to
`d_g(rho u_a u_b u_g)`.
For the ideal constant-density, zero-background transverse wave, k.E = 0
makes that contracted derivative vanish. That is the only claim made.
It does not remove other discrete or finite-Mach errors. It is not
guaranteed once AMR introduces density, longitudinal or higher-mode
contamination. The analytic NS field itself is exact.
2. *Startup.* Equilibrium initialization is not the discrete shear
eigenmode (Mei et al., https://doi.org/10.1016/j.compfluid.2005.08.008).
- The decay rate is a free-intercept least-squares fit of ln R over the
samples with t* >= 0.12, where `R = hypot(a_hat, b_hat)`.
- The intercept cancels only a constant amplitude prefactor, and only
once a single exponential dominates.
- Per-interval rates and the maximum log-fit residual are kept, so a
lingering transient stays visible.
- Late sampling alone does not show that transients have gone.
### Metrics
Computed on ACTIVE leaf cells, each weighted by its area `4**-level` in
root-cell units. The partition must cover the domain exactly once, and one
global pressure gauge is used.
- `a_hat`, `b_hat`: weighted least-squares fit of `u.E` onto sin/cos, using
the 2x2 Gram matrix of the actual composite quadrature. A wrong Fourier
mode need not project to exactly zero on this quadrature.
- `amplitude_error = R/A_exact - 1`.
- `phase_drift = atan2(b_hat, a_hat)`, in radians, reported separately.
- Rates are positive (minus the fitted slope).
- Per root step they are compared with `nu*|k|^2`. Uniform 2N uses its
own `nu = 0.0768` at N=256 and doubled step counts.
- In t* they are compared with `5*(2*pi)^2/Re = 1.97392088`.
- `rate_error = |rate/exact - 1|`.
- `velocity_l2`, `residual_l2` (velocity left after removing the fitted
mode) and `longitudinal_l2` (the `u.k_hat` part), all relative to the
exact-field norm. A longitudinal perturbation also raises the
full-vector residual and the velocity L2.
- `spurious_pressure_rms`: the raw gauged rms of `p = (rho-1)/3`.
- `spurious_pressure_scaled`: that rms divided by `A_exact(t)^2/4`, a
continuum reference scale. It is *not* the discrete, globally gauged
Taylor–Green norm on the composite grid. Exact pressure is constant, so
no relative-to-exact claim is made. Max and per-level values are kept.
### Preregistered screens (`shear_wave.assess`)
Run set: uniform N, uniform 2N, and refined depth-2 runs at root N.
- `eps(N) = (|k| h_root)^2 = 5*(2*pi/N)^2`: dimensionless, coefficient
one, 0.01205 at N=128. This is a chosen screen, not a proven error bound.
- Absolute screens:
- rate_error, max |phase_drift| (radians) and max residual_l2 must each
be <= eps;
- velocity_l2 <= 0.05, mass <= 1e-5, spurious_pressure_scaled <= 0.02.
- Budgets keep the `assess.py` form, `refined <= max(2*control_N, floor)`:
- floors are 0.002 for rate and residual, 0.02 for pressure;
- the comparative pressure budget is always redundant:
`max(2*control, 0.02)` is never below the 0.02 absolute ceiling;
- raw ratios to both the root and finest controls, including raw
pressure rms, are always reported.
- Every record is validated before any screen is applied:
- exact scheduled steps and t*, with no duplicates;
- every numeric field finite, including list fields and density;
- error quantities nonnegative and rho_min > 0;
- signed quantities (amplitudes, `amplitude_error`, `phase_drift`,
per-interval rate errors) keep their sign.
- Outcomes are kept distinct:
- INVALID_CONTROL: a control or refined run is missing, a control is
incomplete or invalid, or the records come from mixed sources;
- INVALID_RUN: a refined record fails validation;
- CONTROL_SCREEN_FAIL: complete, valid controls fail their own screens.
Each refined run's `own_screens_pass` is still reported, but
`controlled_pass` is false, so it is never a controlled-comparison pass;
- PASS/FAIL: every refined run's `controlled_pass` (own screens and
budgets against valid, passing controls).
- Finite modal extinction (late R = 0) is a physical failure, not
malformed data. The run gets `rate_fit_valid=false` with null fit
quantities, and its other metrics are kept. Nothing is clipped and no
rate is invented. The result is CONTROL_SCREEN_FAIL for a control, or
FAIL for a refined run.
- Screens are never retuned.
### Limitations
One flow, one phase and one rectangle, SRT only. The rectangle's vertical
faces span 0.625 tangential periods and its horizontal faces 1.5, so this
is not placement robustness. Two resolutions show a trend, not an order.
### Receipt assessment and runner integrity
- Fixed four-case N128 contract:
`python assess_shear_wave.py U128.json U256.json R128_constant.json R128_projected.json --output report.json --expected-revision <sha>`.
It reuses the shared provenance, build, workload and sample-time checks
from `assess_projected_pairs.py`, and adds shear metadata checks (flow,
mode, polarization, angle, phase, eps, limits, disabled early trace, and
pinned `shear_wave.py` hash).
- Missing, extra, duplicate or mixed-source records give `INVALID_SET`,
as does any failed shared check.
- Otherwise the result comes from `shear_wave.assess`, which separates
`INVALID_CONTROL` from `CONTROL_SCREEN_FAIL`.
- `run_case.verify_source(..., flow="shear_wave")` requires the imported
`shear_wave.py` to be the selected harness file with the pinned
`SHEAR_WAVE_SHA256`. The default TG flow does not import it.
- Sample and READY finiteness use `finite_row`, which accepts scalar and
list diagnostics. For TG's all-scalar rows it behaves the same as before.
- Merge note: native 92b8afe adds a `scaled_n256` receipt block. When the
two are merged, keep both blocks and make `--flow shear_wave` and
`scaled_n256` mutually exclusive. Not merged here.
+5 -2
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@@ -216,8 +216,11 @@ def surface_link_velocity(objects, cfg, flags, fluid_idx, dir, body_id, rx, ry,
enabled = [obj for obj in objects if obj.surface_actuation is not None]
if not enabled and not jets:
return None, None
from .preprocess.flag_overlay import validate_cut_link_ownership
validate_cut_link_ownership(flags, fluid_idx, dir, cfg.nq)
from ..lbm.descriptors import FLUID, SOLID
if np.any((flags[fluid_idx] & FLUID) == 0) or np.any(flags[fluid_idx] & SOLID):
raise ValueError("Surface cut links must have active fluid receivers")
if len(np.unique(fluid_idx.astype(np.uint64)*cfg.nq+dir)) != len(dir):
raise ValueError("Surface boundary requires unique cut-link writers")
surface_velocity = np.zeros((len(dir), 2), np.float32)
surface_aperture = np.zeros(len(dir), bool)
for obj in enabled:
+12 -17
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@@ -27,7 +27,7 @@ import pycuda.driver as cuda
from .objects import SimObject
from .registry import BodyRegistry
from .preprocess.flag_overlay import merge_flag_masks, validate_cut_link_ownership
from .preprocess.flag_overlay import merge_flag_masks
from ..cuda.compiler_v2 import obs_layout
from ..cuda.obs_layout import ObsLayout
from ..lbm.descriptors import (
@@ -369,9 +369,9 @@ class ObjectManager:
Args:
objects: List of SimObject instances to process.
domain_flags: Optional uint16 flags for receiver/donor classification.
domain_flags: Optional uint16 flags for donor-cell classification.
sensor_cell_counts_out: Int array to fill with per-object sensor
cell counts after the full geometry has passed validation.
cell counts. If provided, ``fill(0)`` is called first.
hits_out: List that receives one FP64 (n, 2) array of true hit
points row-aligned with the cut-link columns (for Jets).
@@ -394,8 +394,8 @@ class ObjectManager:
active_fluid = ((domain_flags & FLUID) != 0) & ((domain_flags & SOLID) == 0)
force_owners: set[int] = set()
sensor_counts = (np.zeros_like(sensor_cell_counts_out)
if sensor_cell_counts_out is not None else None)
if sensor_cell_counts_out is not None:
sensor_cell_counts_out.fill(0)
ez = None
if self.cfg and self.cfg.is_d3q19:
@@ -430,9 +430,9 @@ class ObjectManager:
if len(cells) > 0:
s_cells.append(cells)
s_ids.append(ids)
if (sensor_counts is not None
and 0 <= obj.obj_id < sensor_counts.size):
sensor_counts[obj.obj_id] = int(len(cells))
if (sensor_cell_counts_out is not None
and 0 <= obj.obj_id < sensor_cell_counts_out.size):
sensor_cell_counts_out[obj.obj_id] = int(len(cells))
if obj.is_force_region and hasattr(obj, 'get_sensor_list'):
cells, ids = obj.get_sensor_list(self.nx, self.ny, self.nz)
keep = active_fluid[cells]
@@ -461,9 +461,8 @@ class ObjectManager:
r_fr_ids = np.concatenate(fr_ids) if fr_ids else np.zeros(0, dtype=np.int32)
r_hit = np.concatenate(cl_hit) if cl_hit else np.zeros((0, 2))
# Passive walls need the same ownership guarantees as driven walls.
# Overlapping solids are not a supported union-boundary operation.
validate_cut_link_ownership(domain_flags, r_idx, r_dir, self.nq)
if hits_out is not None:
hits_out.append(r_hit)
if self.jets or any(obj.surface_actuation is not None for obj in objects):
# Reject unresolved apertures/ownership before sync or restart mutates state.
from ..lbm.curved_links import CurvedLinkSoA
@@ -471,11 +470,6 @@ class ObjectManager:
links.assign_host(r_idx, r_dir, r_q, r_bid, r_rx, r_ry, r_rz, r_fallback)
links.assign_surface(objects, self.cfg, domain_flags, jets=self.jets, hits=r_hit)
if sensor_cell_counts_out is not None:
sensor_cell_counts_out[:] = sensor_counts
if hits_out is not None:
hits_out.append(r_hit)
return (
r_idx, r_dir, r_q, r_bid,
r_rx, r_ry, r_rz, r_fallback,
@@ -493,6 +487,8 @@ class ObjectManager:
the caller has already prepared and uploaded the final flag field
for this geometry, such as during initialization.
"""
self._telemetry_field = field
next_flags = self.build_flags(field.build_channel_flags()) if rebuild_flags else field.flag
hits = []
@@ -503,7 +499,6 @@ class ObjectManager:
fr_cells, fr_obj_id,
) = self.build_compact_lists(domain_flags=next_flags, hits_out=hits)
self._telemetry_field = field
if rebuild_flags:
field.flag = next_flags
field.upload_flags()
+1 -10
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@@ -1,6 +1,6 @@
# CelerisLab/body/preprocess/flag_overlay.py
"""
Flag overlay and cut-link ownership checks against the merged domain.
Flag overlay: merge per-object flag masks onto a clean domain base.
"""
from __future__ import annotations
@@ -12,15 +12,6 @@ import numpy as np
from ...lbm.descriptors import FLUID, SOLID, SENSOR_FLAG, FRC_REGION
def validate_cut_link_ownership(flags, fluid_idx, directions, nq):
"""Reject solid receivers and multiple writers to one population."""
if np.any((flags[fluid_idx] & FLUID) == 0) or np.any(flags[fluid_idx] & SOLID):
raise ValueError("Cut links must have active fluid receivers")
writers = fluid_idx.astype(np.uint64) * nq + directions
if len(np.unique(writers)) != len(directions):
raise ValueError("Boundary requires unique cut-link writers")
def merge_flag_masks(
base: np.ndarray,
masks: List[np.ndarray],
+8 -17
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@@ -336,19 +336,13 @@ class Simulation:
def read_surface_exchange(self, id: int):
"""Latest step's wall/aperture (Fx,Fy,Tz) exchange, not total nozzle force.
Supports SurfaceActuation and Jet-driven bodies, including zero-amplitude
apertures. Passive bodies without an aperture are rejected.
Unlike read_body this is not accumulated/time-averaged. It resets after
geometry sync or checkpoint load; advance before interpreting it.
"""
obj = self.bodies.get(id)
curved = self.field.curved
has_aperture = (curved.aperture is not None
and np.any(curved.aperture & (curved.body_id == id)))
if obj.surface_actuation is None and not has_aperture:
if self.bodies.get(id).surface_actuation is None:
raise ValueError("Body has no surface actuation")
self.stream.synchronize()
return curved.surface_exchange(id)
return self.field.curved.surface_exchange(id)
@context_bound
def read_body(self, id: int, *,
@@ -457,21 +451,18 @@ class Simulation:
@context_bound
def initialize(self):
"""Initialize flow field and sync objects to GPU."""
self._assert_allocation_contract()
# Validate the complete geometry before flags, populations or modules
# change. Compact-list construction publishes no outputs on failure.
next_flags = self.bodies.build_flags(self.field.build_channel_flags())
if self.bodies.jets and self.bodies.count == 0:
raise ValueError("Jets need bodies with cut links")
self.bodies.build_compact_lists_for(self.bodies.objects, next_flags)
# Recompile if objects were added after construction.
self._assert_allocation_contract()
if self._read_generated_n_objects() != self.bodies.count:
self.recompile()
self.field.flag = next_flags
self.field.flag = self.field.build_channel_flags()
if self.bodies.count > 0:
self.field.flag = self.bodies.build_flags(self.field.flag)
self.field.upload_flags()
if self.bodies.jets and self.bodies.count == 0:
raise ValueError("Jets need bodies with cut links")
self.stepper.initialize()
if self.bodies.count > 0:
self.bodies.sync_to_gpu(self.field, rebuild_flags=False)
-101
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@@ -1,101 +0,0 @@
"""Synthetic checks of the annulus mass ledger. Host-only, stdlib; not solver evidence."""
import random
import sys
from pathlib import Path
import unittest
sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "validation"))
import annulus_ledger as al # noqa: E402
NX = NY = 24
# Annulus 4 <= r <= 8 around (12, 12); dyadic values keep every sum exact.
A = {(x, y) for x in range(NX) for y in range(NY) if 16 <= (x - 12) ** 2 + (y - 12) ** 2 <= 64}
DELTA = 0.375
def owner(seed=1):
rng = random.Random(seed)
return [[[rng.randint(1, 1024) / 1024 for _ in range(NX)] for _ in range(NY)] for _ in range(9)]
def collide(P, source=None):
"""Mass-conserving stand-in: rotate populations within each cell (+ optional source)."""
D = [[[P[(q + 1) % 9][y][x] for x in range(NX)] for y in range(NY)] for q in range(9)]
if source:
(x, y), s = source
D[0][y][x] += s
return D
def link(interior):
"""(x, y, q) with x in A and x - c_q inside (seam) or outside (edge) A."""
for (x, y) in sorted(A):
for q in range(1, 9):
src = ((x - al.CX[q]) % NX, (y - al.CY[q]) % NY)
if (src in A) == interior:
return x, y, q
raise AssertionError
class Ledger(unittest.TestCase):
def setUp(self):
self.O = owner()
self.P = al.pull(self.O, NX, NY)
def run_ledger(self, P, D):
return al.ledger(self.O, P, D, A, NX, NY)
def test_ideal_pull_has_no_h_and_closes(self):
r = self.run_ledger(self.P, collide(self.P))
self.assertEqual((r["H_seam"], r["H_edge"], r["C"], r["residual"]), (0, 0, 0, 0))
self.assertEqual(r["dM"], -r["Q_exact"])
self.assertNotEqual(r["Q_exact"], 0)
def test_collision_source_is_c(self):
x, y = sorted(A)[3]
r = self.run_ledger(self.P, collide(self.P, ((x, y), DELTA)))
self.assertEqual((r["C"], r["H"], r["residual"]), (DELTA, 0, 0))
def test_interior_seam_perturbation(self):
x, y, q = link(interior=True)
self.P[q][y][x] += DELTA
r = self.run_ledger(self.P, collide(self.P))
self.assertEqual((r["H_seam"], r["H_edge"], r["residual"]), (DELTA, 0, 0))
# Invisible to any flux through the edge of A; only H explains the mass change.
self.assertEqual(al.staged_flux(self.O, self.P, A, NX, NY), r["Q_exact"])
self.assertEqual(r["dM"] + r["Q_exact"], DELTA)
def test_edge_perturbation_and_staged_flux_double_count(self):
x, y, q = link(interior=False)
self.P[q][y][x] += DELTA
r = self.run_ledger(self.P, collide(self.P))
self.assertEqual((r["H_seam"], r["H_edge"], r["residual"]), (0, DELTA, 0))
staged = al.staged_flux(self.O, self.P, A, NX, NY)
self.assertEqual(staged, r["Q_exact"] - DELTA)
# Staged flux + full H counts the staging change twice.
self.assertEqual(r["dM"] + staged - r["C"] - r["H"], -DELTA)
# Staged flux alone closes only without the edge part of H.
self.assertEqual(r["dM"] + staged - r["C"] - r["H_seam"], 0)
def test_owner_snapshot_after_staging_hides_the_change(self):
# Snapshot taken after staging wrote the same slot into the owner image.
x, y, q = link(interior=False)
sx, sy = (x - al.CX[q]) % NX, (y - al.CY[q]) % NY
self.P[q][y][x] += DELTA
late = [[row[:] for row in plane] for plane in self.O]
late[q][sy][sx] += DELTA
r = al.ledger(late, self.P, collide(self.P), A, NX, NY)
self.assertEqual((r["H"], r["residual"]), (0, 0))
def test_wrong_pull_direction_is_flagged(self):
# Indexing error (push instead of pull): H is nonzero with no physical cause.
bad = [[[self.O[q][(y + al.CY[q]) % NY][(x + al.CX[q]) % NX] for x in range(NX)]
for y in range(NY)] for q in range(9)]
r = self.run_ledger(bad, collide(bad))
self.assertNotEqual(r["H"], 0)
self.assertEqual(r["residual"], 0)
if __name__ == "__main__":
unittest.main()
-79
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@@ -1,79 +0,0 @@
"""CPU-only contract tests for run_dfg_re20. Not CUDA or DFG acceptance evidence."""
import sys
from pathlib import Path
import unittest
sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "validation"))
import run_dfg_re20 as v # noqa: E402
import run_refined_dfg as rr # noqa: E402
h, _ = rr.helpers(rr.DEFAULT_SOURCE)
def rows(values, tstar_end=v.TSTAR_MAX):
n = int(round(tstar_end / v.SAMPLE_TSTAR))
return [dict(tstar=(i + 1) * v.SAMPLE_TSTAR, **values(i)) for i in range(n)]
class Re20Contract(unittest.TestCase):
def test_lattice_parameters_and_bounds(self):
root, uniform = v.lattice_parameters(40), v.lattice_parameters(80)
self.assertAlmostEqual(root["tau"], 0.56, places=12)
self.assertAlmostEqual(uniform["tau"], 0.62, places=12)
self.assertEqual((root["steps"], root["interval"]), (240000, 2000))
self.assertEqual((uniform["steps"], uniform["interval"]), (480000, 4000))
self.assertAlmostEqual(v.plan()["refined_fine_tau"], 0.62, places=12)
def test_config_only_changes_viscosity(self):
base = v._re100_config(h, 40, "SRT", "none")
cfg, body, p = v.config(h, 40, "SRT")
self.assertAlmostEqual(cfg["physics"]["viscosity"], 0.01 * 40 / 20, places=15)
self.assertEqual((p["re"], p["viscosity"]), (20.0, cfg["physics"]["viscosity"]))
base[0]["physics"]["viscosity"] = cfg["physics"]["viscosity"]
self.assertEqual(base[0], cfg)
self.assertEqual(base[1], body)
with self.assertRaisesRegex(ValueError, "no Jets"):
v.config(h, 40, "MRT", "zero")
def test_units(self):
s = v.sample([2.0, -0.5], 4, 40, 3.0)
den = rr.SPEED**2 * 40 / 2
self.assertAlmostEqual(s["cd"], 2.0 / 4 / den)
self.assertAlmostEqual(s["cl"], -0.5 / 4 / den)
self.assertAlmostEqual(s["p_diff"], 3.0 * 0.04)
self.assertEqual(s["dp_scaled"], 3.0)
def test_steady_and_verdict(self):
inside = dict(cd=5.58, cl=0.0106, p_diff=0.1174)
out = v.summarize(rows(lambda i: inside))
self.assertEqual((out["status"], out["steady"], out["window_samples"]),
("WITHIN_INTERVALS", True, 21))
self.assertTrue(out["cd_positive"])
self.assertAlmostEqual(out["edge_distance"]["cl"], 0.0002)
self.assertTrue(all(out["verdict"].values()))
low = v.summarize(rows(lambda i: dict(inside, cl=0.0100)))
self.assertEqual(low["status"], "OUTSIDE_INTERVALS")
self.assertFalse(low["verdict"]["cl"])
def test_slow_drift_gives_no_verdict(self):
# Range 2e-5 passes (limit 6e-5); slope * window 2e-5 exceeds 1.2e-5.
out = v.summarize(rows(lambda i: dict(cd=5.58, cl=0.0106 + 1e-6 * i, p_diff=0.1174)))
self.assertEqual((out["status"], out["verdict"]), ("NOT_STEADY", None))
self.assertLessEqual(out["ranges"]["cl"], out["range_limits"]["cl"])
self.assertGreater(out["drifts"]["cl"], out["slope_limits"]["cl"])
def test_noise_range(self):
quiet = v.summarize(rows(lambda i: dict(cd=5.58, cl=0.0106 + 2e-5 * (i % 2), p_diff=0.1174)))
self.assertTrue(quiet["steady"]) # within the range limit, no trend
noisy = v.summarize(rows(lambda i: dict(cd=5.58, cl=0.0106 + 1e-4 * (i % 2), p_diff=0.1174)))
self.assertEqual(noisy["status"], "NOT_STEADY")
self.assertGreater(noisy["ranges"]["cl"], noisy["range_limits"]["cl"])
def test_incomplete_run_gives_no_verdict(self):
out = v.summarize(rows(lambda i: dict(cd=5.58, cl=0.0106, p_diff=0.1174), tstar_end=30))
self.assertEqual((out["status"], out["verdict"]), ("INCOMPLETE", None))
if __name__ == "__main__":
unittest.main()
-34
View File
@@ -16,7 +16,6 @@ from run_jet_circle_cv import (
case,
state,
cv,
cv_from_macros,
aperture_probe,
measured_aperture_flux,
verify,
@@ -29,39 +28,6 @@ def eq(rho, u, v):
class Host(unittest.TestCase):
def test_public_macros_pressure_advection_and_cropped_frames(self):
for h, origin, shape, rect in (
(.5, (0., 0.), (48, 64), (5., 4., 25., 20.)),
(.5, (.25, .5), (48, 64), (5.25, 4., 25.25, 20.)),
(.25, (.375, .75), (96, 128), (5.125, 4., 25.125, 20.)),
):
y, x = np.indices(shape)
x = origin[0] + h * (x + .5)
k, u, v = 1e-5, .02, -.01
rho = 1 + 3 * k * x # p=(rho-1)/3=k*x
ux, uy, fluid = np.full(shape, u), np.full(shape, v), np.ones(shape, bool)
result = cv_from_macros(rho, ux, uy, fluid, origin, rect, .004, h)
expected = 320 * np.array([3*k*u, k + 3*k*u*u, 3*k*u*v])
np.testing.assert_allclose(result[1], expected, rtol=1e-11, atol=1e-13)
np.testing.assert_allclose(result, cv(eq(rho, u, v), fluid, origin, rect, .004, h), atol=1e-12)
x0, y0, x1, y1 = np.rint((np.array(rect)-np.tile(origin, 2))/h).astype(int)
selection = np.s_[y0-2:y1+2, x0-2:x1+2]
cropped_origin = np.asarray(origin) + h*np.array([x0-2, y0-2])
cropped = cv_from_macros(rho[selection], ux[selection], uy[selection],
fluid[selection], cropped_origin, rect, .004, h)
np.testing.assert_array_equal(cropped, result)
def test_public_macros_full_normal_viscous_stress(self):
y, x = np.indices((48, 64))
x = (x + .5) * .5
rho, ux, uy, fluid = np.ones_like(x), 1e-4*x*x, np.zeros_like(x), np.ones(x.shape, bool)
args = (rho, ux, uy, fluid, (0., 0.), (5., 4., 25., 20.))
_, viscous = cv_from_macros(*args, .004)
_, inviscid = cv_from_macros(*args, 0.)
np.testing.assert_allclose(viscous-inviscid, [0, -4*.004*1e-4*320, 0], atol=1e-13)
with self.assertRaisesRegex(ValueError, "matching 2D"):
cv_from_macros(rho, ux, uy[:-1], fluid, (0, 0), (5, 4, 25, 20), .004)
def test_descriptor_and_uniform_closed_flux(self):
from CelerisLab.lbm.descriptors import D2Q9_EX, D2Q9_EY
-49
View File
@@ -188,55 +188,6 @@ def jet_case(device, jets):
return field, bodies
def test_public_surface_exchange_for_jet_preserves_aperture_at_zero_and_reverse(device):
from CelerisLab.simulation import Simulation
jet = Jet(Sector(CENTER, 0., .6, 3.), Radial(CENTER, inward=False), "quartic", 2e-3)
field, bodies = jet_case(device, [jet])
sim = SimpleNamespace(bodies=bodies, field=field, _initialized=True,
stream=SimpleNamespace(synchronize=device.synchronize))
cl = field.curved
assert bodies.get(0).surface_actuation is None
aperture, velocity = cl.aperture, cl.surface_velocity.copy()
assert aperture.any() and (~aperture).any()
# Synthetic per-link exchanges test readback/splitting, not kernel physics.
values = np.arange(cl.count * 3, dtype=np.float32).reshape(-1, 3)
device.htod(cl.link_exchange_gpu, values)
for amplitude in (2e-3, 0., -1e-3):
Simulation.set_jet_amplitude(sim, 0, amplitude)
result = Simulation.read_surface_exchange(sim, 0)
assert cl.aperture is aperture
np.testing.assert_array_equal(aperture, cl.jet_id >= 0)
np.testing.assert_allclose(cl.surface_velocity, velocity * (amplitude / 2e-3))
for name, mask in (("wall", ~aperture), ("aperture", aperture)):
np.testing.assert_array_equal(result[name], values[mask].sum(axis=0, dtype=np.float64))
def test_public_surface_exchange_keeps_legacy_and_passive_guards(device):
from CelerisLab.simulation import Simulation
field = make_field(device)
bodies = manager(field, [circle(SurfaceActuation(0., .6, .002), radius=2.)])
bodies.sync_to_gpu(field)
sim = SimpleNamespace(bodies=bodies, field=field,
stream=SimpleNamespace(synchronize=device.synchronize))
for value in Simulation.read_surface_exchange(sim, 0).values():
np.testing.assert_array_equal(value, 0.)
field.curved.free_gpu_columns()
with pytest.raises(RuntimeError, match="diagnostic is allocated"):
Simulation.read_surface_exchange(sim, 0)
# An exchange buffer elsewhere in the scene must not admit a passive body.
for jets in ([], [Jet(Sector(CENTER, 0., .6, 3.), Radial(CENTER))]):
field, bodies = jet_case(device, jets)
passive = bodies.add(circle(center=(2., 3.), radius=.6))
bodies.sync_to_gpu(field)
sim.bodies, sim.field = bodies, field
with pytest.raises(ValueError, match="Body has no surface actuation"):
Simulation.read_surface_exchange(sim, passive)
if not jets:
with pytest.raises(ValueError, match="Body has no surface actuation"):
Simulation.read_surface_exchange(sim, 0)
def test_manager_passes_true_hits_and_reuploads_only_velocity(device):
# CPU memory double only: checks host/device bookkeeping, not GPU numerics.
jet = Jet(Sector(CENTER, 0., .6, 3.), Radial(CENTER, inward=False), "quartic", 2e-3)
+4 -174
View File
@@ -146,26 +146,23 @@ def test_full_requires_completed_pilot():
r.verify_pilot(None, r.verify_source(r.DEFAULT_SOURCE, "MRT", "window"))
def pilot_fixture(path, observation_mode="window", jet_scenario="none", case_selection="both", uniform_diameter=80, placement="wide"):
def pilot_fixture(path, observation_mode="window"):
"""Synthetic contract fixture only; never a physical result or run receipt."""
manifest = (r.verify_source(r.DEFAULT_SOURCE, "MRT", "window", jet_scenario)
manifest = (r.verify_source(r.DEFAULT_SOURCE, "MRT", "window")
if observation_mode == "window" else
json.loads((r.HERE / "data/refined_dfg/source_manifest_mrt.json").read_text()))
selection = dict(case_selection=case_selection, uniform_diameter=uniform_diameter, placement=placement)
(path / "plan.json").write_text(
json.dumps(
dict(
source_manifest=manifest,
**selection,
collision="MRT",
jet_scenario=jet_scenario,
observation_mode=observation_mode,
bounds_root_edge=list(r.PLACEMENTS[placement]),
bounds_root_edge=list(r.BOUNDS),
runner_sha256=r.runner_hash(),
)
)
)
for case, diameter in r.selected_cases(case_selection, uniform_diameter):
for case, diameter in (("uniform", 80), ("refined", 40)):
dest = path / case
dest.mkdir()
interval = round(0.02 * diameter / r.SPEED)
@@ -192,9 +189,7 @@ def pilot_fixture(path, observation_mode="window", jet_scenario="none", case_sel
json.dumps(
dict(
case=case,
**selection,
collision="MRT",
jet_scenario=jet_scenario,
observation_mode=observation_mode,
mode="pilot",
status="pilot_complete",
@@ -211,9 +206,7 @@ def pilot_fixture(path, observation_mode="window", jet_scenario="none", case_sel
json.dumps(
dict(
case=case,
**selection,
collision="MRT",
jet_scenario=jet_scenario,
observation_mode=observation_mode,
mode="pilot",
step=interval,
@@ -458,169 +451,6 @@ def test_window_contract_rejection():
assert not backend.events
def test_public_jet_configuration_and_geometry():
for diameter, center, radius in ((40, (80.5, 81), 20), (80, (160, 160.5), 40)):
cfg, _, _ = r.config(h, diameter, "MRT", "fixed")
assert not cfg["method"]["ddf_shifting"] and not cfg["method"]["les"]["enabled"]
jets = r.public_jets(center, radius, "fixed")
assert [j.amplitude for j in jets] == [.001, -.001]
assert all(j.field.inward is False and j.profile == "parabolic" for j in jets)
assert all(j.region.r_max == radius * 1.005 for j in jets)
assert all(j.amplitude == 0 for j in r.public_jets(center, radius, "zero"))
cfg, _, _, host = r.host_geometry(r.DEFAULT_SOURCE, h, "MRT", "fixed")
assert not cfg.ddf_shifting and len(host.boundary_cells) > 0
assert r.public_jets((0, 0), 1, "none") == ()
with unittest.TestCase().assertRaises(ValueError):
r.config(h, 40, "SRT", "fixed")
def test_public_jet_reversal_boundary_and_windows():
from types import SimpleNamespace
calls = []
handle = SimpleNamespace(set_jet_amplitude=lambda i, a: calls.append((i, a)))
for diameter in (40, 80):
boundary = round(250 * diameter / r.SPEED)
assert r.jet_interval(handle, "fixed", boundary - 3, 80, diameter) == (3, None)
switch = round(300 * diameter / r.SPEED)
assert r.jet_interval(handle, "reverse", switch - 3, 80, diameter) == (3, None)
assert not calls
n, event = r.jet_interval(handle, "reverse", switch, 80, diameter)
assert n == 80 and event["step"] == switch and event["tstar"] == 300
assert calls == [(0, -.001), (1, .001)]
calls.clear()
assert r.jet_interval(handle, "reverse", switch + 80, 80, diameter) == (80, None)
assert r.jet_interval(handle, "fixed", switch, 80, diameter) == (80, None)
assert not calls
rows = [dict(tstar=t, tstar_force=t - .5, cd=2.0, cl=-.1) for t in range(251, 306)]
windows = r.jet_diagnostics(rows, "reverse")
assert len(windows) == 6 and all(w["complete"] for w in windows)
assert all(w["cd"]["mean"] == 2 and np.isclose(w["cl"]["mean"], -.1) for w in windows)
assert windows[-1]["covered_tstar"] == 5
with unittest.TestCase().assertRaisesRegex(ValueError, "crosses"):
r.jet_diagnostics([dict(tstar=250.5, tstar_force=250, cd=1, cl=0)], "fixed")
assert r.plan(h, "MRT", "window", "reverse")["modes"]["full_tstar"] == 305
def test_public_jet_source_and_pilot_separation():
from tempfile import TemporaryDirectory
with TemporaryDirectory() as tmp:
path = Path(tmp)
manifest = pilot_fixture(path, jet_scenario="fixed")
assert manifest["source_capture"].startswith("current checkout")
assert len(manifest["checkout_revision"]) == 40
assert r.verify_pilot(path, manifest, "MRT", "window", "fixed") == 3606.0
for scenario in ("none", "zero", "reverse"):
with unittest.TestCase().assertRaisesRegex(ValueError, "Jet scenario"):
r.verify_pilot(path, manifest, "MRT", "window", scenario)
for relative in ("uniform/summary.json", "refined/ready.json"):
receipt = path / relative
record = json.loads(receipt.read_text())
receipt.write_text(json.dumps(dict(record, jet_scenario="zero")))
with unittest.TestCase().assertRaises(ValueError):
r.verify_pilot(path, manifest, "MRT", "window", "fixed")
receipt.write_text(json.dumps(record))
with unittest.TestCase().assertRaises(ValueError):
r.verify_source(r.DEFAULT_SOURCE, "MRT", "last_base_step", "fixed")
def test_cv_snapshot_common_units_and_window_endpoints():
records = []
for refined, shape, origin, diameter, impulse in (
(True, (240, 568), (38., 22.), 40, [4., -8.]),
(False, (330, 1761), (.25, .5), 80, [16., -32.]),
(False, (658, 3521), (.375, .75), 160, [64., -128.]),
):
rho, ux, uy, fluid = np.ones(shape), np.full(shape, .01), np.zeros(shape), np.ones(shape, bool)
begin, n = round(290*diameter/r.SPEED), round(.02*diameter/r.SPEED)
record = r.cv_snapshot(rho, ux, uy, fluid, origin, refined, begin, n, diameter, impulse)
records.append(record)
np.testing.assert_allclose(record["outward_flux"], 0, atol=1e-12)
assert r.cv_selected(begin, diameter, "full") and not r.cv_selected(begin-n, diameter, "full")
end = round(300*diameter/r.SPEED)
assert r.cv_selected(end, diameter, "full") and not r.cv_selected(end+n, diameter, "full")
assert r.cv_selected(n, diameter, "pilot")
assert sum(r.cv_selected(step, diameter, "full") for step in range(begin-n, end+n+1, n)) == 501
for key in ("time_root", "interval_start_root", "interval_dt_root", "interval_impulse_root", "inventory"):
for record in records[1:]:
np.testing.assert_allclose(records[0][key], record[key], rtol=0, atol=1e-10)
assert records[0]["interval_dt_root"] == 80 and np.isclose(records[0]["tstar"], 290.02)
np.testing.assert_array_equal(records[0]["interval_impulse_root"], [4, -8])
def test_cv_pilot_mode_and_helper_provenance():
from tempfile import TemporaryDirectory
manifest = r.verify_source(r.DEFAULT_SOURCE, "MRT", "window", "fixed", True)
assert "tests/validation/run_jet_circle_cv.py" in manifest["sha256"]
with TemporaryDirectory() as tmp:
path = Path(tmp)
old = pilot_fixture(path, jet_scenario="fixed")
with unittest.TestCase().assertRaisesRegex(ValueError, "CV observation mode"):
r.verify_pilot(path, old, "MRT", "window", "fixed", True)
for relative in ("plan.json", "uniform/summary.json", "refined/summary.json",
"uniform/ready.json", "refined/ready.json"):
file = path / relative
record = json.loads(file.read_text())
record.update(observe_cv=True, cv_samples=250)
if relative == "plan.json":
record["source_manifest"] = manifest
file.write_text(json.dumps(record))
assert r.verify_pilot(path, manifest, "MRT", "window", "fixed", True) == 3606
def test_compact_geometry_and_cv_stencils():
from CelerisLab.lbm.refinement import ACTIVE
from CelerisLab.lbm.descriptors import SOLID
_, pair, _, host = r.host_geometry(r.DEFAULT_SOURCE, h, "MRT", "fixed", "compact")
assert pair.fine_shape == (168, 168) and tuple(pair.fine_origin) == (46, 46)
fluid = (pair.fine_kind == ACTIVE) & ((host.flags.reshape(pair.fine_shape) & SOLID) == 0)
rho, ux, uy = np.ones(pair.fine_shape), np.full(pair.fine_shape, .01), np.zeros(pair.fine_shape)
record = r.cv_snapshot(rho, ux, uy, fluid, pair.fine_origin, True, 1160000, 80, 40, [1, 2], "compact")
np.testing.assert_allclose(record["outward_flux"], 0, atol=1e-12)
stencil = np.zeros(pair.fine_shape, bool)
for rect in r.cv_contours(True, 40, "compact"):
x0, y0, x1, y1 = np.rint((rect - np.tile(pair.fine_origin, 2))/.5).astype(int)
stencil[y0-2:y1+2, x0-2:x0+2] = stencil[y0-2:y1+2, x1-2:x1+2] = True
stencil[y0-2:y0+2, x0-2:x1+2] = stencil[y1-2:y1+2, x0-2:x1+2] = True
assert fluid[stencil].all() and not stencil.ravel()[host.transfer_fine_cells].any()
def test_d160_config_and_single_case_receipts():
from tempfile import TemporaryDirectory
from unittest.mock import patch
cfg, _, p = r.config(h, 160, "MRT", "fixed")
assert (p["nx"], p["ny"], p["center"], p["radius"]) == (3521, 658, [320, 320.5], 80)
assert p["viscosity"] == .016 and p["mean_speed"] == .01 and not cfg["method"]["ddf_shifting"]
assert r.uniform_origin(160) == (.375, .75)
np.testing.assert_array_equal(r.cv_contours(False, 160), r.CV_CONTOURS + [.125, 0, .125, 0])
for scenario, expected_exit in (("fixed", 0), ("zero", 2)):
with TemporaryDirectory() as tmp:
path = Path(tmp)
manifest = pilot_fixture(path, jet_scenario=scenario, case_selection="uniform", uniform_diameter=160)
assert r.verify_pilot(path, manifest, "MRT", "window", scenario, False, "uniform", 160) == 1803
for selection, diameter, placement in (("both", 160, "wide"), ("uniform", 80, "wide"), ("uniform", 160, "compact")):
with unittest.TestCase().assertRaises(ValueError):
r.verify_pilot(path, manifest, "MRT", "window", scenario, False, selection, diameter, placement)
# Synthetic dispatch/result check: no CUDA imports or execution.
output = path / "full"
argv = ["runner", "--collision", "MRT", "--exchange-window", "--jet-scenario", scenario,
"--case", "uniform", "--uniform-diameter", "160", "--mode", "full",
"--pilot-results", str(path), "--output", str(output), "--max-wall-seconds", "10", "--gpu-gates-approved"]
result = dict(case="uniform", healthy=True, periodic=scenario == "zero", jet_diagnostic_windows=[],
status="driven_diagnostics_complete" if scenario == "fixed" else "periodic",
reference_comparison=dict(reference_agreement=False))
with patch.object(sys, "argv", argv), patch.dict(r.os.environ, CUDA_VISIBLE_DEVICES="mock-no-gpu"), \
patch.object(r, "run_case", return_value=result) as run:
assert r.main() == expected_exit and run.call_count == 1
comparison = json.loads((output / "comparison.json").read_text())
assert comparison["matched_case_pass"] is False and "refined_vs_uniform" not in comparison
assert comparison["status"].startswith("single_case_")
if __name__ == "__main__":
suite = unittest.TestSuite(
unittest.FunctionTestCase(fn)
-75
View File
@@ -238,81 +238,6 @@ def test_overlapping_force_regions_rejected(device):
bodies.build_compact_lists(bodies.build_flags(field.flag))
@pytest.mark.parametrize("second_x,error", [(14., "unique cut-link writers"),
(17., "active fluid receivers")])
def test_passive_overlap_rejected_before_publishing_lists(second_x, error):
cfg = LBMConfig(nx=32, ny=24)
cfg.validate()
bodies = ObjectManager(cfg.nx, cfg.ny, cfg.nz, cfg.nq, cfg)
for x in (14., second_x):
bodies.add(obj(x=x, y=12., r=4.3))
bodies.add(obj(x=4., y=4., r=2., is_sensor=True))
counts = np.full(bodies.count, 91, np.int32)
hits = []
flags = bodies.build_flags(np.full(cfg.nx * cfg.ny, FLUID, np.uint16))
for domain_flags in (flags, None):
with pytest.raises(ValueError, match=error):
bodies.build_compact_lists_for(bodies.objects, domain_flags,
sensor_cell_counts_out=counts, hits_out=hits)
np.testing.assert_array_equal(counts, 91)
assert hits == []
@pytest.mark.parametrize("centers", [((10., 12.), (22., 12.)),
((10.5, 12.), (19.5, 12.))])
def test_separated_passive_bodies_keep_valid_writers(centers):
# The second case has a subcell physical gap with a resolved fluid column.
cfg = LBMConfig(nx=32, ny=24)
cfg.validate()
bodies = ObjectManager(cfg.nx, cfg.ny, cfg.nz, cfg.nq, cfg)
for x, y in centers:
bodies.add(obj(x=x, y=y, r=4.3))
flags = bodies.build_flags(np.full(cfg.nx * cfg.ny, FLUID, np.uint16))
indices, directions, _, ids, *_ = bodies.build_compact_lists(flags)
assert set(ids) == {0, 1}
assert np.all(flags[indices] & FLUID) and not np.any(flags[indices] & SOLID)
assert len(np.unique(indices.astype(np.uint64) * cfg.nq + directions)) == len(indices)
@pytest.mark.parametrize("entry", ["sync", "initialize", "runtime_edit"])
@pytest.mark.parametrize("second_x", [5., 6.])
def test_passive_overlap_failure_keeps_live_state(device, entry, second_x):
from CelerisLab.simulation import Simulation
field = make_field(device)
bodies = manager(field, [obj(), obj(x=9., y=3., r=1., is_sensor=True)])
bodies.sync_to_gpu(field)
overlapping = obj(x=second_x)
if entry == "runtime_edit":
bodies.stage_add(overlapping)
else:
bodies.add(overlapping)
objects = bodies.objects
flags, curved, counts = field.flag.copy(), field.curved.fluid_idx.copy(), bodies.sensor_cell_counts.copy()
action = bodies.action.copy()
buffers = [(block, bytes(block.data), block.freed) for block in device.blocks]
writes = device.writes
sim = SimpleNamespace(bodies=bodies, field=field, lbm_cfg=field.cfg,
_initialized=entry == "runtime_edit",
_assert_allocation_contract=lambda: None,
stream=SimpleNamespace(synchronize=device.synchronize))
with pytest.raises(ValueError, match="active fluid receivers|unique cut-link writers"):
if entry == "sync":
bodies.sync_to_gpu(field)
elif entry == "initialize":
Simulation.initialize(sim)
else:
Simulation.sync_bodies(sim)
assert bodies.objects == objects
assert bodies.has_pending_edit() == (entry == "runtime_edit")
assert sim._initialized == (entry == "runtime_edit")
assert device.writes == writes and len(device.blocks) == len(buffers)
assert all(bytes(block.data) == data and block.freed == freed for block, data, freed in buffers)
np.testing.assert_array_equal(field.flag, flags)
np.testing.assert_array_equal(field.curved.fluid_idx, curved)
np.testing.assert_array_equal(bodies.sensor_cell_counts, counts)
np.testing.assert_array_equal(bodies.action, action)
def test_action_upload_and_scratch_are_pinned(device):
field = make_field(device, streaming="esopull")
bodies = manager(field, [obj(is_force_region=True)])
-75
View File
@@ -1,75 +0,0 @@
"""Per-hop mass ledger of a fluid cell set A (host-only, stdlib, D2Q9 pull scheme).
Diagnostic definition only; no solver code, no GPU. Arrays are indexed [q][y][x] on a
periodic nx x ny lattice; A is a set of (x, y) ACTIVE cells.
O owner populations before any staging (canonical owner slots, start of the hop)
P populations each cell actually pulls: P[q](x) is what x reads for direction q
(after halo copy, BFL/coalesce staging, ...)
D populations written by the cell after collision
With M0 = sum_{A,q} O and M1 = sum_{A,q} D (both owner snapshots of A):
M1 - M0 + Q_exact = C + H (exact)
C = sum_{x in A, q} (D_q(x) - P_q(x)) collision source
H = sum_{x in A, q} (P_q(x) - O_q(x - c_q)) actual minus ideal owner input,
split into H_seam (x - c_q in A: internal pulls, e.g. tile seams) and
H_edge (x - c_q not in A: inputs crossing the edge of A)
Q_exact = sum_{y in A, y+c_q not in A} O_q(y) - sum_{y not in A, y+c_q in A} O_q(y)
owner-based net outward flux (outgoing minus incoming)
Proof: sum_{A,q} O_q(x - c_q) - M0 = -Q_exact (relabel y = x - c_q per direction), and
sum_{A,q} D = C + H + sum_{A,q} O_q(x - c_q). Q_exact must use O, not staged values: a
flux built from staged inputs already contains H_edge, so adding the full H counts it
twice (see staged_flux). The edge of A must not cross cut links, otherwise O at the solid
end enters Q_exact.
"""
CX = (0, 1, -1, 0, 0, 1, -1, 1, -1)
CY = (0, 0, 0, 1, -1, 1, -1, -1, 1)
def _src(x, y, q, nx, ny):
return (x - CX[q]) % nx, (y - CY[q]) % ny
def pull(O, nx, ny):
"""Ideal pulled input: P[q](x) = O[q](x - c_q)."""
return [[[O[q][_src(x, y, q, nx, ny)[1]][_src(x, y, q, nx, ny)[0]]
for x in range(nx)] for y in range(ny)] for q in range(9)]
def ledger(O, P, D, A, nx, ny):
A = set(A)
out = dict(dM=0.0, C=0.0, H_seam=0.0, H_edge=0.0, Q_exact=0.0)
for (x, y) in A:
for q in range(9):
out["dM"] += D[q][y][x] - O[q][y][x]
out["C"] += D[q][y][x] - P[q][y][x]
sx, sy = _src(x, y, q, nx, ny)
key = "H_seam" if (sx, sy) in A else "H_edge"
out[key] += P[q][y][x] - O[q][sy][sx]
if (sx, sy) not in A:
out["Q_exact"] -= O[q][sy][sx] # incoming owner population
tx, ty = (x + CX[q]) % nx, (y + CY[q]) % ny
if (tx, ty) not in A:
out["Q_exact"] += O[q][y][x] # outgoing owner population
out["H"] = out["H_seam"] + out["H_edge"]
out["residual"] = out["dM"] + out["Q_exact"] - out["C"] - out["H"]
return out
def staged_flux(O, P, A, nx, ny):
"""Outward flux with incoming terms from the staged inputs P (the wrong combination)."""
A = set(A)
q_out = 0.0
for (x, y) in A:
for q in range(9):
sx, sy = _src(x, y, q, nx, ny)
if (sx, sy) not in A:
q_out -= P[q][y][x]
tx, ty = (x + CX[q]) % nx, (y + CY[q]) % ny
if (tx, ty) not in A:
q_out += O[q][y][x]
return q_out
@@ -80,12 +80,11 @@ class ThreeLevelCPU(unittest.TestCase):
f, g = run._levels[1:]
b = g.boundary
events, feeds = [], []
advance, gather = run._advance, run._gather_halo
def record_feed(index, buffer, **kw): # index 2: L1 hop feeds L2
if index == 2:
self.assertIs(buffer, (f.current, f.spare)[len(feeds)])
feeds.append(buffer)
advance(index, buffer, **kw)
advance, gather = run._advance_child, run._gather_halo
def record_feed(buffer, **kw):
self.assertIs(buffer, (f.current, f.spare)[len(feeds)])
feeds.append(buffer)
advance(buffer, **kw)
def record_halo(level, buffer, **kw):
if level is g:
events.append(("halo", buffer))
@@ -96,7 +95,7 @@ class ThreeLevelCPU(unittest.TestCase):
self.assertIs(kind, g.kind)
events.append(("step", src))
g.kernel.side_effect = record_step
with patch.object(run, "_advance", side_effect=record_feed), \
with patch.object(run, "_advance_child", side_effect=record_feed), \
patch.object(run, "_gather_halo", side_effect=record_halo):
run.step()
self.assertEqual(feeds, [f.current, f.spare])
@@ -106,8 +105,8 @@ class ThreeLevelCPU(unittest.TestCase):
self.assertGreater(len(np.unique(b.tables["block"])), 1)
# Negative control: reusing L1's old source at the midpoint must fail.
feeds.clear()
with patch.object(run, "_advance", side_effect=lambda index, buffer, **kw:
record_feed(index, f.current if index == 2 else buffer, **kw)):
with patch.object(run, "_advance_child", side_effect=lambda buffer, **kw:
record_feed(f.current, **kw)):
with self.assertRaises(AssertionError):
run.step()
run.close()
@@ -173,12 +172,11 @@ class ThreeLevelGPU(unittest.TestCase):
p1, p2 = run.patch, run.child_patch
run.initialize(state(16, 16, 1), state(*p1.fine_shape, 2), state(*p2.fine_shape, 3))
f = run._levels[1]
feeds, original = [], run._advance
def record(index, buffer, **kw): # index 2: L1 hop feeds L2
if index == 2:
feeds.append(int(buffer))
original(index, buffer, **kw)
with patch.object(run, "_advance", side_effect=record):
feeds, original = [], run._advance_child
def record(buffer, **kw):
feeds.append(int(buffer))
original(buffer, **kw)
with patch.object(run, "_advance_child", side_effect=record):
cur, spare = int(f.current), int(f.spare)
run.step(1)
self.assertEqual(feeds, [cur, spare]) # current G, then the new G of hop 1
-222
View File
@@ -1,222 +0,0 @@
"""Steady DFG 2D-1 (Re 20): refined and uniform runs against the official reference intervals.
Not a full benchmark certification. Declared deviations from the official setup:
pressure-NEQ outlet (``neq_extrap``) instead of do-nothing, local Zou-He inlet.
Geometry, inflow profile, initial state, refined layout and observation reuse the
pinned Re100 runner (``run_refined_dfg``) and ``re100_helpers`` unchanged; only the
lattice viscosity is set for Re 20 (nu = U_lattice * D / 20 at the root level).
Units. The helpers use scaled DFG units with mean inflow speed 1, so
Cd = 2 Fx / (rho U^2 D) and Cl = 2 Fy / (rho U^2 D) are scale-free, and
``pressure_probes`` returns dp / (rho U^2). The official p_diff = p(0.15, 0.2) -
p(0.25, 0.2) uses U = 0.2 m/s, rho = 1, so p_diff = dp * 0.04. Both are reported;
only p_diff is compared with the official interval. Forces use the existing sign
convention: F is the force of the fluid on the cylinder, i.e. the refined raw
exchange impulse (window ledger, ``total.impulse``) or the uniform ``read_force``,
with x along the inflow and y up from the bottom wall. Cd must be positive, and the
official Cl is positive (centre 0.20 below the centreline 0.205), so a flipped sign
shows up as Cl outside its interval.
Sampling. One sample every SAMPLE_TSTAR (t* = U t / D; 0.25 s), taken at the end of
a completed root step with all levels synchronized; the step index is recorded. Cd
and Cl are means over the sample interval (window exchange ledger refined, per-batch
forces uniform), which filters acoustic and step-parity oscillation; p_diff is the
end-of-interval value at the exact surface points.
Steady rule (our engineering choice, frozen before any run; not official). Over the
trailing WINDOW_TSTAR (t* 50..60 inclusive, 21 samples), for each of Cd, Cl and
p_diff: range (max - min) <= 10 % and |least-squares slope * window| <= 2 % of the
width of its official interval. Absolute limits, so the small Cl is never a divisor;
the slope term bounds slow monotone drift that the range alone would pass. If the
rule fails at TSTAR_MAX the run reports "not steady" and gives no interval verdict;
limits are never relaxed after a run. The verdict uses the window mean, and the
distance of each mean to its nearest interval edge is reported (negative outside).
"""
import argparse
import json
import math
import os
from pathlib import Path
import sys
import time
from tempfile import TemporaryDirectory
import numpy as np
HERE = Path(__file__).resolve().parent
sys.path.insert(0, str(HERE))
import run_refined_dfg as rr # noqa: E402
RE = 20.0
U_PHYS = 0.2 # m/s mean inflow; rho = 1
TSTAR_MAX = 60.0 # 30 s physical
SAMPLE_TSTAR = 0.5 # 0.25 s
WINDOW_TSTAR = 10.0 # trailing 5 s, 21 samples
# Schaefer & Turek (1996), 2D-1 lower/upper bounds.
BANDS = dict(cd=(5.57, 5.59), cl=(0.0104, 0.0110), p_diff=(0.1172, 0.1176))
STEADY_RANGE = {k: (hi - lo) / 10 for k, (lo, hi) in BANDS.items()}
STEADY_SLOPE = {k: (hi - lo) / 50 for k, (lo, hi) in BANDS.items()}
DEVIATIONS = ("pressure-NEQ outlet (neq_extrap), not do-nothing", "local Zou-He inlet")
_re100_config = rr.config
def config(h, diameter, collision="SRT", jet_scenario="none"):
"""The pinned Re100 configuration with the lattice viscosity set for Re 20."""
if jet_scenario != "none":
raise ValueError("DFG 2D-1 runs have no Jets")
cfg, body, p = _re100_config(h, diameter, collision, jet_scenario)
nu = p["mean_speed"] * p["diameter"] / RE
cfg["physics"]["viscosity"] = nu
return cfg, body, dict(p, viscosity=nu, re=RE)
def lattice_parameters(diameter, speed=rr.SPEED):
nu = speed * diameter / RE
return dict(viscosity=nu, tau=0.5 + 3 * nu, steps=math.ceil(TSTAR_MAX * diameter / speed),
interval=round(SAMPLE_TSTAR * diameter / speed))
def sample(impulse, n, diameter, dp):
den = rr.SPEED**2 * diameter / 2
return dict(cd=float(impulse[0] / n / den), cl=float(impulse[1] / n / den),
dp_scaled=float(dp), p_diff=float(dp) * U_PHYS**2)
def summarize(rows):
"""Steady rule over the trailing window, then the interval verdict (or none)."""
if not rows or rows[-1]["tstar"] < TSTAR_MAX - 1e-9:
return dict(status="INCOMPLETE", steady=False, verdict=None)
window = [r for r in rows if r["tstar"] >= TSTAR_MAX - WINDOW_TSTAR - 1e-9]
t = np.array([r["tstar"] for r in window])
ranges = {k: max(r[k] for r in window) - min(r[k] for r in window) for k in BANDS}
drifts = {k: abs(np.polyfit(t, [r[k] for r in window], 1)[0]) * WINDOW_TSTAR for k in BANDS}
steady = all(ranges[k] <= STEADY_RANGE[k] and drifts[k] <= STEADY_SLOPE[k] for k in BANDS)
final = {k: float(np.mean([r[k] for r in window])) for k in BANDS}
edge = {k: min(final[k] - BANDS[k][0], BANDS[k][1] - final[k]) for k in BANDS}
result = dict(window_samples=len(window), ranges=ranges, drifts=drifts,
range_limits=STEADY_RANGE, slope_limits=STEADY_SLOPE, steady=steady,
window_mean=final, edge_distance=edge, bands=BANDS,
deviations=DEVIATIONS, cd_positive=final["cd"] > 0)
if not steady:
return dict(result, status="NOT_STEADY", verdict=None)
inside = {k: BANDS[k][0] <= final[k] <= BANDS[k][1] for k in BANDS}
return dict(result, status="WITHIN_INTERVALS" if all(inside.values()) else "OUTSIDE_INTERVALS",
verdict=inside)
def healthy(row):
return row["max_mach"] <= 0.2 and row["rho_min"] >= 0.5 and row["rho_max"] <= 1.5
def run_case(a, h, case):
from contextlib import ExitStack
from CelerisLab.cuda.context import CudaContext
from CelerisLab.lbm.descriptors import FLUID
from CelerisLab.lbm.refinement_stepper import FixedPatchStepper
from CelerisLab.simulation import Simulation
refined = case == "refined"
cfgdict, bodydict, p = config(h, 40 if refined else 80, a.collision)
lp = lattice_parameters(p["diameter"])
rows = []
with ExitStack() as stack:
if refined:
cfg, pair, body, host = rr.host_geometry(a.source, h, a.collision)
context = stack.enter_context(CudaContext(0))
backend = stack.enter_context(FixedPatchStepper(
cfg, rr.PLACEMENTS["wide"], context=context, coarse_boundary="channel",
base_block=rr.BASE_BLOCK, fine_block=rr.FINE_BLOCK, fine_objects=(body,),
observe_raw_exchange=True, observe_window_exchange=True))
from CelerisLab.lbm.channel import channel_masks
from CelerisLab.lbm.refinement import ACTIVE
from CelerisLab.lbm.descriptors import SOLID
masks = [channel_masks(pair.coarse_shape)[0] & ~pair.covered,
(pair.fine_kind == ACTIVE)
& ((host.flags.reshape(pair.fine_shape) & SOLID) == 0)]
backend.initialize(rr.initial_state(pair.coarse_shape, (0.0, 0.0), 1.0, root=True),
rr.initial_state(pair.fine_shape, pair.fine_origin, 0.5))
probe_p = dict(p, center=[(80.5 - pair.fine_origin[0]) / 0.5 - 0.5,
(81.0 - pair.fine_origin[1]) / 0.5 - 0.5], radius=40.0)
else:
tmp = Path(stack.enter_context(TemporaryDirectory()))
(tmp / "lbm.json").write_text(json.dumps(cfgdict))
(tmp / "body.json").write_text(json.dumps(bodydict))
sim = stack.enter_context(Simulation(str(tmp / "lbm.json"), str(tmp / "body.json"),
device_id=0))
sim.initialize()
probe_p = p
fluid = (sim.field.flag.reshape(p["ny"], p["nx"]) & FLUID) != 0
begin = 0
while begin < lp["steps"]:
rr.check_deadline(a.deadline)
n = min(lp["interval"], lp["steps"] - begin)
if refined:
impulse = rr.advance_refined_interval(backend, n, a.deadline, "window")
fields = [rr.macros(g) for g in backend.download()]
rho, ux, uy = fields[1]
fluid = masks[1]
vals = [tuple(v[m] for v in f) for m, f in zip(masks, fields)]
else:
impulse, done = np.zeros(2), 0
while done < n:
batch = min(100, n - done)
sim.run(batch)
impulse += sim.read_force(0).astype(np.float64) * batch
done += batch
m = sim.get_macroscopic()
rho, ux, uy = [np.asarray(m[k], np.float64).reshape(p["ny"], p["nx"])
for k in ("rho", "ux", "uy")]
vals = [(rho[fluid], ux[fluid], uy[fluid])]
begin += n
row = dict(step=begin, tstar=begin * rr.SPEED / p["diameter"],
**sample(impulse, n, p["diameter"],
h.pressure_probes(rho, fluid, probe_p)["dp"]),
rho_min=float(min(v[0].min() for v in vals)),
rho_max=float(max(v[0].max() for v in vals)),
max_mach=float(max(np.sqrt(3 * (v[1]**2 + v[2]**2)).max() for v in vals)))
rr.ensure_finite(row)
rows.append(row)
if not healthy(row):
break
summary = summarize(rows) if healthy(rows[-1]) else dict(status="UNHEALTHY", steady=False,
verdict=None)
return dict(case=case, collision=a.collision, lattice=lp, rows=rows, **summary)
def plan(collision="SRT"):
return dict(re=RE, collision=collision, tstar_max=TSTAR_MAX, sample_tstar=SAMPLE_TSTAR,
window_tstar=WINDOW_TSTAR, bands=BANDS, range_limits=STEADY_RANGE, slope_limits=STEADY_SLOPE,
deviations=DEVIATIONS, pressure_scale=U_PHYS**2,
refined_root=lattice_parameters(40), refined_fine_tau=0.5 + 3 * 2 * rr.SPEED * 40 / RE,
uniform=lattice_parameters(80),
label="compared against the official reference bands (non-canonical neq_extrap outlet, zou_he_local inlet); not a full benchmark certification")
def main():
parser = argparse.ArgumentParser(description=__doc__.splitlines()[0])
parser.add_argument("--case", choices=["refined", "uniform", "both"], default="refined")
parser.add_argument("--collision", choices=["SRT", "MRT"], default="SRT")
parser.add_argument("--source", type=Path, default=rr.DEFAULT_SOURCE)
parser.add_argument("--output", type=Path, required=True)
parser.add_argument("--plan", action="store_true", help="Write the frozen plan; no CUDA")
parser.add_argument("--max-wall-seconds", type=float)
a = parser.parse_args()
a.source = a.source.resolve()
a.output.mkdir(parents=True, exist_ok=False)
(a.output / "plan.json").write_text(json.dumps(plan(a.collision), indent=2, allow_nan=False))
if a.plan:
return
if not a.max_wall_seconds or a.max_wall_seconds <= 0 or not os.environ.get("CUDA_VISIBLE_DEVICES"):
raise SystemExit("GPU run needs --max-wall-seconds > 0 and explicit CUDA_VISIBLE_DEVICES")
h, _ = rr.helpers(a.source)
rr.config = config # host_geometry builds its root configuration through this name
a.deadline = time.monotonic() + a.max_wall_seconds
cases = ["refined", "uniform"] if a.case == "both" else [a.case]
results = [run_case(a, h, case) for case in cases]
(a.output / "result.json").write_text(json.dumps(results, indent=2, allow_nan=False))
if __name__ == "__main__":
main()
+1 -19
View File
@@ -74,25 +74,7 @@ def cv(g, fluid, origin, rectangle, nu, h=0.5):
Cauchy stress from centred velocity gradients, NOT postcollision non-equilibrium.
Rectangle faces lie on cell edges; fluid mask excludes the staircase cylinder.
"""
return _cv_quantities(*moments(g), fluid, origin, rectangle, nu, h)
def cv_from_macros(rho, ux, uy, fluid, origin, rectangle, nu, h=0.5):
"""Same CV calculation from public macros, in one common length/time frame.
``origin`` is the lower cell edge, ``h`` the cell width, and ``nu`` uses
that frame. Returns [mass, Px, Py] inventory and outward total flux.
Crop fields/mask together and translate origin before calling if desired.
No boundary-exchange observation enters this independent estimator.
"""
rho = np.asarray(rho, np.float64)
if rho.ndim != 2 or any(np.shape(v) != rho.shape for v in (ux, uy, fluid)):
raise ValueError("CV macros and fluid mask must have matching 2D shapes")
vel = np.asarray([ux, uy], np.float64)
return _cv_quantities(rho, rho[None] * vel, vel, fluid, origin, rectangle, nu, h)
def _cv_quantities(rho, mom, vel, fluid, origin, rectangle, nu, h):
rho, mom, vel = moments(g)
x0, y0, x1, y1 = np.rint((np.array(rectangle) - np.tile(origin, 2)) / h).astype(int)
np.testing.assert_allclose(
np.array([x0, y0, x1, y1]) * h + np.tile(origin, 2), rectangle, atol=1e-12
+38 -276
View File
@@ -17,109 +17,8 @@ HERE = Path(__file__).resolve().parent
DEFAULT_SOURCE = HERE.parents[1]
BOUNDS = (40, 24, 320, 140)
BASE_BLOCK = (2, 881) # Exact 166 x 881 domain; no geometric padding.
FINE_BLOCK = (8, 8) # Wide 240 x 568 or compact 168 x 168, including fine halos.
FINE_BLOCK = (8, 8) # 240 x 568 including four fine halo cells.
SPEED = 0.01
JET_PEAK = 0.001
JET_WINDOWS = [(t, t + 10) for t in range(250, 300, 10)]
CV_CONTOURS = np.array([(48., 44., 160., 120.), (44., 36., 180., 128.)])
PLACEMENTS = {"wide": BOUNDS, "compact": (48, 48, 128, 128)}
COMPACT_CV_CONTOURS = np.array([(52., 52., 112., 112.), (50., 50., 120., 120.)])
def selected_cases(selection="both", uniform_diameter=80):
return [(case, diameter) for case, diameter in (("uniform", uniform_diameter), ("refined", 40))
if selection in ("both", case)]
def uniform_origin(diameter):
h = 40 / diameter
return (.5 - .5*h, 1 - h)
def cv_contours(refined, diameter, placement="wide"):
contours = CV_CONTOURS if placement == "wide" else COMPACT_CV_CONTOURS
return contours if refined else contours + [20/diameter, 0., 20/diameter, 0.]
def cv_selected(step, diameter, mode):
return mode == "pilot" or round(290 * diameter / SPEED) <= step <= round(300 * diameter / SPEED)
def cv_snapshot(rho, ux, uy, fluid, origin, refined, begin, n, diameter, impulse, placement="wide"):
"""Cropped public macros only; all inventories, fluxes and impulses use root units."""
from run_jet_circle_cv import cv_from_macros
rectangles = cv_contours(refined, diameter, placement)
h_cell = .5 if refined else 40 / diameter
origin = np.asarray(origin, dtype=float)
x0, y0, x1, y1 = np.rint((rectangles[-1] - np.tile(origin, 2)) / h_cell).astype(int)
selection = np.s_[y0-2:y1+2, x0-2:x1+2]
cropped_origin = origin + h_cell * np.array([x0-2, y0-2])
fields = [v[selection] for v in (rho, ux, uy, fluid)]
values = [cv_from_macros(*fields, cropped_origin, rect, .004, h=h_cell)
for rect in rectangles]
h_native = 1.0 if refined else 40 / diameter
return dict(step=begin+n, tstar=(begin+n)*SPEED/diameter,
time_root=(begin+n)*h_native, interval_start_root=begin*h_native,
interval_dt_root=n*h_native,
interval_impulse_root=(np.asarray(impulse)*h_native**2).tolist(),
inventory=[inventory.tolist() for inventory, _ in values],
outward_flux=[flux.tolist() for _, flux in values])
def public_jets(center, radius, scenario):
"""Same physical apertures; caller supplies its public geometry frame."""
if scenario == "none":
return ()
from CelerisLab.body.jets import Jet, Sector, Radial
peak = 0.0 if scenario == "zero" else JET_PEAK
return tuple(
Jet(Sector(center, angle, math.pi / 12, radius * 1.005),
Radial(center, inward=False), "parabolic", amplitude)
for angle, amplitude in ((math.pi / 2, peak), (3 * math.pi / 2, -peak))
)
def jet_interval(handle, scenario, begin, n, diameter):
"""Apply a reversal only at a completed interval boundary, before advancing."""
if scenario != "none":
boundaries = [round(t * diameter / SPEED) for t in (250, 260, 270, 280, 290, 300, 305)]
n = min([n] + [step - begin for step in boundaries if step > begin])
if scenario != "reverse":
return n, None
switch = round(300 * diameter / SPEED)
if begin < switch:
return min(n, switch - begin), None
if begin == switch:
handle.set_jet_amplitude(0, -JET_PEAK)
handle.set_jet_amplitude(1, JET_PEAK)
return n, dict(step=begin, tstar=300.0, amplitudes=[-JET_PEAK, JET_PEAK])
return n, None
def jet_diagnostics(rows, scenario):
"""Raw interval-weighted diagnostics only; no driven-flow qualification gate."""
windows = JET_WINDOWS + ([(300, 305)] if scenario == "reverse" else [])
result = []
for start, end in windows:
selected = [r for r in rows if start <= r["tstar_force"] < end]
if not selected:
continue
if any(2 * r["tstar_force"] - r["tstar"] < start - 1e-9
or r["tstar"] > end + 1e-9 for r in selected):
raise ValueError("Jet diagnostic interval crosses a window boundary")
weights = np.array([2 * (r["tstar"] - r["tstar_force"]) for r in selected])
record = dict(start_tstar=start, end_tstar=end, samples=len(selected),
covered_tstar=float(weights.sum()),
complete=bool(np.isclose(weights.sum(), end - start, rtol=0, atol=1e-9)))
for key in ("cd", "cl"):
values = np.array([r[key] for r in selected])
record[key] = dict(mean=float(np.average(values, weights=weights)),
min=float(values.min()), max=float(values.max()),
rms=float(np.sqrt(np.average(values**2, weights=weights))))
result.append(record)
return result
def helpers(source):
@@ -140,34 +39,26 @@ def helpers(source):
return h, periodic
def config(h, diameter, collision="SRT", jet_scenario="none"):
def config(h, diameter, collision="SRT"):
cfg, body, p = h.make_config(diameter, SPEED, collision, "neq_extrap", "zou_he_local")
cfg["method"]["outlet"]["srt_neq_damp"] = 0.5
if jet_scenario != "none":
if collision != "MRT":
raise ValueError("Public Jet scenarios require MRT")
cfg["method"]["ddf_shifting"] = False
return cfg, body, p
def plan(h, collision="SRT", observation_mode="last_base_step", jet_scenario="none", uniform_diameter=80, placement="wide"):
_, _, c = config(h, 40, collision, jet_scenario)
_, _, f = config(h, uniform_diameter, collision, jet_scenario)
bounds = PLACEMENTS[placement]
x0, y0, x1, y1 = bounds
def plan(h, collision="SRT", observation_mode="last_base_step"):
_, _, c = config(h, 40, collision)
_, _, f = config(h, 80, collision)
x0, y0, x1, y1 = BOUNDS
fine_active = 4 * (x1 - x0) * (y1 - y0)
coarse_uncovered = c["nx"] * c["ny"] - fine_active // 4
return dict(
status="prepared_not_run",
collision=collision,
jet_scenario=jet_scenario,
ddf_shifting=jet_scenario == "none",
observation_mode=observation_mode,
root_gpu_gates_required=True,
root=c,
uniform=f,
bounds_root_edge=list(bounds),
fine_origin_root_edge=[x0 - 2, y0 - 2],
bounds_root_edge=list(BOUNDS),
physical_patch_m=[
(x0 - 0.5) * c["dx"],
(y0 - 1) * c["dx"],
@@ -187,31 +78,19 @@ def plan(h, collision="SRT", observation_mode="last_base_step", jet_scenario="no
physical_viscosity_m2_s=0.001,
finest_dx_m=f["dx"],
finest_dt_s=f["dt"],
refined_finest_dx_m=c["dx"]/2,
refined_finest_dt_s=c["dt"]/2,
approximate_leaf_cell_ratio=(coarse_uncovered + fine_active)
/ (f["nx"] * f["ny"]),
approximate_collision_work_ratio=(coarse_uncovered + 2 * fine_active)
/ ((uniform_diameter/40) * f["nx"] * f["ny"]),
/ (2 * f["nx"] * f["ny"]),
cost_caveat="Geometry-only estimates include ghosts/solids; exclude block halos, transfers, observation and launch overhead. Not measured speedup.",
sampling_offset="Uniform nodes map to root edges X=.5+i*(40/D), Y=1+(j-.5)*(40/D). Refined centers are fine_origin_root_edge+(index+.5)*.5. Body, wall and source planes coincide; compare observables, not pointwise arrays.",
sampling_offset="For origin (38,22), fine physical x=(j+75.5)*dx80 versus uniform i*dx80: half-fine-cell x offset. Fine physical y=(k+42.5)*dx80 equals uniform (l-.5)*dx80 at l=k+43: y samples align. Body, wall and source planes coincide.",
outlet=(
"SRT pressure NEQ, all nine fneq damped by .5, no backflow clamp; noncanonical DFG outlet"
if collision == "SRT" else
"MRT pressure NEQ, unknowns q2/6/8 extrapolated; no backflow clamp; noncanonical DFG outlet"
),
modes={"pilot_tstar": 5.0, "full_tstar": 305.0 if jet_scenario == "reverse" else 300.0},
modes={"pilot_tstar": 5.0, "full_tstar": 300.0},
observation_dense_tstar=0.02,
**(dict(jets=dict(
uniform_origin_node=f["center"], refined_origin_root_edge=[80.5, 81.0],
angles_rad=[math.pi / 2, 3 * math.pi / 2], half_width_rad=math.pi / 12,
radial_extent_over_radius=[0.0, 1.005],
field="Radial(outward)", profile="parabolic", condition="velocity",
initial_amplitudes=[0.0, 0.0] if jet_scenario == "zero" else [JET_PEAK, -JET_PEAK],
reversal_tstar=300.0 if jet_scenario == "reverse" else None,
diagnostic_windows_tstar=JET_WINDOWS + ([(300, 305)] if jet_scenario == "reverse" else []),
transfer="constant", driven_qualification="not assessed",
)) if jet_scenario != "none" else {}),
)
@@ -247,7 +126,7 @@ def initial_state(shape, origin, spacing, height=164.0, speed=SPEED, root=False)
return w * (1 + 3 * cu + 4.5 * cu * cu - 1.5 * velocity * velocity)
def host_geometry(source, h, collision="SRT", jet_scenario="none", placement="wide"):
def host_geometry(source, h, collision="SRT"):
"""Production donor/transfer and complete cut-link checks, without CUDA."""
from CelerisLab.config import load_lbm_config
from CelerisLab.lbm.refinement import FixedPatch2D, prepare_fine_boundary
@@ -260,12 +139,12 @@ def host_geometry(source, h, collision="SRT", jet_scenario="none", placement="wi
from CelerisLab.body.geometry.circle import CircleGeometry
from CelerisLab.body.objects import SimObject
cfgdict, _, _ = config(h, 40, collision, jet_scenario)
cfgdict, _, _ = config(h, 40, collision)
with TemporaryDirectory() as tmp:
p = Path(tmp) / "cfg.json"
p.write_text(json.dumps(cfgdict))
cfg = load_lbm_config(str(p))
pair = FixedPatch2D.from_config(cfg, PLACEMENTS[placement])
pair = FixedPatch2D.from_config(cfg, BOUNDS)
layout = BlockLayout2D.build(cfg.ny, cfg.nx, *BASE_BLOCK)
validate_channel_config(cfg, [BASE_BLOCK, FINE_BLOCK])
targets = blocked_base_tables(pair, layout, np.argsort(pair.coalesce_coarse))[1]
@@ -274,41 +153,18 @@ def host_geometry(source, h, collision="SRT", jet_scenario="none", placement="wi
body = SimObject(
0, geometry=CircleGeometry(80.5, 81.0, 20.0), center=(80.5, 81.0), radius=20.0
)
host = prepare_fine_boundary(
cfg, pair, (body,), jets=public_jets((80.5, 81.0), 20.0, jet_scenario),
_shifted_blocked=jet_scenario == "none",
)
host = prepare_fine_boundary(cfg, pair, (body,), _shifted_blocked=True)
return cfg, pair, body, host
def verify_source(source, collision="SRT", observation_mode="last_base_step", jet_scenario="none", observe_cv=False):
def verify_source(source, collision="SRT", observation_mode="last_base_step"):
if collision not in ("SRT", "MRT"):
raise ValueError("Matched collision must be SRT or MRT")
if observation_mode not in ("last_base_step", "window"):
raise ValueError("Unknown refined observation mode")
if observe_cv and jet_scenario == "none":
raise ValueError("--observe-cv requires an explicit public Jet scenario")
name = ("source_manifest_window.json" if observation_mode == "window" else
"source_manifest.json" if collision == "SRT" else "source_manifest_mrt.json")
expected = json.loads((HERE / "data/refined_dfg" / name).read_text())
if jet_scenario != "none":
if collision != "MRT" or observation_mode != "window":
raise ValueError("Public Jet scenarios require MRT and --exchange-window")
import subprocess
sys.path.insert(0, str(HERE))
from source_provenance import checkout_provenance
paths = set(expected["sha256"])
if observe_cv:
paths.add("tests/validation/run_jet_circle_cv.py")
paths.update(subprocess.check_output(
["git", "-C", str(source), "ls-files", "src"], text=True).splitlines())
return dict(
source_capture="current checkout, not historical DFG qualification",
**checkout_provenance(source), observation_mode=observation_mode,
sha256={name: hashlib.sha256((source / name).read_bytes()).hexdigest()
for name in sorted(paths)},
)
for name, digest in expected["sha256"].items():
if hashlib.sha256((source / name).read_bytes()).hexdigest() != digest:
raise RuntimeError("Source mismatch: " + name)
@@ -363,33 +219,29 @@ def run_case(a, h, periodic, case):
from contextlib import ExitStack
refined = case == "refined"
cfgdict, bodydict, p = config(h, 40 if refined else a.uniform_diameter, a.collision, a.jet_scenario)
cap = 5.0 if a.mode == "pilot" else (305.0 if a.jet_scenario == "reverse" else 300.0)
cfgdict, bodydict, p = config(h, 40 if refined else 80, a.collision)
cap = 5.0 if a.mode == "pilot" else 300.0
max_steps = math.ceil(cap * p["diameter"] / SPEED)
rows = []
healthy = True
step_seconds = 0.0
cv_seconds, cv_samples = 0.0, 0
amplitude_changes = []
started = time.monotonic()
check_deadline(a.deadline)
dest = a.output / case
dest.mkdir()
with ExitStack() as stack:
cv_out = stack.enter_context((dest / "cv_history.jsonl").open("w")) if a.observe_cv else None
if refined:
cfg, pair, body, host = host_geometry(a.source, h, a.collision, a.jet_scenario, a.placement)
cfg, pair, body, host = host_geometry(a.source, h, a.collision)
context = stack.enter_context(CudaContext(0))
backend = stack.enter_context(
FixedPatchStepper(
cfg,
PLACEMENTS[a.placement],
BOUNDS,
context=context,
coarse_boundary="channel",
base_block=BASE_BLOCK,
fine_block=FINE_BLOCK,
fine_objects=(body,),
jets=public_jets((80.5, 81.0), 20.0, a.jet_scenario),
observe_raw_exchange=True,
**({"observe_window_exchange": True} if a.observation_mode == "window" else {}),
)
@@ -422,9 +274,6 @@ def run_case(a, h, periodic, case):
sim = stack.enter_context(
Simulation(str(tmp / "lbm.json"), str(tmp / "body.json"), device_id=0)
)
for index, jet in enumerate(public_jets(p["center"], p["radius"], a.jet_scenario)):
if sim.add_jet(jet) != index:
raise RuntimeError("Unexpected public Jet registration index")
sim.initialize()
probe_p = p
fluid = (sim.field.flag.reshape(p["ny"], p["nx"]) & FLUID) != 0
@@ -441,10 +290,6 @@ def run_case(a, h, periodic, case):
else 0.5
)
n = min(max(1, round(width * p["diameter"] / SPEED)), max_steps - begin)
n, change = jet_interval(backend if refined else sim, a.jet_scenario,
begin, n, p["diameter"])
if change is not None:
amplitude_changes.append(change)
impulse = np.zeros(2)
tick = time.monotonic()
if refined:
@@ -514,19 +359,6 @@ def run_case(a, h, periodic, case):
/ SPEED,
**h.pressure_probes(rho, fluid, probe_p),
)
if a.jet_scenario != "none":
row.update(step_start=begin, tstar_start=begin * SPEED / p["diameter"],
interval_steps=n, impulse_x=float(impulse[0]),
impulse_y=float(impulse[1]))
if a.observe_cv and cv_selected(begin+n, p["diameter"], a.mode):
tick = time.monotonic()
record = cv_snapshot(rho, ux, uy, fluid,
pair.fine_origin if refined else uniform_origin(p["diameter"]),
refined, begin, n, p["diameter"], impulse, a.placement)
cv_out.write(json.dumps(record, allow_nan=False) + "\n")
cv_out.flush()
cv_samples += 1
cv_seconds += time.monotonic() - tick
check_deadline(a.deadline)
ensure_finite(row)
rows.append(row)
@@ -570,24 +402,14 @@ def run_case(a, h, periodic, case):
steps=begin,
startup_seconds=startup,
step_seconds=step_seconds,
observation_and_overhead_seconds=time.monotonic() - started - startup - step_seconds,
wall_seconds=time.monotonic() - started,
force="raw stationary-body link momentum reaction, per-unit-depth; average over entire observation interval; normalized in each base lattice",
mass_units="rho_reference * m^2 per unit depth",
flux_units="rho_reference * m^2/s per unit depth",
pressure="postcollision end-sample; physical pressure difference / (rho_reference * 1 m/s squared)",
suite_validated=False,
**(periodic.assess(rows) if a.jet_scenario in ("none", "zero") else
dict(periodic=False, checks={}, cycles=[])),
**periodic.assess(rows),
)
if a.jet_scenario != "none":
result.update(jet_diagnostic_windows=jet_diagnostics(rows, a.jet_scenario),
amplitude_changes=amplitude_changes,
pressure_classification=("DFG reference verdict retained, including pressure"
if a.jet_scenario == "zero" else "diagnostic only; no official DFG reference gate"))
if a.observe_cv:
result.update(cv_observation_seconds=cv_seconds, cv_samples=cv_samples,
cv_qualification="not assessed; scalar observations only")
if not healthy:
result["periodic"] = False
reference = json.loads(
@@ -603,8 +425,7 @@ def run_case(a, h, periodic, case):
else (
"pilot_complete"
if a.mode == "pilot"
else ("driven_diagnostics_complete" if a.jet_scenario in ("fixed", "reverse") else
"periodic" if result["periodic"] else "incomplete_periodicity")
else ("periodic" if result["periodic"] else "incomplete_periodicity")
)
)
(dest / "summary.json").write_text(json.dumps(result, indent=2, allow_nan=False))
@@ -643,39 +464,27 @@ def check_deadline(deadline):
)
def verify_pilot(path, manifest, collision="SRT", observation_mode="last_base_step", jet_scenario="none", observe_cv=False,
case_selection="both", uniform_diameter=80, placement="wide"):
def verify_pilot(path, manifest, collision="SRT", observation_mode="last_base_step"):
if path is None:
raise ValueError(
"Full comparison requires --pilot-results from a completed matched pilot"
)
previous = read_finite_json(path / "plan.json")
options = dict(case_selection=(case_selection, "both"), uniform_diameter=(uniform_diameter, 80), placement=(placement, "wide"))
if any(previous.get(k, default) != expected for k, (expected, default) in options.items()):
raise ValueError("Pilot case, resolution or placement differs")
if previous.get("observe_cv", False) != observe_cv:
raise ValueError("Pilot CV observation mode differs")
if previous.get("jet_scenario", "none") != jet_scenario:
raise ValueError("Pilot Jet scenario differs")
if previous.get("observation_mode") != observation_mode:
raise ValueError("Pilot observation mode differs")
if previous.get("collision") != collision:
raise ValueError("Pilot collision differs")
if previous["source_manifest"] != manifest or previous["bounds_root_edge"] != list(
PLACEMENTS[placement]
BOUNDS
):
raise ValueError("Pilot source or frozen geometry differs")
if previous.get("runner_sha256") != runner_hash():
raise ValueError("Pilot runner differs")
calibrated_seconds = 0.0
for case, diameter in selected_cases(case_selection, uniform_diameter):
for case, diameter in (("uniform", 80), ("refined", 40)):
summary = read_finite_json(path / case / "summary.json")
if (
any(summary.get(k, default) != expected for k, (expected, default) in options.items())
or summary.get("observe_cv", False) != observe_cv
or (observe_cv and summary.get("cv_samples") != 250)
or summary.get("jet_scenario", "none") != jet_scenario
or summary.get("observation_mode") != observation_mode
summary.get("observation_mode") != observation_mode
or summary.get("collision") != collision
or summary.get("case") != case
or summary.get("mode") != "pilot"
@@ -728,10 +537,7 @@ def verify_pilot(path, manifest, collision="SRT", observation_mode="last_base_st
raise ValueError("Unhealthy pilot observations")
ready = read_finite_json(path / case / "ready.json")
if (
any(ready.get(k, default) != expected for k, (expected, default) in options.items())
or ready.get("observe_cv", False) != observe_cv
or ready.get("jet_scenario", "none") != jet_scenario
or ready.get("observation_mode") != observation_mode
ready.get("observation_mode") != observation_mode
or ready.get("collision") != collision
or ready.get("case") != case
or ready.get("mode") != "pilot"
@@ -749,9 +555,9 @@ def verify_pilot(path, manifest, collision="SRT", observation_mode="last_base_st
or not 0 < stepping <= wall
):
raise ValueError("Invalid pilot calibration timings")
# Full duration is 60 (or 61 with reversal) times pilot; dense sampling makes
# Full physical duration is 60 times pilot; dense pilot sampling makes
# this conservative for the sparser early full observations. Not a guarantee.
calibrated_seconds += startup + (61 if jet_scenario == "reverse" else 60) * (wall - startup)
calibrated_seconds += startup + 60 * (wall - startup)
return 3 * calibrated_seconds
@@ -760,13 +566,6 @@ def main():
parser.add_argument("--exchange-window", action="store_true",
help="Opt in to refined window-ledger observations on the pinned candidate")
parser.add_argument("--collision", choices=["SRT", "MRT"], default="SRT")
parser.add_argument("--case", choices=["both", "uniform", "refined"], default="both")
parser.add_argument("--uniform-diameter", type=int, choices=[80, 160], default=80)
parser.add_argument("--placement", choices=list(PLACEMENTS), default="wide")
parser.add_argument("--jet-scenario", choices=["none", "zero", "fixed", "reverse"],
default="none", help="Opt in to public unshifted MRT Jets; reverse switches at t*=300 and ends at 305")
parser.add_argument("--observe-cv", action="store_true",
help="Record independent cropped-macro CV samples during pilot or full t*=290..300")
parser.add_argument("--source", type=Path, default=DEFAULT_SOURCE)
parser.add_argument("--output", type=Path, required=True)
parser.add_argument("--mode", choices=["plan", "pilot", "full"], default="plan")
@@ -778,26 +577,15 @@ def main():
help="Required explicit campaign wall-time ceiling for GPU execution",
)
a = parser.parse_args()
if a.uniform_diameter == 160 and a.case != "uniform":
raise ValueError("D160 requires --case uniform; no matched-resolution claim")
if a.placement == "compact" and a.case != "refined":
raise ValueError("Compact placement requires --case refined")
if (a.uniform_diameter != 80 or a.placement != "wide") and a.jet_scenario == "none":
raise ValueError("Resolution/placement variants require an explicit public Jet scenario")
a.source = a.source.resolve()
a.observation_mode = "window" if a.exchange_window else "last_base_step"
manifest = verify_source(a.source, a.collision, a.observation_mode, a.jet_scenario, a.observe_cv)
manifest = verify_source(a.source, a.collision, a.observation_mode)
h, periodic = helpers(a.source)
from source_provenance import checkout_provenance
a.provenance = checkout_provenance(a.source)
a.provenance.update(jet_scenario=a.jet_scenario, ddf_shifting=a.jet_scenario == "none")
a.provenance.update(case_selection=a.case, uniform_diameter=a.uniform_diameter, placement=a.placement)
if a.observe_cv:
a.provenance["observe_cv"] = True
calibration = (
verify_pilot(a.pilot_results, manifest, a.collision, a.observation_mode, a.jet_scenario, a.observe_cv,
a.case, a.uniform_diameter, a.placement)
verify_pilot(a.pilot_results, manifest, a.collision, a.observation_mode)
if a.mode == "full" else None
)
if a.mode != "plan" and (
@@ -814,31 +602,17 @@ def main():
if a.output.exists() and any(a.output.iterdir()):
raise ValueError("Output must be empty/new")
a.output.mkdir(parents=True, exist_ok=True)
specification = plan(h, a.collision, a.observation_mode, a.jet_scenario, a.uniform_diameter, a.placement)
specification = plan(h, a.collision, a.observation_mode)
specification.update(
source_manifest=manifest,
**a.provenance,
gates=periodic.GATES if a.jet_scenario in ("none", "zero") else None,
reference_gates=periodic.REFERENCE_GATES if a.jet_scenario in ("none", "zero") else None,
gates=periodic.GATES,
reference_gates=periodic.REFERENCE_GATES,
runner_sha256=runner_hash(),
wall_time_budget_seconds=budget,
full_pilot_calibration_seconds=calibration,
)
if a.observe_cv:
specification["cv_observation"] = dict(
full_tstar=[290, 300], pilot_tstar=[.02, 5], spacing_tstar=.02,
refined_contours_root=cv_contours(True, 40, a.placement).tolist(),
uniform_contours_root=cv_contours(False, a.uniform_diameter, a.placement).tolist(),
uniform_grid_origin_root=uniform_origin(a.uniform_diameter),
refined_grid_origin_root=specification["fine_origin_root_edge"],
cell_width_root={"uniform": 40/a.uniform_diameter, "refined": .5},
viscosity_root=.004, components=["mass", "Px", "Py"],
units="root lattice per unit depth; outward flux per root time",
interval="Impulse belongs to the interval ending at each snapshot; first retained endpoint (pilot .02, full 290) supplies initial inventory only: exclude its preceding impulse",
qualification="not assessed; trapezoidal integration and time-coarsening are offline",
)
if a.case != "uniform":
host_geometry(a.source, h, a.collision, a.jet_scenario, a.placement)
host_geometry(a.source, h, a.collision)
(a.output / "plan.json").write_text(json.dumps(specification, indent=2))
if a.mode == "plan":
return 0
@@ -847,9 +621,8 @@ def main():
"GPU execution blocked: root GPU gates approval and explicit device selection required"
)
results = []
cases = selected_cases(a.case, a.uniform_diameter)
a.deadline = time.monotonic() + budget
for case, _ in cases:
for case in ("uniform", "refined"):
try:
result = run_case(a, h, periodic, case)
except TimeoutError as exc:
@@ -877,12 +650,7 @@ def main():
status="pilot_only" if a.mode == "pilot" else "incomplete",
matched_case_pass=False,
)
if a.jet_scenario in ("fixed", "reverse"):
comparison.update(status=("pilot_only" if a.mode == "pilot" else "driven_diagnostics_complete")
if len(results) == len(cases) and all(r["healthy"] for r in results) else "invalid_state",
qualification="not assessed; execution completion is not physical acceptance",
jet_diagnostic_windows={r["case"]: r["jet_diagnostic_windows"] for r in results})
if a.case == "both" and len(results) == 2 and all(r["healthy"] and r["periodic"] for r in results):
if len(results) == 2 and all(r["healthy"] and r["periodic"] for r in results):
comparison.update(
status="periodic_comparison",
refined_vs_uniform=periodic.compare(
@@ -892,20 +660,14 @@ def main():
comparison["matched_case_pass"] = comparison["refined_vs_uniform"][
"reference_agreement"
]
if a.case != "both":
comparison.update(status="single_case_" + results[0]["status"],
own_reference_comparison=results[0].get("reference_comparison"))
(a.output / "comparison.json").write_text(
json.dumps(comparison, indent=2, allow_nan=False)
)
return (
0
if len(results) == len(cases)
if len(results) == 2
and all(r["healthy"] for r in results)
and (a.mode == "pilot" or comparison["matched_case_pass"]
or a.jet_scenario in ("fixed", "reverse")
or (a.case != "both" and results[0]["periodic"]
and results[0].get("reference_comparison", {}).get("reference_agreement", False)))
and (a.mode == "pilot" or comparison["matched_case_pass"])
else 2
)
@@ -0,0 +1,81 @@
"""Fixed N128 four-case shear-wave contract: U128, U256, constant R128, projected R128.
Shared provenance, build, workload and sample-time checks are reused from
assess_projected_pairs (same cases, source pins and geometry); only the
Taylor-Green-specific checks are replaced by shear-wave metadata and physics.
"""
import argparse
import json
from pathlib import Path
import assess_projected_pairs as tg
import shear_wave as sw
from run_case import SHEAR_WAVE_SHA256
SHARED = ("complete_matrix", "no_extra_cases", "no_duplicate_cases", "finite_receipts",
"same_source_and_harness", "clean_a135252_numerical_source",
"same_recorded_runtime", "same_explicit_device", "same_early_sampling")
PER_CASE = ("complete_times", "scales", "actual_builds", "reference", "runtime_source",
"patch", "workload")
def metadata_ok(record, n):
return (record.get("flow") == "shear_wave" and record.get("mode") == list(sw.MODE)
and record.get("polarization") == sw.E.tolist()
and record.get("angle_deg") == sw.ANGLE_DEG and record.get("phase") == sw.PHI
and record.get("eps") == sw.eps(n)
and record.get("numerics") == tg.NUMERICS
and record.get("initialization") == sw.INITIALIZATION
and record.get("limits") == sw.LIMITS
and record.get("early_pressure") == dict(enabled=False, rows=[],
sampled_max_pressure_l2=None)
and (record.get("source") or {}).get("shear_wave_sha256") == SHEAR_WAVE_SHA256)
def assess(records, expected_revision=None):
if not isinstance(records, list) or not all(isinstance(r, dict) for r in records):
raise ValueError("records must be a list of receipt objects")
base_checks = tg.assess(records, expected_revision)["checks"]
checks = {name: base_checks.get(name, False) for name in SHARED}
indexed = {}
for r in records:
indexed.setdefault(tuple(r.get(k) for k in ("re_L", "n", "depth", "explosion")), r)
for key in tg.CASES:
_, n, depth, scheme = key
label = f"{n}/{depth}/{scheme}"
for name in PER_CASE:
checks[f"{label} {name}"] = base_checks.get(f"{label} {name}", False)
checks[f"{label} shear_metadata"] = key in indexed and metadata_ok(indexed[key], n)
contract_valid = all(checks.values())
result = dict(checks=checks, contract_valid=contract_valid,
cases=[list(k) for k in tg.CASES], expected_revision=expected_revision,
scope="2D periodic Re100 oblique (2,1) shear wave; one phase and one "
"rectangle; no placement robustness or convergence order")
if not contract_valid:
result.update(status="INVALID_SET", passed=False)
return result
try:
physics = sw.assess(indexed[tg.CASES[0]], indexed[tg.CASES[1]],
[indexed[tg.CASES[2]], indexed[tg.CASES[3]]])
except (KeyError, ValueError) as error:
result.update(status="INVALID_SET", passed=False, reason=str(error))
return result
result.update(physics=physics, status=physics["status"],
passed=physics["status"] == "PASS")
return result
if __name__ == "__main__":
p = argparse.ArgumentParser(description=__doc__)
p.add_argument("files", type=Path, nargs=4)
p.add_argument("--output", type=Path, required=True)
p.add_argument("--expected-revision", required=True)
args = p.parse_args()
if args.output.exists():
p.error("Output already exists; choose a new path to retain prior evidence")
result = assess([json.loads(path.read_text()) for path in args.files], args.expected_revision)
text = json.dumps(result, indent=2, allow_nan=False) + "\n"
args.output.write_text(text)
print(text, end="")
raise SystemExit(0 if result["passed"] else 1)
+49 -13
View File
@@ -18,6 +18,30 @@ SOURCE_SHA256 = "a5dbfd804befce868067d79a23e5fd47dce7f505b3f9b1bb2145fb57cb5f217
BUILD_CAPTURE_SHA256 = "3dbaa6547cb0a4cb1541054f3b64ad8b6e18cc70527ac6166e56b944e9bd464a"
REFERENCE_HARNESS = "11901a7f77557a901e017a171eeae1758d584fa5"
INITIALIZATION = "physical FP64 equilibrium G at actual cell centers; rho=1+3p"
SHEAR_WAVE_SHA256 = "81d5c8ee60864372887cddf9239580c82fb6750d956038f1e3ee9de61aa4e877"
def flow_functions(flow="taylor_green"):
"""(initial, metrics, limits, initialization); the default is the frozen TG oracle."""
if flow == "taylor_green":
return initial, metrics, LIMITS, INITIALIZATION
if flow == "shear_wave":
import shear_wave
return shear_wave.initial, shear_wave.metrics, shear_wave.LIMITS, shear_wave.INITIALIZATION
raise ValueError(f"unknown flow {flow!r}")
def finite_row(row):
"""Every scalar or list-valued diagnostic is finite (TG rows are all scalars)."""
return all(np.isfinite(np.asarray(value, dtype=float)).all() for value in row.values())
def sample(run, masks, step, n, viscosity, initial_mass, metrics, depth, label="sample"):
arrays = (run.download(),) if depth == 1 else run.download()
row = metrics(arrays, masks, step, n, viscosity, initial_mass)
if not finite_row(row):
raise FloatingPointError(f"nonfinite {label} diagnostics")
return row
def sample_steps(n, early_pressure=False):
@@ -64,7 +88,7 @@ def provenance(repo):
)
def verify_source(repo, revision):
def verify_source(repo, revision, flow="taylor_green"):
"""Exact clean harness commit, fixed production tree, and reviewed capture helper."""
import oracle
from tests.validation.multigrid import check_projected_pairs as gate
@@ -83,6 +107,13 @@ def verify_source(repo, revision):
if result["source_tree_sha256"] != SOURCE_SHA256:
raise RuntimeError("Wrong numerical source fingerprint")
result["build_capture_sha256"] = BUILD_CAPTURE_SHA256
if flow == "shear_wave":
import shear_wave
module = harness / "shear_wave.py"
if (Path(shear_wave.__file__).resolve() != module
or hashlib.sha256(module.read_bytes()).hexdigest() != SHEAR_WAVE_SHA256):
raise RuntimeError("Wrong shear_wave module checkout or content")
result["shear_wave_sha256"] = SHEAR_WAVE_SHA256
return result
@@ -151,7 +182,11 @@ def main():
p.add_argument("--explosion", choices=["constant", "projected_linear"], default="constant")
p.add_argument("--early-pressure", action="store_true",
help="also save 65 scalar pressure samples at t*=k*.001875, k=0..64")
p.add_argument("--flow", choices=["taylor_green", "shear_wave"], default="taylor_green")
args = p.parse_args()
if args.flow == "shear_wave" and (args.re != 100 or args.depth == 3 or args.early_pressure):
p.error("shear_wave requires --re 100, depth 1 or 2 and no --early-pressure")
initial, metrics, limits, initialization = flow_functions(args.flow)
if args.output.exists():
p.error("Output already exists; choose a new path to retain prior evidence")
if args.explosion != "constant" and args.depth != 2:
@@ -161,7 +196,7 @@ def main():
p.error("--run-gpu and exactly one explicit CUDA_VISIBLE_DEVICES are required")
repo = args.repo.resolve()
sys.path[:0] = [str(repo / "src"), str(repo)]
source = verify_source(repo, args.expected_revision)
source = verify_source(repo, args.expected_revision, args.flow)
runtime = runtime_source(repo)
if args.dry_run:
print(json.dumps(dict(source=source, runtime_source=runtime, dry_run=True)))
@@ -197,7 +232,7 @@ def main():
mach=U * np.sqrt(3),
viscosity=cfg.viscosity,
tau_by_level=[0.5 + 3 * c.viscosity for c in h.configs],
initialization=INITIALIZATION,
initialization=initialization,
numerics=dict(lattice_model=cfg.lattice_model, collision=cfg.collision,
store_precision=cfg.store_precision, ddf_shifting=cfg.ddf_shifting,
streaming=cfg.streaming, les_enabled=cfg.les_enabled,
@@ -205,13 +240,18 @@ def main():
sample_phase="postcollision G at root synchronization"),
cuda_visible_devices=selected,
device_id=0,
limits=LIMITS,
limits=limits,
workload=workload(masks, round(TIMES[-1] * args.n / U)),
rows=[],
early_pressure=dict(enabled=args.early_pressure, rows=[],
sampled_max_pressure_l2=None),
completed=False,
)
if args.flow != "taylor_green":
import shear_wave
report.update(flow=args.flow, mode=list(shear_wave.MODE),
polarization=shear_wave.E.tolist(), angle_deg=shear_wave.ANGLE_DEG,
phase=shear_wave.PHI, eps=shear_wave.eps(args.n))
args.output.parent.mkdir(parents=True, exist_ok=True)
def save():
temporary = args.output.with_suffix(args.output.suffix + ".tmp")
@@ -248,10 +288,8 @@ def main():
initial_mass = None
for step in sorted(set(main_steps + early_steps)):
run.step(step - run.step_count)
arrays = (run.download(),) if args.depth == 1 else run.download()
row = metrics(arrays, masks, step, args.n, cfg.viscosity, initial_mass)
if not all(np.isfinite(value) for value in row.values()):
raise FloatingPointError("nonfinite sample diagnostics")
row = sample(run, masks, step, args.n, cfg.viscosity, initial_mass,
metrics, args.depth)
row["step"] = step
if initial_mass is None:
initial_mass = row["mass"]
@@ -278,10 +316,8 @@ def main():
# Exercise real kernels/halos/transfers on every level before READY.
# This is the first measured trajectory step, not discarded warmup.
run.step(1)
probe = (run.download(),) if args.depth == 1 else run.download()
probe_metrics = metrics(probe, masks, 1, args.n, cfg.viscosity, initial_mass)
if not all(np.isfinite(value) for value in probe_metrics.values()):
raise FloatingPointError("nonfinite READY diagnostics")
sample(run, masks, 1, args.n, cfg.viscosity, initial_mass,
metrics, args.depth, "READY")
report["ready_after_step"] = 1
save()
print(
@@ -301,7 +337,7 @@ def main():
completed=True,
seconds=time.monotonic() - started,
screening_pass=all(
row[key] <= limit for row in report["rows"] for key, limit in LIMITS.items()
row[key] <= limit for row in report["rows"] for key, limit in limits.items()
),
)
save()
+312
View File
@@ -0,0 +1,312 @@
"""CPU-only oblique shear-wave reference and composite-leaf diagnostics.
Convention: integer mode MODE=(2,1) on the L x L periodic root domain, so the
wavevector k = (2*pi/L)*(2,1) points 26.565 deg from +x (mode (1,2) would be
63.435 deg). Velocity is polarized along E = (-1,2)/sqrt(5), perpendicular to k.
The frozen Taylor-Green oracle is reused for constants and geometry only.
"""
import math
import numpy as np
from oracle import CX, CY, W, U, TIMES, centers
MODE = (2, 1)
PHI = 0.0
E = np.array([-MODE[1], MODE[0]], dtype=float) / math.hypot(*MODE)
ANGLE_DEG = math.degrees(math.atan2(MODE[1], MODE[0]))
RE = 100 # Re = U L / nu, the same nu as Taylor-Green Re100 at equal N
FIT_FROM_TSTAR = 0.12 # late-time samples only; reduces startup sensitivity
INITIALIZATION = (
"physical FP64 equilibrium G at actual cell centers; rho=1 (exact p const)"
)
# Per-row screens. phase_drift_abs, residual_l2 and the run-level rate screen
# use eps(n) and are preregistered diagnostic choices, not error bounds.
LIMITS = dict(velocity_l2=0.05, spurious_pressure_scaled=0.02, mass_relative=1e-5)
# The comparative pressure budget max(2*control, 0.02) is never below the 0.02
# absolute ceiling, so it is always redundant; raw control ratios are kept.
FLOORS = dict(rate_error=0.002, residual_l2=0.002, spurious_pressure_scaled=0.02)
BASELINE_FACTOR = 2.0
def wavevector(length):
return 2 * np.pi / length * np.array(MODE, dtype=float)
def decay_rate(length, viscosity):
"""Exact amplitude decay rate per root step: nu |k|^2."""
k = wavevector(length)
return viscosity * float(k @ k)
def eps(n):
"""(|k| h_root)^2 with h_root = 1: dimensionless, coefficient one."""
k = wavevector(n)
return float(k @ k)
def exact(x, y, t, length, viscosity, amplitude=U):
k = wavevector(length)
a = amplitude * np.exp(-decay_rate(length, viscosity) * t)
s = np.sin(k[0] * x + k[1] * y + PHI)
p = np.zeros_like(s)
return a * E[0] * s, a * E[1] * s, p # kinematic pressure, constant
def equilibrium(rho, ux, uy):
# Same second-order D2Q9 equilibrium as oracle.initial.
cu = CX[:, None, None] * ux + CY[:, None, None] * uy
return (
W[:, None, None]
* rho
* (1 + 3 * cu + 4.5 * cu * cu - 1.5 * (ux * ux + uy * uy))
)
def initial(shape, level, length, viscosity):
x, y = centers(shape, level)
ux, uy, p = exact(x, y, 0.0, length, viscosity)
return equilibrium(1 + 3 * p, ux, uy)
def _leaves(arrays, masks):
accum = []
for level, (g, mask) in enumerate(zip(arrays, masks)):
if g.shape != (9, *mask.shape):
raise ValueError("population/mask shape mismatch")
values = g[:, mask].astype(float)
if not np.isfinite(values).all():
raise FloatingPointError("nonfinite leaf populations")
rho = values.sum(axis=0)
if (rho <= 0).any():
raise FloatingPointError("nonpositive leaf density")
x, y = centers(mask.shape, level)
area = np.full(rho.size, 0.25**level)
lev = np.full(rho.size, level)
accum.append((rho, CX @ values / rho, CY @ values / rho, x[mask], y[mask], area, lev))
return [np.concatenate(v) for v in zip(*accum)]
def metrics(arrays, masks, t, length, viscosity, initial_mass=None):
rho, ux, uy, x, y, w, lev = _leaves(arrays, masks)
volume = w.sum()
if not np.isclose(volume, length**2, rtol=0, atol=1e-10):
raise ValueError("leaf partition does not cover domain once")
k = wavevector(length)
theta = k[0] * x + k[1] * y + PHI
s, c = np.sin(theta), np.cos(theta)
v = ux * E[0] + uy * E[1]
# Weighted least squares on the actual composite quadrature (no
# continuous-orthogonality assumption).
gram = np.array([[w @ (s * s), w @ (s * c)], [w @ (s * c), w @ (c * c)]])
a_hat, b_hat = np.linalg.solve(gram, [w @ (v * s), w @ (v * c)])
ex, ey, _ = exact(x, y, t, length, viscosity)
exact_norm = w @ (ex * ex + ey * ey)
fit = a_hat * s + b_hat * c
longitudinal = (ux * k[0] + uy * k[1]) / math.sqrt(k @ k)
amplitude = U * math.exp(-decay_rate(length, viscosity) * t)
scale = amplitude * amplitude / 4 # continuum reference scale, not the TG norm
modal = math.hypot(a_hat, b_hat)
p = (rho - 1) / 3
p = p - w @ p / volume # one global gauge
mass = float(w @ rho)
return dict(
tstar=t * U / length,
mass=mass,
mass_relative=(
0.0 if initial_mass is None else abs(mass - initial_mass) / initial_mass
),
a_hat=float(a_hat),
b_hat=float(b_hat),
amplitude_exact=amplitude,
amplitude_ratio=float(a_hat / amplitude),
modal_amplitude=modal,
amplitude_error=modal / amplitude - 1,
phase_drift=float(math.atan2(b_hat, a_hat)),
phase_drift_abs=abs(float(math.atan2(b_hat, a_hat))),
velocity_l2=float(
np.sqrt(w @ ((ux - ex) ** 2 + (uy - ey) ** 2) / exact_norm)
),
residual_l2=float(
np.sqrt(w @ ((ux - fit * E[0]) ** 2 + (uy - fit * E[1]) ** 2) / exact_norm)
),
longitudinal_l2=float(np.sqrt(w @ (longitudinal**2) / exact_norm)),
spurious_pressure_rms=float(np.sqrt(w @ (p * p) / volume)),
spurious_pressure_scaled=float(np.sqrt(w @ (p * p) / volume) / scale),
spurious_pressure_max_scaled=float(np.max(np.abs(p)) / scale),
spurious_pressure_scaled_by_level=[
float(np.sqrt(w[lev == i] @ (p[lev == i] ** 2) / w[lev == i].sum()) / scale)
for i in range(len(masks))
],
rho_min=float(rho.min()),
rho_max=float(rho.max()),
max_speed=float(np.max(np.hypot(ux, uy))),
leaf_cells=int(len(rho)),
)
def fit_rate(rows, length, viscosity):
"""Free-intercept least squares of ln R, R = hypot(a_hat, b_hat), late samples.
The intercept absorbs only a constant amplitude prefactor once a single
exponential dominates; per-interval rates and the fit residual are kept so
a lingering transient stays visible. Rates are per root step of the record
(uniform 2N uses its own nu and doubled step counts).
"""
late = [r for r in rows if r["tstar"] >= FIT_FROM_TSTAR - 1e-12]
amp = np.array([math.hypot(r["a_hat"], r["b_hat"]) for r in late])
if len(late) < 3 or not np.isfinite(amp).all():
raise ValueError("need >= 3 late samples with finite R")
exact_rate = decay_rate(length, viscosity)
to_tstar = length / U # root steps per unit t*
if not (amp > 0).all():
# Finite modal extinction: a physical failure, not malformed data. No
# clipping and no invented rate; fit quantities are unavailable.
return dict(rate_fit_valid=False, rate=None, exact_rate=exact_rate,
rate_tstar=None, exact_rate_tstar=exact_rate * to_tstar,
rate_error=None, interval_rate_errors=None, log_fit_residual_max=None)
t = np.array([r["step"] for r in late], dtype=float)
(slope, intercept) = np.polyfit(t, np.log(amp), 1)
residual = np.log(amp) - (slope * t + intercept)
return dict(
rate_fit_valid=True, rate=float(-slope), exact_rate=exact_rate,
rate_tstar=float(-slope * to_tstar),
exact_rate_tstar=exact_rate * to_tstar, # = 5 (2 pi)^2 / Re
rate_error=abs(-slope / exact_rate - 1),
interval_rate_errors=[
float(-np.log(amp[i + 1] / amp[i]) / (t[i + 1] - t[i]) / exact_rate - 1)
for i in range(len(t) - 1)
],
log_fit_residual_max=float(np.max(np.abs(residual))),
)
NONNEGATIVE = ("tstar", "mass", "mass_relative", "amplitude_exact", "modal_amplitude",
"phase_drift_abs", "velocity_l2", "residual_l2", "longitudinal_l2",
"spurious_pressure_rms", "spurious_pressure_scaled",
"spurious_pressure_max_scaled", "rho_min", "rho_max", "max_speed")
SIGNED = ("a_hat", "b_hat", "amplitude_ratio", "amplitude_error", "phase_drift")
def _number(value):
return (isinstance(value, (int, float)) and not isinstance(value, bool)
and math.isfinite(value))
def validate_rows(record):
"""Exact schedule, finite numbers (incl. lists) and nonnegative error fields.
Signed quantities (amplitudes, amplitude/phase errors) keep their sign.
Raises ValueError so callers can report an invalid run before any screen.
"""
n, rows = record["n"], record["rows"]
steps = [round(tstar * n / U) for tstar in TIMES]
if not isinstance(rows, list) or len(rows) != len(steps):
raise ValueError("rows do not match the scheduled samples")
for row, step in zip(rows, steps):
if type(row.get("step")) is not int or row["step"] != step:
raise ValueError(f"unscheduled or duplicate step {row.get('step')!r}")
if not _number(row.get("tstar")) or abs(row["tstar"] - step * U / n) > 3e-17:
raise ValueError(f"wrong sample time at step {step}")
if not all(_number(row.get(key)) for key in (*NONNEGATIVE, *SIGNED)):
raise ValueError(f"missing or nonfinite diagnostic at step {step}")
if any(row[key] < 0 for key in NONNEGATIVE) or row["rho_min"] <= 0:
raise ValueError(f"negative error quantity or density at step {step}")
levels = row.get("spurious_pressure_scaled_by_level")
if (not isinstance(levels, list) or len(levels) != record["depth"]
or not all(_number(v) and v >= 0 for v in levels)):
raise ValueError(f"invalid per-level pressure at step {step}")
def summarize(record):
validate_rows(record)
rows = record["rows"]
n = record["n"]
out = fit_rate(rows, n, record["viscosity"])
out.update(
eps=eps(n),
complete=record["completed"] is True,
residual_l2=max(r["residual_l2"] for r in rows),
phase_drift_abs=max(r["phase_drift_abs"] for r in rows),
spurious_pressure_scaled=max(r["spurious_pressure_scaled"] for r in rows),
spurious_pressure_rms=max(r["spurious_pressure_rms"] for r in rows),
amplitude_error_abs=max(abs(r["amplitude_error"]) for r in rows),
velocity_l2=max(r["velocity_l2"] for r in rows),
mass_relative=max(r["mass_relative"] for r in rows),
)
if out["rate_fit_valid"] and not all(
_number(v) for v in (out["rate"], out["rate_error"], *out["interval_rate_errors"],
out["log_fit_residual_max"])):
raise ValueError("nonfinite rate fit")
out["own_screens_pass"] = out["complete"] and out["rate_fit_valid"] and all(
out[key] <= out["eps"] for key in ("rate_error", "phase_drift_abs", "residual_l2")
) and all(out[key] <= limit for key, limit in LIMITS.items())
return out
def _usable(record):
try:
out = summarize(record)
except (KeyError, TypeError, ValueError):
return None
return out if out["complete"] else None
def assess(base_control, fine_control, refined):
"""Uniform root-spacing and finest-spacing controls versus refined runs.
INVALID_CONTROL: missing, incomplete, invalid-row or mixed-source controls.
INVALID_RUN: a refined record has invalid rows (schedule, NaN, sign).
CONTROL_SCREEN_FAIL: complete valid controls that fail their own screens;
refined own-screen results are kept, but no controlled comparison passes.
PASS/FAIL: every refined run's controlled_pass (own screens and budgets).
"""
if base_control is None or fine_control is None or not refined:
return dict(status="INVALID_CONTROL", reason="missing control or refined run")
n = base_control["n"]
if (base_control["depth"], fine_control["depth"], fine_control["n"]) != (1, 1, 2 * n):
raise ValueError("controls must be uniform N and uniform 2N")
if any(r["depth"] != 2 or r["n"] != n for r in refined):
raise ValueError("refined runs must be depth 2 at root N")
if len({r.get("explosion") for r in refined}) != len(refined):
raise ValueError("duplicate refined explosion scheme")
sources = {repr(r.get("source")) for r in [base_control, fine_control, *refined]}
base, fine = _usable(base_control), _usable(fine_control)
if base is None or fine is None or len(sources) != 1:
return dict(status="INVALID_CONTROL",
reason="incomplete/invalid control or mixed source")
controls_pass = base["own_screens_pass"] and fine["own_screens_pass"]
report = dict(base_control=base, fine_control=fine, refined={},
controls_pass=controls_pass)
statuses = []
for r in refined:
try:
s = summarize(r)
except (KeyError, TypeError, ValueError) as error:
report["refined"][r["explosion"]] = dict(valid=False, reason=str(error))
statuses.append("INVALID_RUN")
continue
s["valid"] = True
# rate_error is None when a modal fit is unavailable; never a pass.
s["budget"] = {
key: (None if base[key] is None else max(BASELINE_FACTOR * base[key], floor))
for key, floor in FLOORS.items()
}
s["budget_pass"] = all(
s[key] is not None and s["budget"][key] is not None and s[key] <= s["budget"][key]
for key in FLOORS)
s["control_ratios"] = {
name: {key: (s[key] / c[key] if s[key] is not None and c[key] else None)
for key in (*FLOORS, "spurious_pressure_rms")}
for name, c in (("root", base), ("finest", fine))
}
s["controlled_pass"] = controls_pass and s["own_screens_pass"] and s["budget_pass"]
report["refined"][r["explosion"]] = s
statuses.append("PASS" if s["controlled_pass"] else "FAIL")
if "INVALID_RUN" in statuses:
report["status"] = "INVALID_RUN"
elif not controls_pass:
report["status"] = "CONTROL_SCREEN_FAIL"
else:
report["status"] = "PASS" if all(v == "PASS" for v in statuses) else "FAIL"
return report
@@ -319,7 +319,7 @@ class ProjectedPairsTests(unittest.TestCase):
patch.object(run_case, "runtime_identity", side_effect=AssertionError("CUDA reached")), \
redirect_stdout(stdout):
self.assertEqual(run_case.main(), 0)
verify.assert_called_once_with(REPO, MOCK_REVISION)
verify.assert_called_once_with(REPO, MOCK_REVISION, "taylor_green")
self.assertTrue(json.loads(stdout.getvalue())["dry_run"])
self.assertFalse(output.exists())
@@ -412,7 +412,7 @@ class ProjectedPairsTests(unittest.TestCase):
else:
self.assertEqual(run_case.main(), 0)
receipt = json.loads(output.read_text())
verify.assert_called_once_with(REPO, MOCK_REVISION)
verify.assert_called_once_with(REPO, MOCK_REVISION, "taylor_green")
self.assertEqual(selectors, ["projected_linear" if early else "constant"] if depth == 2 else [])
self.assertEqual(receipt["source"], source())
self.assertEqual(receipt["runtime_identity"], RUNTIME)
@@ -0,0 +1,471 @@
"""Standalone CPU manufactured checks for the oblique shear wave.
Run from this directory with PYTHONPATH=<checkout>/src (same as test_oracle.py).
"""
import hashlib
import json
import math
import unittest
from pathlib import Path
import numpy as np
import oracle
import run_case
import shear_wave as sw
from oracle import CX, CY, U, TIMES, centers, rectangles
N = 32
NU = U * N / sw.RE
HERE = Path(__file__).resolve().parent
ORACLE_SHA256_EEC4677 = "83e4d7425d45538278e9fb181af450a36358bd9a5ed6be57ff611dd9ae5eb35b"
def composite_masks(n):
"""Level-wide union masks for rectangles(n, 2): root complement + fine box."""
(x0, y0, x1, y1), = rectangles(n, 2)[0]
root = np.ones((n, n), dtype=bool)
root[y0:y1, x0:x1] = False
fine = np.zeros((2 * n, 2 * n), dtype=bool)
fine[2 * y0:2 * y1, 2 * x0:2 * x1] = True
return [root, fine]
def populations(masks, field, t=0.0):
"""Equilibrium G of an arbitrary (ux, uy, rho) field on every level."""
out = []
for level, m in enumerate(masks):
x, y = centers(m.shape, level)
ux, uy, rho = field(x, y, t)
out.append(sw.equilibrium(rho, ux, uy))
return out
def exact_field(phase=0.0, rate_factor=1.0, mode=sw.MODE, longitudinal=0.0, ripple=0.0,
offset=0.0):
k = 2 * np.pi / N * np.array(mode, dtype=float)
e = np.array([-mode[1], mode[0]], dtype=float) / math.hypot(*mode)
rate = rate_factor * sw.decay_rate(N, NU)
kh = k / np.linalg.norm(k)
def field(x, y, t):
theta = k[0] * x + k[1] * y + phase
a = U * np.exp(-rate * t)
ux = a * e[0] * np.sin(theta) + longitudinal * kh[0] * np.sin(theta)
uy = a * e[1] * np.sin(theta) + longitudinal * kh[1] * np.sin(theta)
rho = 1 + offset + ripple * np.cos(theta)
return ux, uy, rho
return field
class ConventionTests(unittest.TestCase):
def test_mode_angle_and_polarization(self):
k = sw.wavevector(N)
self.assertAlmostEqual(sw.ANGLE_DEG, 26.565051177077994)
self.assertAlmostEqual(math.degrees(math.atan2(k[1], k[0])), sw.ANGLE_DEG)
self.assertAlmostEqual(float(sw.E @ k), 0.0)
self.assertAlmostEqual(float(sw.E @ sw.E), 1.0)
self.assertAlmostEqual(sw.eps(128), 5 * (2 * math.pi / 128) ** 2)
def test_navier_stokes_and_vanishing_advection(self):
# Independent central differences: du/dt = nu lap u, (u.grad)u = 0, div u = 0.
x = np.array([2.7, 8.1, 13.3])
y = np.array([3.2, 7.4, 21.6])
t, h = 10.0, 1e-3
f = lambda x, y, t: np.array(sw.exact(x, y, t, N, NU)[:2])
z = f(x, y, t)
dt = (f(x, y, t + h) - f(x, y, t - h)) / (2 * h)
dx = (f(x + h, y, t) - f(x - h, y, t)) / (2 * h)
dy = (f(x, y + h, t) - f(x, y - h, t)) / (2 * h)
lap = (f(x + h, y, t) + f(x - h, y, t) + f(x, y + h, t) + f(x, y - h, t) - 4 * z) / h**2
np.testing.assert_allclose(dt, NU * lap, atol=1e-9)
# Analytic identities: div u = A cos(theta) (E.k) and (u.grad)u = A sin(theta) (E.k) u/A.
k = sw.wavevector(N)
self.assertLess(abs(float(sw.E @ k)), 1e-17)
# Central differences do not cancel exactly: each derivative carries
# -(k_j h)^2/6 relative truncation, so div_h = -A cos(theta) h^2/6 sum_j E_j k_j^3
# + O(h^4) (nonzero for an oblique k). Bound it with that leading term plus roundoff.
a = U * math.exp(-sw.decay_rate(N, NU) * t)
trunc = a * h * h / 6 * float(np.abs(sw.E * k**3).sum()) * 1.01
# Argument rounding: eps*max|x|/h*U*|k| ~ 2.2e-16*21.6/1e-3*0.03*0.44 ~ 6e-14.
roundoff = 1e-13
self.assertLess(np.max(np.abs(dx[0] + dy[1])), trunc + roundoff)
# Discrete advection: same truncation scaled by |u| <= a.
self.assertLess(np.max(np.abs(z[0] * dx + z[1] * dy)), a * trunc + roundoff)
# Halving h reduces the divergence truncation about fourfold.
hh = h / 2
div2 = ((f(x + hh, y, t) - f(x - hh, y, t))[0] + (f(x, y + hh, t) - f(x, y - hh, t))[1]) / (2 * hh)
np.testing.assert_allclose(div2 * 4, dx[0] + dy[1], rtol=1e-2, atol=6 * roundoff)
self.assertTrue(np.all(sw.exact(x, y, t, N, NU)[2] == 0))
class InitialTests(unittest.TestCase):
def test_moments_on_each_level(self):
for level, m in enumerate(composite_masks(N)):
g = sw.initial(m.shape, level, N, NU)
x, y = centers(m.shape, level)
ux, uy, _ = sw.exact(x, y, 0.0, N, NU)
rho = g.sum(axis=0)
np.testing.assert_allclose(rho, 1.0, atol=1e-14)
np.testing.assert_allclose(np.tensordot(CX, g, 1) / rho, ux, atol=1e-15)
np.testing.assert_allclose(np.tensordot(CY, g, 1) / rho, uy, atol=1e-15)
def test_equilibrium_matches_frozen_oracle_formula(self):
# Same equilibrium as oracle.initial when fed the TG field.
shape = (8, 8)
x, y = centers(shape, 1)
ux, uy, p = oracle.exact(x, y, 0.0, 4.0, 0.01)
np.testing.assert_array_equal(
sw.equilibrium(1 + 3 * p, ux, uy), oracle.initial(shape, 1, 4.0, 0.01)
)
class MetricTests(unittest.TestCase):
def setUp(self):
self.masks = composite_masks(N)
def sample(self, field, t):
return sw.metrics(populations(self.masks, field, t), self.masks, t, N, NU, None)
def test_exact_field_on_composite_partition(self):
for t in (0.0, 100.0, 512.0):
r = self.sample(exact_field(), t)
self.assertLess(r["velocity_l2"], 1e-12)
self.assertLess(r["residual_l2"], 1e-12)
self.assertLess(r["longitudinal_l2"], 1e-12)
self.assertLess(r["phase_drift_abs"], 1e-12)
self.assertAlmostEqual(r["amplitude_ratio"], 1.0, places=12)
self.assertLess(abs(r["amplitude_error"]), 1e-12)
self.assertLess(r["spurious_pressure_scaled"], 1e-10)
self.assertEqual(len(r["spurious_pressure_scaled_by_level"]), 2)
self.assertEqual(r["leaf_cells"], int(sum(m.sum() for m in self.masks)))
def test_phase_control(self):
r = self.sample(exact_field(phase=0.01), 0.0)
self.assertAlmostEqual(r["phase_drift"], 0.01, delta=1e-9)
self.assertLess(abs(r["amplitude_error"]), 1e-12) # R = hypot(a, b) is phase-free
self.assertLess(r["residual_l2"], 1e-12) # a pure phase shift stays modal
def test_rate_control_and_fit(self):
for factor, expected in ((1.0, 0.0), (1.01, 0.01)):
field = exact_field(rate_factor=factor)
rows = []
for tstar in TIMES:
step = round(tstar * N / U)
rows.append(dict(self.sample(field, step), step=step))
fit = sw.fit_rate(rows, N, NU)
self.assertAlmostEqual(fit["rate_error"], expected, delta=1e-9)
np.testing.assert_allclose(fit["interval_rate_errors"], expected, atol=1e-9)
self.assertLess(fit["log_fit_residual_max"], 1e-9)
self.assertAlmostEqual(fit["exact_rate_tstar"], 5 * (2 * math.pi) ** 2 / sw.RE)
self.assertAlmostEqual(fit["exact_rate_tstar"], 1.97392088, places=8)
def test_fit_ignores_startup_sample(self):
rows = [dict(tstar=0.0, step=0, a_hat=2 * U, b_hat=0.0)]
rows += [dict(tstar=s, step=round(s * N / U), b_hat=0.0,
a_hat=U * math.exp(-sw.decay_rate(N, NU) * round(s * N / U)))
for s in TIMES[1:]]
self.assertLess(sw.fit_rate(rows, N, NU)["rate_error"], 1e-12)
rows[-1]["a_hat"] = float("nan")
with self.assertRaises(ValueError):
sw.fit_rate(rows, N, NU)
def test_wrong_mode_control(self):
# Swapping (2,1) for (1,2), i.e. 26.6 vs 63.4 deg, is not silently modal.
# Composite quadrature need not give an exactly zero projection.
r = self.sample(exact_field(mode=(1, 2)), 0.0)
self.assertLess(abs(r["amplitude_ratio"]), 0.05)
self.assertGreater(r["residual_l2"], 0.95)
def test_longitudinal_control(self):
r = self.sample(exact_field(longitudinal=1e-3), 0.0)
self.assertAlmostEqual(r["longitudinal_l2"], 1e-3 / U, delta=1e-9)
# The full-vector residual and velocity error see it too.
self.assertAlmostEqual(r["residual_l2"], 1e-3 / U, delta=1e-9)
self.assertAlmostEqual(r["velocity_l2"], 1e-3 / U, delta=1e-9)
self.assertLess(r["phase_drift_abs"], 1e-12)
self.assertAlmostEqual(r["amplitude_ratio"], 1.0, places=12)
def test_pressure_gauge_and_ripple(self):
r = self.sample(exact_field(offset=1e-4), 0.0)
self.assertLess(r["spurious_pressure_scaled"], 1e-10) # one global gauge
ripple = 3e-5
r = self.sample(exact_field(ripple=ripple), 0.0)
# p = ripple/3 cos(theta); rms over a whole number of periods = ripple/(3 sqrt 2).
# Composite midpoint quadrature is not exactly periodic: 3% tolerance.
expected = ripple / (3 * math.sqrt(2)) / (U * U / 4)
self.assertAlmostEqual(r["spurious_pressure_scaled"], expected, delta=0.03 * expected)
self.assertAlmostEqual(r["spurious_pressure_rms"], expected * U * U / 4,
delta=0.03 * expected * U * U / 4)
def test_volume_weighting_and_double_count(self):
bad = [np.ones_like(m) for m in self.masks]
with self.assertRaises(ValueError):
sw.metrics(populations(bad, exact_field()), bad, 0.0, N, NU)
# Unweighted (count-based) averaging would change the fit; weights matter.
r = self.sample(exact_field(), 0.0)
self.assertEqual(r["leaf_cells"], N * N - self.masks[1].sum() // 4 + self.masks[1].sum())
def record(n, depth, rows, explosion="constant", completed=True, source="s"):
for row in rows:
row["spurious_pressure_scaled_by_level"] = [row["spurious_pressure_scaled"]] * depth
return dict(n=n, depth=depth, viscosity=U * n / sw.RE, rows=rows, completed=completed,
explosion=explosion, source=source)
def rows_for(n, rate_error=0.0, residual=1e-4, pressure=1e-3, phase=0.0):
rate = (1 + rate_error) * sw.decay_rate(n, U * n / sw.RE)
out = []
for tstar in TIMES:
step = round(tstar * n / U)
amp = U * math.exp(-rate * step)
out.append(dict(tstar=step * U / n, step=step, a_hat=amp, b_hat=0.0,
amplitude_ratio=1.0, modal_amplitude=amp, amplitude_exact=amp,
phase_drift=phase, mass=float(n * n), rho_min=0.999, rho_max=1.001,
max_speed=amp, longitudinal_l2=0.0, spurious_pressure_max_scaled=pressure,
amplitude_error=0.0, residual_l2=residual, phase_drift_abs=phase,
spurious_pressure_scaled=pressure,
spurious_pressure_rms=pressure * U * U / 4,
velocity_l2=residual, mass_relative=0.0))
return out
class AssessTests(unittest.TestCase):
def test_budget_form_is_max_not_sum(self):
base = record(128, 1, rows_for(128, rate_error=1e-3, pressure=0.015))
fine = record(256, 1, rows_for(256, rate_error=2e-4))
# rate budget = max(2*1e-3, 0.002) = 0.002; 0.0025 would pass a sum form.
refined = record(128, 2, rows_for(128, rate_error=0.0025))
report = sw.assess(base, fine, [refined])
self.assertEqual(report["status"], "FAIL")
self.assertAlmostEqual(report["refined"]["constant"]["budget"]["rate_error"], 0.002)
# pressure budget = max(2*0.015, 0.02) = 0.03 (control-dominated).
self.assertAlmostEqual(
report["refined"]["constant"]["budget"]["spurious_pressure_scaled"], 0.03)
self.assertIn("finest", report["refined"]["constant"]["control_ratios"])
ok = record(128, 2, rows_for(128, rate_error=0.0015), explosion="projected_linear")
self.assertEqual(sw.assess(base, fine, [ok])["status"], "PASS")
def test_control_outcomes_are_distinct(self):
fine = record(256, 1, rows_for(256))
refined = record(128, 2, rows_for(128))
failing = record(128, 1, rows_for(128, residual=0.5)) # complete, > eps(128)
report = sw.assess(failing, fine, [refined])
self.assertEqual(report["status"], "CONTROL_SCREEN_FAIL")
own = report["refined"]["constant"]
self.assertTrue(own["own_screens_pass"]) # refined own screens kept
self.assertFalse(own["controlled_pass"]) # but no controlled comparison passes
good = record(128, 1, rows_for(128))
self.assertEqual(sw.assess(None, fine, [refined])["status"], "INVALID_CONTROL")
incomplete = record(128, 1, rows_for(128), completed=False)
self.assertEqual(sw.assess(incomplete, fine, [refined])["status"], "INVALID_CONTROL")
mixed = record(256, 1, rows_for(256), source="other")
self.assertEqual(sw.assess(good, mixed, [refined])["status"], "INVALID_CONTROL")
def test_invalid_rows_are_rejected_before_screens(self):
base = record(128, 1, rows_for(128))
fine = record(256, 1, rows_for(256))
for mutate in (
lambda rows: rows[2].update(rho_min=float("nan")),
lambda rows: rows[2].update(spurious_pressure_scaled_by_level=[0.0, float("nan")]),
lambda rows: rows[2].update(step=rows[1]["step"], tstar=rows[1]["tstar"]),
lambda rows: rows[2].update(residual_l2=-1e-6),
lambda rows: rows[2].pop("longitudinal_l2"),
):
refined = record(128, 2, rows_for(128))
mutate(refined["rows"])
self.assertEqual(sw.assess(base, fine, [refined])["status"], "INVALID_RUN")
# Legitimate signs stay allowed: negative amplitude and phase errors.
refined = record(128, 2, rows_for(128))
for row in refined["rows"]:
row.update(amplitude_error=-1e-3, phase_drift=-1e-4, phase_drift_abs=1e-4)
report = sw.assess(base, fine, [refined])
self.assertEqual(report["status"], "PASS")
self.assertEqual(sw.assess(base, fine, [])["status"], "INVALID_CONTROL")
with self.assertRaises(ValueError):
sw.assess(base, fine, [record(128, 2, rows_for(128)), record(128, 2, rows_for(128))])
def test_modal_extinction_is_a_failure_not_malformed(self):
def extinct(rows):
for row in rows[1:]:
row.update(a_hat=0.0, b_hat=0.0, modal_amplitude=0.0, amplitude_ratio=0.0,
amplitude_error=-1.0)
return rows
base = record(128, 1, rows_for(128))
fine = record(256, 1, rows_for(256))
refined = record(128, 2, extinct(rows_for(128)))
report = sw.assess(base, fine, [refined])
self.assertEqual(report["status"], "FAIL")
own = report["refined"]["constant"]
self.assertTrue(own["valid"])
self.assertFalse(own["rate_fit_valid"])
self.assertIsNone(own["rate_error"])
self.assertIsNone(own["control_ratios"]["root"]["rate_error"])
self.assertFalse(own["own_screens_pass"] or own["controlled_pass"] or own["budget_pass"])
self.assertEqual(own["residual_l2"], 1e-4) # other finite metrics retained
json.loads(json.dumps(report, allow_nan=False))
control = sw.assess(record(128, 1, extinct(rows_for(128))), fine,
[record(128, 2, rows_for(128))])
self.assertEqual(control["status"], "CONTROL_SCREEN_FAIL")
self.assertIsNone(control["refined"]["constant"]["budget"]["rate_error"])
self.assertFalse(control["refined"]["constant"]["controlled_pass"])
json.loads(json.dumps(control, allow_nan=False))
def test_wrong_shapes(self):
base = record(128, 1, rows_for(128))
fine = record(256, 1, rows_for(256))
refined = record(128, 2, rows_for(128))
with self.assertRaises(ValueError):
sw.assess(base, record(128, 1, rows_for(128)), [refined])
with self.assertRaises(ValueError):
sw.assess(record(128, 1, rows_for(128)), fine, [record(256, 2, rows_for(256))])
def test_incomplete_record_fails(self):
base = record(128, 1, rows_for(128))
fine = record(256, 1, rows_for(256))
refined = record(128, 2, rows_for(128), completed=False)
self.assertEqual(sw.assess(base, fine, [refined])["status"], "FAIL")
class FakeRun:
def __init__(self, arrays):
self.arrays = arrays
def download(self):
return self.arrays if len(self.arrays) > 1 else self.arrays[0]
class RunnerSampleTests(unittest.TestCase):
def test_refined_shear_sample_with_list_diagnostics(self):
masks = composite_masks(N)
arrays = [sw.initial(m.shape, level, N, NU) for level, m in enumerate(masks)]
row = run_case.sample(FakeRun(arrays), masks, 0, N, NU, None, sw.metrics, 2)
self.assertIsInstance(row["spurious_pressure_scaled_by_level"], list)
self.assertTrue(run_case.finite_row(row))
bad = [a.copy() for a in arrays]
bad[1][0, masks[1]] = np.nan
with self.assertRaises(FloatingPointError):
run_case.sample(FakeRun(bad), masks, 0, N, NU, None, sw.metrics, 2, "READY")
self.assertFalse(run_case.finite_row(dict(a=1.0, b=[0.0, float("inf")])))
def test_taylor_green_sample_unchanged(self):
masks = composite_masks(N)
arrays = [oracle.initial(m.shape, level, N, NU) for level, m in enumerate(masks)]
row = run_case.sample(FakeRun(arrays), masks, 0, N, NU, None, oracle.metrics, 2)
self.assertEqual(row, oracle.metrics(arrays, masks, 0, N, NU, None))
uniform = [oracle.initial((N, N), 0, N, NU)]
row = run_case.sample(FakeRun(uniform), [np.ones((N, N), bool)], 0, N, NU, None,
oracle.metrics, 1)
self.assertEqual(row["leaf_cells"], N * N)
def receipt(n, depth, explosion="constant"):
"""Synthetic receipt satisfying every contract field of the fixed four-case set."""
import assess_projected_pairs as tg
steps = run_case.sample_steps(n)[0]
rows = rows_for(n)
for row, step in zip(rows, steps):
row.update(step=step, tstar=step * U / n,
spurious_pressure_scaled_by_level=[row["spurious_pressure_scaled"]] * depth)
cells = [n * n] if depth == 1 else [8704, 30720]
hops = [16 * n * 2**level for level in range(depth)]
builds = []
for level in range(depth):
size = n * 2**level
builds.append(dict(source_sha256=tg.BUILD_SOURCES[size], arch="sm_70",
flags=["--use_fast_math"], n_objects=0, ptx_sha256="a" * 64,
config=dict(nx=10, ny=10, nz=1, lattice_model="D2Q9", collision="SRT",
store_precision="FP32", streaming="double_buffer",
ddf_shifting=True, les_enabled=False, velocity=0.0,
viscosity=U * size / 100, rho=1.0,
omega=1 / (.5 + 3 * U * size / 100),
threads_per_block=256)))
checkout = "/x/CelerisLab"
return dict(
n=n, depth=depth, re_L=100, explosion=explosion, U=U, mach=U * math.sqrt(3),
viscosity=U * n / 100, tau_by_level=[0.5 + 3 * U * n / 100 * 2**l for l in range(depth)],
source=dict(revision="r", dirty=False, source_tree_sha256=run_case.SOURCE_SHA256,
harness_sha256={"x.py": "h"}, build_capture_sha256=run_case.BUILD_CAPTURE_SHA256,
shear_wave_sha256=run_case.SHEAR_WAVE_SHA256),
runtime_identity=dict(device=dict(name="V100", pci_bus_id="0", capability=[7, 0],
driver=1, runtime=[12, 0]),
nvcc_path="/nvcc", nvcc_version="v", python="3", numpy="1",
pycuda="2"),
runtime_source=dict(checkout=checkout, module=checkout + "/src/CelerisLab/__init__.py",
compiler=checkout + "/src/CelerisLab/cuda/compiler_v2.py",
kernel_root=checkout + "/src/CelerisLab/lbm/kernels"),
cuda_visible_devices="0", numerical_revision=run_case.NUMERICAL_REVISION,
reference_harness=run_case.REFERENCE_HARNESS, numerics=dict(tg.NUMERICS),
initialization=sw.INITIALIZATION, limits=dict(sw.LIMITS),
early_pressure=dict(enabled=False, rows=[], sampled_max_pressure_l2=None),
refinements=[] if depth == 1 else rectangles(n, depth),
workload=dict(active_cells_by_level=cells, level_hops=hops, root_intervals=16 * n,
active_collision_updates_by_level=[c * h for c, h in zip(cells, hops)],
active_collision_updates=sum(c * h for c, h in zip(cells, hops))),
actual_build_sidecars=builds, rows=rows, completed=True,
flow="shear_wave", mode=list(sw.MODE), polarization=sw.E.tolist(),
angle_deg=sw.ANGLE_DEG, phase=sw.PHI, eps=sw.eps(n))
class ContractTests(unittest.TestCase):
def setUp(self):
import assess_shear_wave
self.assess = assess_shear_wave.assess
self.records = [receipt(128, 1), receipt(256, 1), receipt(128, 2),
receipt(128, 2, "projected_linear")]
def test_complete_contract_passes(self):
result = self.assess(self.records, "r")
self.assertTrue(result["contract_valid"], [k for k, v in result["checks"].items() if not v])
self.assertEqual(result["status"], "PASS")
def test_reproduced_false_passes_are_rejected(self):
a = self.assess
self.assertEqual(a(self.records[:2], "r")["status"], "INVALID_SET") # empty refined
dup = [*self.records[:3], receipt(128, 2)]
self.assertEqual(a(dup, "r")["status"], "INVALID_SET") # duplicate constant-only
for mutate in (
lambda r: r.pop("source"),
lambda r: r.update(flow="taylor_green"),
lambda r: r.update(mode=[1, 2]),
lambda r: r.update(re_L=1000),
lambda r: r.update(refinements=[[(0, 0, 8, 8)]]),
lambda r: r["actual_build_sidecars"][0].update(arch="sm_80"),
lambda r: r["rows"][0].update(step=1, tstar=U / 128), # wrong initial time
lambda r: r["source"].update(shear_wave_sha256="0" * 64),
):
records = [dict(r, rows=[dict(x) for x in r["rows"]],
source=dict(r["source"]),
actual_build_sidecars=[dict(b) for b in r["actual_build_sidecars"]])
for r in self.records]
mutate(records[2])
self.assertEqual(a(records, "r")["status"], "INVALID_SET")
mixed = [dict(r) for r in self.records]
mixed[1] = dict(mixed[1], source=dict(mixed[1]["source"], revision="other"))
self.assertEqual(a(mixed, "r")["status"], "INVALID_SET")
self.assertEqual(a(self.records, "wrong-revision")["status"], "INVALID_SET")
class DefaultPathTests(unittest.TestCase):
def test_frozen_oracle_is_byte_identical(self):
digest = hashlib.sha256((HERE / "oracle.py").read_bytes()).hexdigest()
self.assertEqual(digest, ORACLE_SHA256_EEC4677)
def test_default_flow_is_frozen_taylor_green(self):
init, met, limits, text = run_case.flow_functions()
self.assertIs(init, oracle.initial)
self.assertIs(met, oracle.metrics)
self.assertIs(limits, oracle.LIMITS)
self.assertEqual(text, run_case.INITIALIZATION)
self.assertEqual(run_case.flow_functions("taylor_green"), (init, met, limits, text))
shear = run_case.flow_functions("shear_wave")
self.assertIs(shear[0], sw.initial)
self.assertIs(shear[1], sw.metrics)
with self.assertRaises(ValueError):
run_case.flow_functions("tg")
if __name__ == "__main__":
unittest.main()